KR102655382B1 - Method, apparatus and program for providing made-to-order service of customized bed - Google Patents

Abstract

A method of providing a customized bed custom manufacturing service according to various embodiments of the present invention is disclosed. The method includes: obtaining order information related to a customized bed from a user terminal; generating production information based on the order information; Transmitting the production information to an external server related to the production of a bed, requesting production of the customized bed corresponding to the production information; After requesting the production, obtaining production status information about the customized bed from the external server; And when it is recognized that production of the customized bed has been completed based on the production status information, requesting delivery to the external server to deliver the bed to a delivery address corresponding to the order information.

Description

Method, apparatus and program for providing custom bed customization service {METHOD, APPARATUS AND PROGRAM FOR PROVIDING MADE-TO-ORDER SERVICE OF CUSTOMIZED BED}

The present invention relates to a method, device, and program for providing a customized bed customization service. Specifically, the present invention relates to a method, device, and program for providing a customized bed customization service for receiving options from a user and manufacturing a customized bed according to the selected option. will be.

As the number of single-person households increases, lifestyle becomes more important, and interest in personal space increases along with the popularization of interior design, the various home furnishing markets are expanding.

Home furnishing is a compound word of home and furnishing, and refers to decorating a house with furniture and lighting as well as wallpaper, bedding, carpets, and interior accessories.

Among the words that reflect recent consumption trends, there is a new word called ‘Nana Land.’ It means escaping from other people's opinions or prejudices and consuming as the protagonist of the world. The industry has paid attention to individual 'tastes' from an early age, and home furnishing services tailored to consumers' tastes have been popular in the living industry for a long time.

You can not only create your own product by choosing furniture material, design, and color, but also create spaces such as the kitchen, living room, and bathroom according to your taste.

Recently, interest in custom-made and made-to-order consumption structures has been increasing in online business.

Various companies are increasing consumer satisfaction, increasing sales, and creating new consumption structures by introducing customization methods that provide customized services that directly reflect users' usage methods and preferences.

However, distributed furniture brands have limitations in expressing taste and individuality, and it is difficult to take into account the space where they will be installed, individual tastes, and lifestyles.

In addition, there is a problem in that it is difficult for small-scale furniture design and manufacturing companies to increase sales in the furniture market's consumption structure, which is dominated by a standardized, large-scale distribution structure.

Accordingly, there is a need in the industry for a method of providing custom bed customization services. In this regard, Republic of Korea Patent Publication No. 10-1670462 discloses a customer-customized multi-bed.

The present invention was conceived in response to the above-described background technology and is intended to provide a method, device, and program for providing a customized bed custom manufacturing service.

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

According to an embodiment of the present invention for solving the above-described problem, a method of providing a customized bed custom manufacturing service is disclosed. The method includes: obtaining order information related to a customized bed from a user terminal; generating production information based on the order information; Transmitting the production information to an external server related to the production of a bed, requesting production of the customized bed corresponding to the production information; After requesting the production, obtaining production status information about the customized bed from the external server; And when it is recognized that production of the customized bed has been completed based on the production status information, requesting delivery to the external server to deliver the bed to a delivery address corresponding to the order information.

In an alternative embodiment, obtaining order information related to a customized bed from a user terminal includes obtaining a first selection input for selecting one type from a plurality of preset bed types; providing an option list corresponding to a specific type corresponding to the first selection input and an item list from which one item can be selected for each of a plurality of options included in the option list; Obtaining a second selection input for selecting one item from the list of items for each of the plurality of options; If there is an unselected option in which one of the plurality of options is not selected, determining a recommended item for the unselected option based on the remaining options in which one of the plurality of options is selected; and providing the recommended item to the user terminal and obtaining a third selection input for applying or selecting the recommended item.

In an alternative embodiment, the step of obtaining a second selection input for selecting one item from the list of items for each of the plurality of options may include selecting any one item related to at least one option among the plurality of options. When selected, inputting information about the selected item into a pre-trained neural network model corresponding to the specific type; Obtaining a score value for each item corresponding to each of the remaining options for which no item is selected from the pre-trained neural network model; and rearranging the item list of each of the remaining options in which any one of the items is not selected in descending order of the score value for each item.

In an alternative embodiment, when there is an unselected option in which one of the plurality of options is not selected, the step of determining a recommended item for the unselected option based on the remaining options for which one of the plurality of options is selected includes the steps of: Inputting information about an item selected from each of the remaining options in which one item is selected into a pre-trained neural network model corresponding to a specific type; Obtaining a score value for each item corresponding to each unselected option in which any one item is not selected from the pre-trained neural network model; and determining the recommended item based on the score value for each item.

In an alternative embodiment, the method includes obtaining order history for each of the preset plurality of bed types; Recognizing selected items for a plurality of options included in an option list for each bed type, based on the preset order history for each bed type; Generating learning data for each of the plurality of preset bed types by labeling each item selected for each of the plurality of options; And using the learning data, training a neural network model for each of the plurality of preset bed types, wherein each of the selected items for each of the plurality of options is labeled in the neural network model for each of the plurality of preset bed types. The higher the number of times it is done, the higher the score can be output.

In an alternative embodiment, the method includes: upon obtaining the order information, generating a virtual image of a custom bed corresponding to the order information; After delivery of the customized bed corresponding to the order information is completed, obtaining a review image of the customized bed from the user terminal; generating an image set by mapping the virtual image and the review image of the bed; and providing the image set to another user terminal, and providing a reward to the user terminal when a new order related to the image set is received from the other user terminal.

In an alternative embodiment, obtaining order information related to a customized bed from a user terminal includes: obtaining information about a housing type of a user of the customized bed from the user terminal; And based on the information about the housing type, determining an installation method of the customized bed; wherein the production information may include the installation method.

In an alternative embodiment, the method includes obtaining inventory and prices of each of a plurality of raw materials available for manufacturing the custom bed; Recognizing a first raw material whose inventory amount exceeds a preset quantity among the plurality of raw materials; Recognizing a second raw material among the plurality of raw materials whose price has been reduced by more than a preset amount compared to the previous price; And generating discount information applying a preset discount rate to the price of each option and bed type in which at least one of the first raw material and the second raw material is used; further comprising, ordering related to a customized bed from the user terminal. In the information acquisition step, the discount information may be provided to the user terminal.

According to one embodiment of the present invention for solving the above-described problems, a device is disclosed. The device includes: a memory storing one or more instructions; and a processor executing the one or more instructions stored in the memory, and the processor may perform the above-described methods by executing the one or more instructions.

According to an embodiment of the present invention for solving the above-described problem, a computer program is disclosed that is combined with a computer as hardware and stored in a computer-readable recording medium to perform the above-described methods.

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

The present invention provides a service in which various options related to bed production are selected by the user and a customized bed is custom-made according to the selected options, so that a bed that reflects the user's needs can be custom-made.

The 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 description below.

1 is a diagram illustrating a system according to an embodiment of the present invention.
Figure 2 is a hardware configuration diagram of a computing device according to an embodiment of the present invention.
Figure 3 is a flowchart illustrating an example of a method of providing a customized bed custom manufacturing service according to an embodiment of the present invention.
Figure 4 is a flowchart illustrating an example of a method for obtaining order information according to an embodiment of the present invention.
Figure 5 is a flowchart illustrating an example of a method for rearranging an option item list according to an embodiment of the present invention.
Figure 6 is a flowchart illustrating an example of a method for determining recommended items according to an embodiment of the present invention.
7 to 9 are diagrams illustrating an example of a user interface (UI) for a computing device to provide a customized bed customization service according to an embodiment of the present invention.

Various embodiments are now described with reference to the drawings. In this specification, various descriptions are presented to provide an understanding of the invention. However, it is clear that these embodiments may be practiced without these specific descriptions.

As used herein, the terms “component,” “module,” “system,” and the like refer to a computer-related entity, hardware, firmware, software, a combination of software and hardware, or an implementation of software. For example, a component may be, but is not limited to, a process running on a processor, a processor, an object, a thread of execution, a program, and/or a computer. For example, both an application running on a computing device and the computing device can be a component. One or more components may reside within a processor and/or thread of execution. A component may be localized within one computer. A component may be distributed between two or more computers. Additionally, these components can execute from various computer-readable media having various data structures stored thereon. Components can transmit signals, for example, with one or more data packets (e.g., data and/or signals from one component interacting with other components in a local system, a distributed system, to other systems and over a network such as the Internet). Depending on the data being transmitted, they may communicate through local and/or remote processes.

Additionally, the term “or” is intended to mean an inclusive “or” and not an exclusive “or.” That is, unless otherwise specified or clear from context, “X utilizes A or B” is intended to mean one of the natural implicit substitutions. That is, either X uses A; X uses B; Or, if X uses both A and B, “X uses A or B” can apply to either of these cases. Additionally, the term “and/or” as used herein should be understood to refer to and include all possible combinations of one or more of the related listed items.

Additionally, the terms “comprise” and/or “comprising” should be understood to mean that the corresponding feature and/or element is present. However, the terms “comprise” and/or “comprising” should be understood as not excluding the presence or addition of one or more other features, elements and/or groups thereof. Additionally, unless otherwise specified or the context is clear to indicate a singular form, the singular terms herein and in the claims should generally be construed to mean “one or more.”

Those skilled in the art will additionally recognize that the various illustrative logical blocks, components, modules, circuits, means, logic, and algorithm steps described in connection with the embodiments disclosed herein may be implemented using electronic hardware, computer software, or a combination of both. It must be recognized that it can be implemented with To clearly illustrate the interchangeability of hardware and software, various illustrative components, blocks, configurations, means, logics, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented in hardware or software will depend on the specific application and design constraints imposed on the overall system. A skilled technician can implement the described functionality in a variety of ways for each specific application. However, such implementation decisions should not be construed as departing from the scope of the present invention.

The description of the presented embodiments is provided to enable anyone skilled in the art to use or practice the present invention. Various modifications to these embodiments will be apparent to those skilled in the art. The general principles defined herein may be applied to other embodiments without departing from the scope of the invention. Therefore, the present invention is not limited to the embodiments presented herein. The present invention is to be interpreted in the broadest scope consistent with the principles and novel features presented herein.

In this specification, a computer refers to all types of hardware devices including at least one processor, and depending on the embodiment, it may be understood as encompassing software configurations that operate on the hardware device. For example, a computer can be understood to include, but is not limited to, a smartphone, tablet PC, desktop, laptop, and user clients and applications running on each device.

Hereinafter, embodiments of the present invention will be described in detail with reference to the attached 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 depending on the embodiment, at least part of each step may be performed in a different device.

1 is a diagram illustrating a system according to an embodiment of the present invention.

Referring to FIG. 1, a system according to an embodiment of the present invention may include a computing device 100, a user terminal 200, and an external server 300. The system shown in FIG. 1 is according to one embodiment, and its components are not limited to the embodiment shown in FIG. 1, and may be added, changed, or deleted as necessary.

In one embodiment, computing device 100 may provide a custom bed customization service.

Specifically, the computing device 100 may obtain order information related to a customized bed from the user terminal 200. Additionally, the computing device 100 may generate production information based on order information. Additionally, the computing device 100 may transmit production information to the external server 300 related to the production of the bed and request production of a customized bed corresponding to the production information. Additionally, the computing device 100 may obtain production status information about the customized bed from the external server 300 after requesting production. In addition, when the computing device 100 recognizes that the production of the customized bed has been completed based on the production status information, it may request delivery to the external server 300 to deliver the bed to the delivery address corresponding to the order information.

Accordingly, the computing device 100 of the present invention can provide a customized bed by custom-manufacturing a bed corresponding to order information for each user.

Hereinafter, an example of a method by which the computing device 100 provides a customized bed customization service will be described later with reference to FIGS. 3 to 9.

According to various embodiments of the present invention, the computing device 100 may provide a custom manufacturing service for customized furniture in addition to a customized bed custom manufacturing service. In this case, the computing device 100 may obtain order information and generate production information in the same manner as for a custom bed. Additionally, the computing device 100 may request production of customized furniture based on production information and request delivery of customized furniture that has been manufactured.

In other words, the method of providing a customization service of the present invention is not limited to customized beds, and can be used for customization services for various customized items.

In various embodiments, the computing device 100 may provide web- or application-based services. However, it is not limited to this.

Computing device 100 may include any type of computer system or computer device, such as, for example, microprocessors, mainframe computers, digital processors, portable devices, and device controllers. However, it is not limited to this.

Hereinafter, the hardware configuration of the computing device 100 will be described with reference to FIG. 2 .

Meanwhile, the user terminal 200 may be connected to the computing device 100 through the network 400 and may be a user terminal that uses a customized bed customization service provided by the computing device 100. For example, the user terminal 200 may be an orderer's terminal for ordering a customized bed.

Here, the user terminal 200 may include, for example, various types of computer devices. For example, the user terminal 200 may refer to various terminal devices such as a smartphone, tablet PC, desktop, or laptop.

The user terminal 200 includes a display in at least a portion of the terminal, and may include an operating system for running an application or extension program-based service provided by the computing device 100. For example, the user terminal 200 may be a smart phone, but is not limited to this. The user terminal 200 is a wireless communication device that guarantees portability and mobility, and may be used for navigation, personal communication (PCS), etc. System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)- 2000, all types of handheld-based wireless communication devices such as W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet) terminals, smartpads, tablet PCs, etc. It can be included.

The external server 300 can be connected to the computing device 100 through the network 400, and the computing device 100 can transmit and receive various information/data necessary to provide a customized bed customization service, and the computing device 100 As (100) provides customized bed customization services, various information/data generated can be stored and managed.

For example, the external server 300 may be a server of a manufacturing factory responsible for manufacturing and delivering beds in a custom bed custom manufacturing service. For another example, the external server 300 may be a database server that stores information used in a custom bed customization service. As another example, the external server 300 may be a server that provides information used in a custom bed customization service.

The network 400 may refer to a connection structure that allows information exchange between nodes such as a computing device, a plurality of terminals, and servers. For example, the network 400 includes a local area network (LAN), a wide area network (WAN), the World Wide Web (WWW), a wired and wireless data communication network, a telephone network, and a wired and wireless television communication network. do.

Wireless data communication networks include 3G, 4G, 5G, 3GPP (3rd Generation Partnership Project), 5GPP (5th Generation Partnership Project), LTE (Long Term Evolution), WIMAX (World Interoperability for Microwave Access), Wi-Fi, and Internet. (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, NFC (Near- Field Communication) network, satellite broadcasting network, analog broadcasting network, DMB (Digital Multimedia Broadcasting) network, etc., but is not limited thereto.

Figure 2 is a hardware configuration diagram of a computing device according to an embodiment of the present invention.

Referring to FIG. 2, the computing device 100 according to an embodiment of the present invention includes one or more processors 110 and a memory 120 that loads a computer program 151 executed by the processor 110. , it may include a bus 130, a communication interface 140, and a storage 150 that stores a computer program 151. Here, only components related to the embodiment of the present invention are shown in Figure 2. Accordingly, anyone skilled in the art to which the present invention pertains will know that other general-purpose components may be included in addition to the components shown in FIG. 2.

The processor 110 controls the overall operation of each component of the computing device 100. The processor 110 may be composed of one or more cores, and may include a central processing unit (CPU), a general purpose graphics processing unit (GPGPU), and a tensor processing unit (TPU) of the computing device. unit) may include a processor for data analysis and deep learning. Alternatively, it may be configured to include any type of processor well known in the art of the present invention.

Additionally, the processor 110 may perform operations on at least one application or program for executing methods according to embodiments of the present invention, and the computing device 100 may include one or more processors.

In various embodiments, the processor 110 includes random access memory (RAM) (not shown) and read memory (ROM) that temporarily and/or permanently store signals (or data) processed within the processor 110. -Only Memory, not shown) may be further included. Additionally, the processor 110 may be implemented in the form of a system on chip (SoC) that includes at least one of a graphics processing unit, RAM, and ROM.

Memory 120 stores various data, commands and/or information. Memory 120 may load a computer program 151 from storage 150 to execute methods/operations according to various embodiments of the present invention. When the computer program 151 is loaded into the memory 120, the processor 110 can 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 invention is not limited thereto.

Bus 130 provides communication functionality between components of 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 and wireless Internet communication of the computing device 100. Additionally, 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 technical field of the present invention. In some embodiments, communication interface 140 may be omitted.

Storage 150 may store the computer program 151 non-temporarily. When performing a process according to an embodiment of the present invention through the computing device 100, the storage 150 may store various information necessary to perform analysis according to the disclosed embodiment.

The storage 150 is a non-volatile memory such as Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), flash memory, a hard disk, a removable disk, or a device well known in the technical field to which the present invention pertains. It may be configured to include any known type of computer-readable recording medium.

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

In one embodiment, computer program 151 may include one or more instructions to perform various methods related to various tasks related to training a neural network model.

The steps of the method or algorithm described in connection with embodiments of the present invention may be implemented directly in hardware, implemented as a software module executed by hardware, or a combination thereof. The software module may be RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), Flash Memory, hard disk, removable disk, CD-ROM, or It may reside on 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) and stored in a medium in order to be executed in conjunction with a hardware computer. Components of the invention may be implemented as software programming or software elements, and similarly, embodiments may include various algorithms implemented as combinations of data structures, processes, routines or other programming constructs, such as C, C++, , may be implemented in a programming or scripting language such as Java, assembler, etc. Functional aspects may be implemented as algorithms running on one or more processors.

Figure 3 is a flowchart illustrating an example of a method of providing a customized bed custom manufacturing service according to an embodiment of the present invention.

Referring to FIG. 3, the computing device 100 may obtain order information related to a customized bed from the user terminal 200 (S100). Here, the order information is information for ordering a customized bed, and may include, but is not limited to, the bed type selected by the user, options according to the bed type, each option item, and information about the delivery address.

Specifically, the computing device 100 may provide a user interface for providing a bed customization service to the user terminal 200 and obtain order information through the user interface.

For example, the computing device 100 may input an input for selecting one type among a plurality of bed types preset through a user interface, and select one item from each item list of an option list corresponding to a specific type. You can get input about what to do.

In the present invention, a plurality of preset bed types are pre-classified according to the design, material, or function of the bed, for example, at least one of a design bed, a design hotel bed, a hotel bed, a wooden bed, a foundation, a headboard, and a motion bed. It may include one, but is not limited to this.

In addition, a list of options (e.g., bed size, bed height, fabric, color, material grade, head height addition) that can be selected by the user for each of the plurality of preset bed types or bed models may be preset. Additionally, each option list may have a preset list of items (for example, in the case of bed size, S, SS, D, Q, K, LK, SK, CK, EK).

In various embodiments, when obtaining order information related to a customized bed from the user terminal 200, the computing device 100 may obtain information about the housing type of the user of the customized bed from the user terminal 200. Additionally, the computing device 100 may determine the installation method of the customized bed based on information about the housing type. In this case, the computing device 100 may include the installation method in the production information in step S200, which will be described later.

Here, information on the user's housing type may include at least one of self-owned or rented (specifically, jeonse or monthly rent), and the installation method may be determined differently depending on whether the user owns or rents.

For example, the computing device 100 cannot perform construction work such as driving nails when the space in which the customized bed is placed is not owned by the owner but is rented on a monthly basis or a lease basis, so taking this into account, driving nails, etc. when placing the bed is not possible. You can decide on the installation method so that a customized bed can be manufactured in a way that does not require any process.

As an additional example, the computing device 100 may move frequently if the space in which the customized bed is placed is not owned but is rented or rented, so taking this into account, it is possible to use a method that is easy to assemble when placing the bed (e.g. For example, a manufacturing method can be determined so that a customized bed can be manufactured in which several parts to be assembled are manufactured in a pre-joined form so that several assembly steps can be omitted. In this case, the computing device 100 may include the manufacturing method in the manufacturing information in step S200, which will be described later.

Hereinafter, a more detailed description of the method by which the computing device 100 obtains order information will be described with reference to FIGS. 4 to 6 .

In one embodiment, when order information is obtained, the computing device 100 may generate production information based on the order information (S200). Then, the computing device 100 may transmit the production information to the external server 300 related to the production of the bed and request the production of a customized bed corresponding to the production information (S300).

Specifically, the computing device 100 may generate a list of raw materials corresponding to order information and generate production information by mapping sizes and quantities to each of the raw material lists. Then, the computing device 100 may request bed manufacturing by transmitting the corresponding information to the external server 300 related to bed manufacturing.

Accordingly, the computing device 100 can increase the convenience of bed manufacturers and improve productivity related to the bed manufacturing process through the list of raw materials, the size and quantity of each raw material, etc. included in the production information.

In one embodiment, the computing device 100 may obtain production status information about a customized bed from an external server after requesting production (S400). Here, the production status information may include, but is not limited to, the process rate of the custom bed being manufactured.

Specifically, the computing device 100 may obtain information on the production status of the customized bed at a preset period (eg, 1 day).

Additionally, the computing device 100 may recognize whether production of the customized bed has been completed based on production status information. That is, the computing device 100 may recognize that manufacturing of the customized bed has been completed when the process rate of the customized bed is 100%.

When the computing device 100 recognizes that production of the customized bed has been completed, it may request delivery to the external server 300 to deliver the bed to the delivery address corresponding to the order information (S500).

In various embodiments, when the computing device 100 acquires information on the production status of a customized bed at a preset cycle, the computing device 100 may provide the process rate of the customized bed to the user who ordered the customized bed through a user interface. there is.

According to various embodiments of the present invention, when order information is obtained in step S100, the computing device 100 may generate a virtual image of a customized bed corresponding to the order information. Additionally, the computing device 100 may obtain a review image of the customized bed from the user terminal 200 after delivery of the customized bed corresponding to the order information is completed in step S500. Additionally, the computing device 100 may generate an image set by mapping the virtual image and the review image of the bed. Additionally, the computing device 100 may provide the image set to another user terminal, and provide a reward to the user terminal 200 when a new order related to the image set is received from the other user terminal.

Specifically, the computing device 100 may recognize several users who provided review images among users who purchased a bed through a custom bed customization service. Additionally, the computing device 100 may generate a virtual image based on order information of several users and create an image set by mapping the virtual image and the review image.

Meanwhile, the computing device 100 that generated the image set may provide an image set corresponding to the specific bed type when a user who wishes to purchase a customized bed selects a specific bed type.

For example, when a first user who wants to purchase a customized bed selects bed type A, the computing device 100 may display a review image provided by a second user who previously ordered bed A, and the second user's order information. The virtual images created based on can be grouped into a set and provided to the first user.

In this case, the first user can intuitively understand what configuration other users, including the second user, ordered for the bed type they selected. Additionally, the first user may select one of the provided image sets and order a customized bed with the same configuration as the image set. In this case, the computing device 100 may provide rewards (e.g., discount coupons, points, etc. that can be used to order a customized bed) to the user terminal of a specific user selected by the first user, or to a user account associated with the specific user. You can.

On the other hand, the computing device 100 that created the image set may provide the image set through a separate space (eg, a review bulletin board) within the user interface. In this case, the first user who wants to purchase a customized bed can easily check the beds ordered by other users and use them as a reference when purchasing a customized bed. Additionally, the first user may order a customized bed with the same configuration as the customized bed configured by the second user. In this case, the computing device 100 may provide a reward (eg, a discount coupon, points, etc. that can be used to order a customized bed) to the user terminal of the second user or to the user account associated with the second user.

Additionally, the computing device 100 collects evaluation information (e.g., score, like, dislike, etc.) about the image set provided in a separate space within the user interface at preset intervals (e.g., 1 month). can do. In this case, the computing device 100 may calculate a ranking for the image set (eg, order of high score, number of likes, etc.) for the image set based on the evaluation information. Additionally, the computing device 100 may provide rewards according to the calculated ranking to the user terminal or user account corresponding to each image set.

According to various embodiments of the present invention, the computing device 100 may obtain inventory and prices of each of a plurality of raw materials available for manufacturing a customized bed. Additionally, the computing device 100 may recognize a first raw material whose inventory amount exceeds a preset quantity among the plurality of raw materials. Additionally, the computing device 100 may recognize a second raw material whose price among the plurality of raw materials has been reduced by more than a preset amount compared to the previous price. In addition, the computing device 100 may generate discount information by applying a preset discount rate to the price of each option and bed type in which at least one of the first raw material and the second raw material is used. In this case, the computing device 100 may provide discount information to the user terminal 200 in step S100 of obtaining order information related to a customized bed from the user terminal.

Therefore, the computing device 100 of the present invention can help users make reasonable purchases by providing options and bed types using raw materials with relatively low market prices. In addition, the computing device 100 of the present invention can induce orders through options using raw materials with large inventory and discounts on bed types, and facilitate inventory management of raw materials.

Figure 4 is a flowchart illustrating an example of a method for obtaining order information according to an embodiment of the present invention. Figure 5 is a flowchart illustrating an example of a method for rearranging an option item list according to an embodiment of the present invention. Figure 6 is a flowchart illustrating an example of a method for determining recommended items according to an embodiment of the present invention.

Referring to FIG. 4, the computing device 100 may obtain a first selection input for selecting one type from a plurality of preset bed types (S110).

For example, the computing device 100 may obtain a first selection input for selecting at least one of a design bed, a design hotel bed, a hotel bed, a wooden bed, a foundation, a headboard, and a motion bed.

The computing device 100 may provide an option list corresponding to a specific type corresponding to the first selection input and an item list from which one item can be selected for each of a plurality of options included in the option list (S120). And, the computing device 100 may obtain a second selection input for selecting one item from the list of items for each option (S130).

For example, when a hotel bed is selected in the first selection input, the computing device 100 may select head color, bed size, foundation, panel (left, right), drawer (left, right), lighting (left, right), An option list containing multiple options for each switch (left, right), head backlight, and additional mattress selection can be provided. Here, each option included in the option list may include one or more items.

With the option list provided, the computing device 100 may obtain a second selection input for selecting one item from the list of items for each option.

In various embodiments, when an item for one of a plurality of options included in the option list is selected, the computing device 100 may rearrange the item list for the remaining options that have not yet been selected.

Specifically, referring to FIG. 5, when an item related to at least one option among a plurality of options is selected, the computing device 100 provides information about the selected item to a pre-trained neural network model corresponding to a specific type. You can input (S131). Then, the computing device 100 may obtain a score value for each item corresponding to each of the remaining options for which no one item is selected from the pre-trained neural network model (S132). In this case, the computing device 100 may rearrange the item list of each remaining option in which one item is not selected in order of the highest score value for each item (S133).

For example, when the selected bed type is a hotel bed and one item related to the head color option is selected among the plurality of options corresponding to the hotel bed, the computing device 100 generates a pre-trained neural network model corresponding to the hotel bed. You can enter the items selected in the head color options. In this case, the neural network model can output score values for each of the floating 150, floating 230, and drawer type 230 items included in the foundation option among the plurality of options corresponding to the hotel bed.

In one embodiment, the computing device 100 may train the neural network model used in the above-described steps (S131-S133) in advance.

Specifically, the computing device 100 may obtain order history for each preset plurality of bed types. Additionally, the computing device 100 may recognize items selected for each of the plurality of options included in the option list for each bed type, based on the order history for each of the plurality of preset bed types. Additionally, the computing device 100 may label each item selected for each of the plurality of options and generate learning data for each of the plurality of preset bed types. Additionally, the computing device 100 may use the learning data to learn a neural network model for each of a plurality of preset bed types. Here, the neural network model for each of the plurality of preset bed types may be trained to output a higher score as the number of times each item selected for each of the plurality of options is labeled increases.

That is, when the user selects an item for one of a plurality of options included in the option list, the computing device 100 of the present invention organizes the list of items for the remaining options that have not yet been selected in order of high score value. By rearranging the options, the options most selected by other users are prioritized, thereby increasing user convenience and satisfaction.

Referring again to FIG. 4, when there is an unselected option in which any one item of a plurality of options is not selected, the computing device 100 provides a recommended item for the unselected option based on the remaining options in which one item is selected. You can decide (S140). Additionally, the computing device 100 may provide a recommended item to the user terminal and obtain a third selection input for applying or selecting the recommended item (S150).

Specifically, referring to FIG. 6, the computing device 100 may input information about the item selected from each of the remaining options in which one item is selected to a pre-trained neural network model corresponding to a specific type (S141). Additionally, the computing device 100 may obtain a score value for each item corresponding to each unselected option in which any one item is not selected from the pre-trained neural network model (S142). Then, the computing device 100 may determine a recommended item based on the score value for each item (S143).

For example, the computing device 100 may determine that the selected bed type is a hotel bed, one item related to each of the head color option and foundation option is selected among a plurality of options corresponding to the hotel bed, and an item for the lighting option is selected. If not selected, the items selected in the head color option and the items selected in the foundation option can be input into the pre-trained neural network model corresponding to the hotel bed. In this case, the neural network model uses the items included in the lighting options among the plurality of options corresponding to hotel beds: Bloel, Cylinder White, Cylinder Black, Moreal White, Morel Gray, Morel Black, Square White, Square Black, Round Black, and Round. The score values for white and round champagne gold can be output. Additionally, the computing device 100 may determine, among the score values of each item included in the lighting option, items that are higher than a preset score value as recommended items, or may generate a list of recommended items in order of highest score value.

In the above example, each score value of each item included in the lighting options output by the pre-trained neural network model is the same as each item of the head color option and foundation option selected by the user among the order history of hotel beds ordered by other users. While an item is selected, the lighting option may be proportional to the number of times the item is selected.

In one embodiment, the computing device 100 may train the neural network model used in the above-described steps (S141-S143) in advance.

Specifically, the computing device 100 may obtain order history for each preset plurality of bed types. Additionally, the computing device 100 may recognize items selected for each of the plurality of options included in the option list for each bed type, based on the order history for each of the plurality of preset bed types. Additionally, the computing device 100 may label each item selected for each of the plurality of options and generate learning data for each of the plurality of preset bed types. Additionally, the computing device 100 may use the learning data to learn a neural network model for each of a plurality of preset bed types. Here, the neural network model for each of the plurality of preset bed types may be trained to output a higher score as the number of times each item selected for each of the plurality of options is labeled increases.

That is, when the user does not select an item for any one of a plurality of options included in the option list, the computing device 100 of the present invention recommends an item whose score value is greater than or equal to a preset value, or recommends an item that is not selected. By recommending a list of items for options in order, you can increase the convenience of selecting an option item.

7 to 9 are diagrams illustrating an example of a user interface (UI) for a computing device to provide a customized bed customization service according to an embodiment of the present invention.

According to one embodiment of the present invention, as described above with reference to the drawings, the computing device 100 may provide a customized bed customization service based on the user's needs, in which a customized bed is customized based on the user's needs.

Here, the customized bed customization service based on the user's needs may refer to a service in which the user selects various options for bed production and custom produces a bed that reflects the user's needs according to the selected options. In this specification, it is explained that a customized bed is custom-made based on the user's needs, but it is not limited to this and can be applied to various types of furniture such as wardrobes, chests of drawers, and tables.

First, the computing device 100 may select an option for making a bed from the user. That is, the computing device 100 may obtain order information from the user.

For example, the computing device 100 may be connected to the user terminal 200 through the network 400, and may provide a user interface (e.g., FIGS. 7 to 9) to the user terminal 200, and the user interface You can select one or more options from a plurality of predetermined options. However, it is not limited to this, and may be implemented in a form where the user freely inputs options through text input such as words, phrases, clauses, and sentences.

The order information acquired by the computing device 100 is information for ordering a customized bed, and may include selection information about the bed type selected by the user.

For example, as shown in FIG. 7, one of a design bed, a design hotel bed, a hotel bed, a wooden bed, a foundation, and a headboard is provided for selection, and the order information may include selection information for this. there is.

In addition, as shown in Figures 8 and 9, when a specific bed type or a specific bed is selected, a list of selectable items corresponding to the bed type or the bed (e.g., head color, bed size, foundation, Panel (left, right), drawer (left, right), lighting (left, right), switch (left, right), head backlight, mattress (additional selection) are provided, and ordering information may include selection information for these. there is. However, it is not limited to this, and the selectable items may include various additional options such as the type and material of the fabric included in the bed, such as the bed mattress cover, and the type and grade of wood.

In various embodiments, the computing device 100 receives options for a plurality of items for custom manufacturing of a user-customized bed, but when only options for at least some of the plurality of items are input, the computing device 100 does not receive input. Options for this can be provided separately. For example, when the computing device 100 receives only 5 options out of a total of 10 items, it selects the 5 options input from the user based on the history of creating a plurality of user-customized beds. A user-customized bed that includes all can be selected, and the remaining five options that have not been input from the user can be recommended based on the options of the selected user-customized bed.

In various embodiments, the computing device 100 may be used to custom-manufacture furniture other than a bed, that is, furniture that can be used for multiple purposes rather than just one (for example, a desk, a dining table, a decorative table, etc. (if you want to create a table that can be used), options that are not entered can be recommended depending on the purpose of use of the furniture.

In various embodiments, when the computing device 100 receives information about the space in which the user wants to place a customized bed (e.g., a spatial image or a numerical value such as the width, length, and height of the space) from the user, the computing device 100 is placed in the space. Options can be recommended based on the information provided.

In various embodiments, the computing device 100 may 3D model a space in which a user-customized bed is to be placed using information about the space input from the user, and create a 3D model corresponding to the user-customized bed on the 3D modeled space. A simulation can be performed to place the model, and depending on the results of the simulation, options that have not been entered can be recommended, or changes/adjustments to already entered options can be recommended.

In various embodiments, the computing device 100 may determine the placement location of the user-customized bed in a space where the user-customized bed is to be placed through the above simulation, and recommend the determined placement location. At this time, the computing device 100 can receive information about other furniture to be placed together in the space in addition to the user-customized bed, and can determine the placement position of the user-customized bed by considering this.

In various embodiments, the computing device 100 receives one or more options from the user, and includes user attributes (e.g., user's physical characteristics, gender, behavioral patterns, etc.) or space attributes (e.g., size of space, self-occupancy, rent, etc.) etc.), one or more options can be adjusted or detailed options for each of the one or more options can be determined. For example, in the computing device 100, if the space where the user-customized bed is placed is not owned by the owner but is rented on a monthly basis or rented out, construction such as driving nails is not possible, so a process such as driving nails is necessary taking this into consideration. You can set detailed options in a configuration that does not exist, or exclude the option.

In various embodiments, the computing device 100 may generate a user-customized bed that satisfies the option based on the option input by the user, and may verify the generated user-customized bed. For example, when budget information is previously input by the user, the computing device 100 verifies whether the user-customized bed exceeds the pre-entered budget, or actually produces a user-customized bed corresponding to the option input by the user. You can verify possibilities or problems that may occur during actual production.

At this time, if a problem is detected through the above verification process (e.g., actual production is impossible, placement in the space desired by the user during production is impossible, etc.), the computing device 100 resolves the problem. You can adjust options in the right direction or suggest recommended options to solve the problem. For example, if it is impossible to place the computing device 100 in the space where the user wants to place it, the computing device 100 may adjust a size option among options input by the user or provide information about a recommended size to the user.

In various embodiments, the computing device 100 provides the user with 3D modeling of the user-customized bed and the placement space of the user-customized bed, and provides furniture that may be placed together according to the size of the placement space, the size of the user-customized bed, and the placement location. Information can be recommended and provided.

In various embodiments, the computing device 100 obtains information about the budget input from the user, the type of furniture needed, the size of each furniture, the shape of the furniture, the type of furniture, etc., and prioritizes or weights each piece of information. can be decided.

For example, a high priority or weight may be set for furniture that must be placed, and a relatively low priority or weight may be set for furniture that can be omitted. As another example, the priority or weight of each size, shape, type, and budget of furniture may be set in advance according to the user's selection. Each priority or weight may be input according to the user's selection, or one of preset patterns may be selected from the user, and a priority or weight corresponding to the selected pattern may be set.

In one embodiment, in the process of simulating the arrangement of furniture selected by the user, the computing device 100 may suggest an optimal alternative based on a preset priority or weight if it is difficult to place the furniture in the space. For example, computing device 100 may omit low-priority furniture. As another example, the computing device 100 may recommend other furniture that is more expensive but small in size and can be placed in the space for a user who has a higher priority or weight on shape than on budget. . As another example, for users who have a high priority or weight for bed size, it is recommended to omit or change other furniture while maintaining the bed size, and for users who have a relatively low priority or weight for bed size, it is recommended to omit or change other furniture. In this case, it may be recommended to reduce the size of the bed.

In one embodiment, the computing device 100 may obtain information about households that can be merged with each other. For example, a bed and a wardrobe can be merged with each other to have a wardrobe built into the bed frame, and a bed and a dresser or a bed and a bookshelf can also be merged with each other so that the head of the bed is equipped with a dresser or bookshelf. When it is difficult to place furniture in a space, the computing device 100 may recommend merging furniture that can be merged with each other. In this case as well, the score for the merge result is calculated by comprehensively considering the user's priorities for the price of the merged furniture and the shape, type, and size of the furniture to be merged, and the score for the merge result is calculated when some households are omitted. If the score is higher, merging may be recommended.

In various embodiments, computing device 100 may provide a user-customized bed sharing platform. For example, users can freely create a customized bed that reflects their needs through actions such as entering and selecting options, and the computing device 100 creates each customized bed created by the user according to the user's request. It can be converted into content and shared with multiple users.

Here, sharing a user-customized bed as content not only means customizing the same user-customized bed through the content, but also customizing your own customized bed by changing and adding some options based on the content. It may include:

At this time, when the first user requests custom manufacturing for the second user's customized bed, the computing device 100 requests custom manufacturing for the second user's customized bed and at the same time provides a predetermined amount to the second user. Rewards can be provided.

Above, embodiments of the present invention have been described with reference to the attached drawings, but those skilled in the art will understand that the present invention can be implemented in other specific forms without changing its technical idea or essential features. You will be able to understand it. Therefore, the embodiments described above should be understood in all respects as illustrative and not restrictive.

Claims (10)

A method performed by a computing device comprising at least one processor, comprising:
Obtaining order information related to a customized bed from a user terminal;
generating production information based on the order information;
Transmitting the production information to an external server related to the production of a bed, requesting production of the customized bed corresponding to the production information;
After requesting the production, obtaining production status information about the customized bed from the external server; and
When it is recognized that production of the customized bed has been completed based on the production status information, requesting delivery to the external server to deliver the bed to a delivery address corresponding to the order information;
Including,
When obtaining the order information, generating a virtual image of a customized bed corresponding to the order information;
After delivery of the customized bed corresponding to the order information is completed, obtaining a review image of the customized bed from the user terminal;
generating an image set by mapping the virtual image and the review image of the bed; and
providing the image set to another user terminal, and providing a reward to the user terminal when a new order related to the image set is received from the other user terminal;
It further includes,
The step of obtaining order information related to a customized bed from the user terminal,
Recognizing from the user terminal whether the residential type of the user of the customized bed is rental; and
If the housing type is rental, the installation method is determined so that the customized bed can be manufactured in a way that does not require the process of driving nails when placing the customized bed, and several parts to be assembled are manufactured in a pre-combined form. deciding on a production method;
Including,
Obtaining information about the space in which you want to place a user-customized bed from the user terminal;
Obtaining information about other furniture to be placed together in the space from the user terminal;
Obtaining weights for each of the type of furniture, size of furniture, shape of furniture, type of furniture, and budget input from the user terminal; and
3D modeling the space using information about the space, and performing a simulation of arranging the user-customized bed and other furniture on the 3D modeled space;
It further includes,
The step of performing the simulation is,
If it is impossible to place the customized bed and other furniture in the space, and the shape of the furniture is given more weight than the budget, other furniture that is more expensive but small in size can be placed in the space. recommend, and
If it is impossible to place all of the user-customized bed and the other furniture in the space, and the weight for the size of the bed is relatively higher than other weights, it is recommended to omit or change the other furniture while maintaining the size of the bed, Recommending to reduce the size of the bed when it is impossible to place all of the user-customized bed and the other furniture in the space and the weight for the size of the bed is relatively lower than other weights;
Including,
Obtaining information about households that can be merged with each other; and
If it is impossible to place all of the user-customized bed and the other furniture in the space, and there is furniture that can be merged with each other, recommending that they be merged;
It further includes,
If it is impossible to place all of the user-customized bed and the other furniture in the space, and there is furniture that can be merged with each other, the step of recommending merging them is,
calculating a score for the merge result based on the weights related to the type, size, shape, and price of the furniture to be merged; and
Recommending merging if the score is higher than the score when omitting the other households;
Including,
How to provide custom bed customization service.
According to claim 1,
The step of obtaining order information related to a customized bed from the user terminal is,
Obtaining a first selection input for selecting one type from a plurality of preset bed types;
providing an option list corresponding to a specific type corresponding to the first selection input and an item list from which one item can be selected for each of a plurality of options included in the option list;
Obtaining a second selection input for selecting one item from the list of items for each of the plurality of options;
If there is an unselected option in which one of the plurality of options is not selected, determining a recommended item for the unselected option based on the remaining options in which one of the plurality of options is selected; and
providing the recommended item to the user terminal and obtaining a third selection input for applying or selecting the recommended item;
Including,
How to provide custom bed customization service.
According to clause 2,
The step of obtaining a second selection input for selecting one item from the list of items for each of the plurality of options,
When an item related to at least one option among the plurality of options is selected, inputting information about the selected item into a pre-trained neural network model corresponding to the specific type;
Obtaining a score value for each item corresponding to each of the remaining options for which no item is selected from the pre-trained neural network model; and
rearranging the item list of each remaining option in which any one of the items is not selected in order of the highest score value for each item;
Including,
How to provide custom bed customization service.
According to clause 2,
If there is an unselected option in which one of the plurality of options is not selected, the step of determining a recommended item for the unselected option based on the remaining options for which one of the plurality of options is selected includes:
Inputting information about an item selected from each of the remaining options in which one item is selected into a pre-trained neural network model corresponding to the specific type;
Obtaining a score value for each item corresponding to each unselected option in which any one item is not selected from the pre-trained neural network model; and
determining the recommended item based on the score value for each item;
Including,
How to provide custom bed customization service.
According to claim 3 or 4,
The method is:
Obtaining order history for each of the preset plurality of bed types;
Recognizing selected items for a plurality of options included in an option list for each bed type, based on the preset order history for each bed type;
Labeling each item selected for each of the plurality of options to generate learning data for each of the plurality of preset bed types; and
Using the learning data, training a neural network model for each of the plurality of preset bed types;
It further includes,
The neural network model for each of the plurality of bed types set above is,
Learned to output a higher score as the number of times each selected item for each of the plurality of options is labeled,
How to provide custom bed customization service.
delete delete According to claim 1,
The above method is,
Obtaining inventory and prices of each of a plurality of raw materials available for manufacturing the customized bed;
Recognizing a first raw material whose inventory amount exceeds a preset quantity among the plurality of raw materials;
Recognizing a second raw material among the plurality of raw materials whose price has been reduced by more than a preset amount compared to the previous price; and
Generating discount information applying a preset discount rate to the price of each option and bed type using at least one of the first raw material and the second raw material;
It further includes,
Providing the discount information to the user terminal in the step of obtaining order information related to a customized bed from the user terminal,
How to provide custom bed customization service.
A memory that stores one or more instructions; and
A processor that executes the one or more instructions stored in the memory
Contains,
The processor executes the one or more instructions,
An apparatus for performing the method of claim 1.
A computer program combined with a computer as hardware and stored on a computer-readable recording medium so as to perform the method of claim 1.