system

Abstract

We provide the system. [Solution] A means for the user to input layout information of the wedding venue, A means for the server to acquire market flower material information in real time and store it in a database, A means for generating 3D designs of decorative flowers using a server-generated AI model based on layout information entered by the user and acquired market data, A means of sending the generated 3D design to the user's device and displaying it visually, A system including means for a user to select a different plan and send that selection information to a server.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the preparation for a wedding, the bride and groom currently spend a great deal of time and effort on the planning of decorative flowers. Also, it is difficult to select a desired design within the budget, and the waste of flower materials in the market is also a major issue. Therefore, there is a need for a method that can easily and effectively select the optimal floral decoration for a wedding.

Means for Solving the Problems

[0005] This invention provides a system that allows users to input layout information corresponding to their wedding venue, and a server collects market information on floral materials in real time to provide the optimal floral arrangement plan within the user's budget. By utilizing a generation AI model, the system can automatically generate floral arrangement designs according to the venue layout and visually present the user with options in multiple price ranges. This makes it easy for the user to select the most suitable plan.

[0006] A "user" refers to an individual or group that uses the system to select a floral decoration plan for their wedding.

[0007] A "wedding venue" refers to the physical space used to hold a wedding ceremony.

[0008] "Layout information" refers to data that shows the physical arrangement and shape of the wedding venue.

[0009] A "server" refers to a computing device that receives information from users and performs processing such as collecting market information and generating designs.

[0010] "Market flower material information" refers to data on the types of flowers traded in the market, their prices, availability, seasonality, and other related information.

[0011] A "generative AI model" refers to an artificial intelligence algorithm used to generate floral arrangement designs.

[0012] "3D design" refers to three-dimensional floral arrangement design data that users can visually confirm through simulation.

[0013] A "plan" refers to a floral arrangement design and its proposed content that is tailored to the user's budget.

[0014] A "terminal" refers to a device used by a user to access a system and input or verify information. [Brief explanation of the drawing]

[0015] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] Shows an emotion map to which a plurality of emotions are mapped. [Figure 10] Shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0016] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention provides a system for efficiently selecting wedding venue decoration plans. Specific embodiments of the system are shown below.

[0037] The user begins by entering the layout information of the venue where their wedding will be held into the terminal. This layout information is provided as 3D model data, floor plans, etc. The terminal then sends the entered layout information to the server. This information is used as the basic data for the 3D floral arrangement simulation described later.

[0038] Next, the server collects real-time information on floral materials from the market. This is done using APIs provided by existing flower markets and includes data such as the type of flower, price, inventory information, and even seasonality. Based on this information, the server prepares to provide the optimal floral arrangement plan within the user's budget.

[0039] The server uses a generation AI model to generate 3D floral arrangement designs based on venue layout information entered by the user and acquired market data. This AI model is designed to suggest the most suitable floral arrangements while considering the venue's shape and atmosphere, as well as the user's budget.

[0040] Users can visually confirm 3D designs of floral arrangements sent from the server via their devices. The system offers floral arrangement options at various price points, i.e., "pine, bamboo, and plum" plans, allowing users to select the design they most desire based on the visual information.

[0041] To give a specific example, if a user chooses wedding venue A and requests a mid-range decoration plan within their budget, they send a 3D layout of the venue from their device to the server. After the server obtains market information, it uses AI to combine the most suitable mid-range floral materials for that layout and generates a 3D design. The user can then review the design on their device and select the one they are satisfied with.

[0042] In this way, the system provides a stress-free environment where users can select high-quality, budget-friendly interior floral plans through simple and intuitive operation.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user enters information about the venue layout for their wedding into the terminal. The terminal converts this information into the correct format and prepares to send it to the server.

[0046] Step 2:

[0047] The server receives the transmitted venue layout information and saves it to the database. This information is then used for subsequent 3D modeling.

[0048] Step 3:

[0049] The server obtains real-time flower information through an external flower market API. This information includes flower type, price, and availability.

[0050] Step 4:

[0051] The server uses an AI model generated based on venue layout information and market data to create multiple 3D floral arrangement designs tailored to the user's budget.

[0052] Step 5:

[0053] The server sends the generated floral design to the terminal and presents it to the user. The terminal displays this visually so that the user can confirm it.

[0054] Step 6:

[0055] The user uses their device to select their desired floral arrangement plan from the presented designs and sends that selection to the server.

[0056] Step 7:

[0057] The server saves the user's selected plan in a database, making it available later for detailed discussions and ordering procedures.

[0058] (Example 1)

[0059] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0060] In modern event planning, selecting decorations is often accompanied by detailed requests and budget constraints. There is a need to develop a system that can efficiently select the optimal decoration plan while addressing these demands and allowing for visual confirmation. Traditional methods require manual selection from a vast number of options, which is time-consuming and labor-intensive, often resulting in unsatisfactory outcomes for users.

[0061] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0062] In this invention, the server includes means for the user to input event venue layout information, means for the information processing device to immediately acquire information on decorative items from supply sources and store it in a data storage device, and means for the information processing device to use a generated artificial intelligence model to generate a three-dimensional design of decorative items based on the layout information input by the user and the acquired supply source data. This allows the user to quickly check decoration plans that suit their budget and preferences and select the optimal plan.

[0063] "Users" refer to individuals or organizations that operate the system to input event venue layout information and select decoration plans.

[0064] An "event venue" refers to a place where special events such as weddings and parties are held, and it is the space for which layout information is entered.

[0065] "Layout information" refers to data that details the layout, size, shape, and other characteristics of the event venue.

[0066] An "information processing device" refers to a device that has the function of acquiring and storing information on decorative items from a supply source, and processes the data within the system to generate a three-dimensional design.

[0067] "Supply source" refers to an external information provider that provides real-time information on decorative items.

[0068] "Jewelry information" refers to detailed data related to jewelry, such as the type of jewelry, price, availability, and seasonality.

[0069] A "data storage device" refers to a storage device used to store acquired information.

[0070] The term "generated artificial intelligence model" refers to a learning model designed to perform three-dimensional design according to the user's requirements.

[0071] "Three-dimensional design" refers to a three-dimensional digital model that visually represents how decorative items will be arranged.

[0072] A "display device" refers to a device used by users to visually confirm three-dimensional designs.

[0073] "Plan" refers to decorative plans that are prepared with different budget ranges and design options.

[0074] The following describes embodiments for carrying out the invention.

[0075] The user first inputs the layout information of the event venue into a terminal. This information is provided in the form of a 3D model or floor plan. The terminal sends the entered layout information to the server, which then receives the basic data.

[0076] The server retrieves information on decorative items from markets and suppliers. This process uses APIs provided by existing suppliers to collect data such as the type of decorative item, price, inventory information, and seasonality. This data is stored in a data storage device within the server and used in subsequent processes.

[0077] Next, the server uses a generative AI model to generate 3D designs of decorative items based on the placement information entered by the user and the acquired market data. This generative AI model considers shape, atmosphere, budget, etc., and proposes the optimal combination of decorative items. The AI ​​model receives the prompt "Based on the 3D layout of the event venue, please propose beautiful decorative designs within the price range desired by the user" as input and creates multiple design proposals.

[0078] The generated 3D design is sent from the server to the user's display device. The user can use the display device to visually confirm the proposed design. The user compares the various price ranges offered, such as "Pine, Bamboo, and Plum," and selects their preferred plan.

[0079] This system allows users to efficiently select decorations that fit their budget and preferences, shortening the selection process. This enables users to prepare for events effectively and quickly.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The user inputs the event venue layout information into a terminal. This information is input as 3D model data or floor plan. The terminal converts the input layout information into a data package and sends it to the server. Here, the input is the layout information, and the output is a data package converted into a data format usable by the server.

[0083] Step 2:

[0084] The server registers the placement information received from the terminal into the database. This information is used as the basic data for 3D design. The server converts the information to conform to its internal format and saves it to the database. The input is a data package of placement information, and the output is the placement information stored in the database.

[0085] Step 3:

[0086] The server retrieves jewelry information through external source APIs. This information includes the type of jewelry, price, inventory, and seasonality. The server sends requests to each API endpoint, organizes the obtained data, and stores it in a database. The input is API response data, and the output is the organized jewelry information.

[0087] Step 4:

[0088] The server generates 3D designs using a generative AI model. The server takes placement and decoration information stored in the database as input and provides the AI ​​model with the prompt "Based on the 3D layout of the event venue, please propose beautiful decoration designs within the user's desired price range." The AI ​​model then generates multiple design proposals. The input consists of the prompt and basic data, and the output is the generated 3D design of the decorations.

[0089] Step 5:

[0090] The server sends the generated 3D design to the user's display device. The user uses this information to visually review multiple designs. The server converts the data into a format viewable on the terminal and delivers the information to the user. Here, the input is the 3D design data, and the output is the data sent to the user's display device.

[0091] Step 6:

[0092] The user selects a design from visually reviewed options. The selection information is sent from the terminal to the server, which records it. The user clicks on their preferred design on the selection screen and presses the confirm button. The input is the user's selected design, and the output is the recorded selection information.

[0093] (Application Example 1)

[0094] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0095] Balancing design aesthetics with budget while efficiently proposing the optimal decoration plan for a space is a challenging task. Traditional methods involve manually designing spaces, which has limitations in terms of time and accuracy, and cost management is also cumbersome. A system is needed to solve these problems and allow users to easily select designs.

[0096] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0097] In this invention, the server includes means for inputting spatial arrangement information, means for acquiring market item information in real time and storing it in data storage, and means for generating a 3D design of the decorative item based on the input spatial arrangement information and acquired market data using a generative AI model. This allows the user to efficiently and effectively select the optimal decorative plan and choose a design after visual confirmation.

[0098] "In-spatial placement information" refers to information that allows a user to indicate the location and layout of items or decorations within a specific physical space.

[0099] "Market goods information" refers to real-time data including the types of goods, prices, inventory levels, and seasonality of goods in a specific market.

[0100] "Data storage" refers to a storage device or area that stores acquired data and allows it to be searched and manipulated as needed.

[0101] A "generative AI model" is an artificial intelligence algorithm used to automatically generate optimal designs and layouts based on input data.

[0102] A "visualization device" is a device used to display information or data so that humans can visually confirm it; examples include monitors and display devices.

[0103] "Selection information" refers to data about a specific item or plan that the user chose from among several options presented.

[0104] "Resource range" refers to the range of items and budget available to the user, and the conditions under which choices are made based on this range.

[0105] "Options" refer to multiple plans or options presented to the user, allowing the user to choose the one that best suits them.

[0106] The system that realizes this application is a platform that generates optimal 3D designs for decorative items by utilizing market item information based on spatial placement information entered by the user. The main elements of the system include a user terminal, a server, and a generating AI model.

[0107] Users input spatial layout information using devices such as smartphones and tablets. This information is detailed through descriptions and floor plans. The device sends this information to the server, which then retrieves market item information in real time. Market information includes data such as item type, price, inventory, and seasonality, and is retrieved via an API. The server stores this data in data storage.

[0108] The server uses a generated AI model (e.g., a model created with TENSORFLOW®) to generate an optimal 3D design for the ornament based on acquired spatial placement information and market information. The generated design is sent to the user's visualization device, such as smart glasses or a head-mounted display, for realistic visual representation. Based on this visualization information, the user can consider and select from different options.

[0109] As a concrete example, consider a case where a store owner wants to update the in-store display to reflect the season in order to highlight new products. The owner inputs the store's layout information into a terminal, and the server generates decorative designs based on the latest floral material data obtained from the market. The owner then reviews several proposed display designs through a visualization device and selects the most appealing one. This selection is fed back to the server in real time and reflected in the final decision.

[0110] Examples of prompt messages include: "I'd like to change the in-store display to a spring theme. Please generate a refreshing and stylish design centered around cherry blossoms."

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] The user uses a terminal to input spatial layout information. This input includes floor plans and detailed descriptions. The input information is sent to the server in digital format. As output, the layout information data is stored on the server.

[0114] Step 2:

[0115] The server retrieves market item information in real time via an external API. This retrieved data includes item type, price, inventory, seasonality, and other information. The retrieved information is stored in data storage. The output here is a dataset of market item information.

[0116] Step 3:

[0117] The server uses a generating AI model to combine input placement information and market information to generate 3D designs for decorative items. The AI ​​model calculates the optimal placement of items using placement information data and item data, and outputs it as 3D data.

[0118] Step 4:

[0119] The server sends the generated 3D design to the user's visualization device. The user visually confirms the 3D design through that device. The output is a realistic 3D design displayed on the visualization device.

[0120] Step 5:

[0121] The user selects a different plan based on the presented 3D design. The selected information is sent back to the server, which stores the selection information in its database. The output is the selection information data, which will be reflected in future design proposals.

[0122] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0123] This invention is a system for effectively selecting floral arrangements for weddings, providing floral designs that take into account the user's emotions. Embodiments of this system are described below.

[0124] First, the user enters the layout information of their chosen wedding venue into the terminal. The terminal formats the entered information appropriately and sends it to the server. The server uses this data as the basis for the floral design incorporating the emotion engine described later.

[0125] Next, the server uses an API from an external flower market to collect real-time information on floral materials. This information includes flower types, prices, and availability, and is used to select the most suitable floral materials that can be suggested within the user's budget.

[0126] A crucial component, the emotion engine, performs real-time facial expression analysis through the camera on the user's device. The emotion engine analyzes the user's facial expression data to identify emotional states such as joy or surprise. This makes it possible to provide a floral arrangement plan that is optimally suited to the user's emotions.

[0127] The server uses an AI model based on collected market information and sentiment analysis results to generate multiple 3D floral arrangement designs. The generated designs are presented to the user's visual system via the terminal, offered as choices that evoke joy and emotion.

[0128] For example, if a user expresses a relaxed mood through their facial expressions on their wedding day, the emotion engine analyzes this and instructs the server to generate a calming floral design. As a result, the user is presented with a floral arrangement plan that creates a relaxed atmosphere.

[0129] In this way, this system goes beyond mere visual effects, supporting more personalized wedding preparations by offering floral arrangement suggestions that resonate with the user's emotions. Users can select the optimal plan based on emotion-based feedback.

[0130] The following describes the processing flow.

[0131] Step 1:

[0132] The user enters the wedding venue layout information into the terminal. The terminal formats this data and sends it to the server.

[0133] Step 2:

[0134] The server saves the received layout information to a database. This information serves as the basic data necessary for generating the 3D design.

[0135] Step 3:

[0136] The server obtains real-time flower material information using APIs from partnered external flower markets. This ensures that the latest market data is available.

[0137] Step 4:

[0138] A camera installed on the user's device captures the user's facial expressions in real time. The device then sends this facial expression data to a server.

[0139] Step 5:

[0140] The server uses an emotion engine to analyze the user's facial expression data. It determines the user's emotional state and generates appropriate emotion tags.

[0141] Step 6:

[0142] The server uses an AI model to generate multiple 3D floral arrangement designs based on the analyzed emotion tags and market data.

[0143] Step 7:

[0144] The server sends the generated 3D design to the terminal. The terminal visually presents it to the user for confirmation.

[0145] Step 8:

[0146] The user selects their desired plan from the designs presented on their device. The selection information is sent to the server.

[0147] Step 9:

[0148] The server saves the selected plan to a database, which is then used for future order processing and feedback collection.

[0149] (Example 2)

[0150] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0151] Selecting decorations for celebratory events often results in uniform designs, as it's difficult to fully consider the feelings and wishes of the participants. Furthermore, finding the optimal decoration plan within a budget requires considerable time and effort. There is a need to solve this problem and provide a more personalized decoration experience.

[0152] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0153] This invention includes a server that acquires ornament information from the market in real time and stores it in an information collection, a means for generating a three-dimensional design of ornaments based on placement information input by the user and acquired market data using a generative model, and a means for an operating device to analyze the user's facial expressions and provide emotion-based feedback to the information processing device. This makes it possible to generate personalized ornament plans that take the user's emotions into account.

[0154] A "user" is defined as the entity that uses the operating device to select and customize the decoration plan for a celebratory event.

[0155] A "control device" is a computer device used by users to input data and confirm displayed information. This device is also equipped with a camera, which is used to analyze the user's emotional state.

[0156] An "information processing device" is a central processing unit that generates and manages decoration plans based on user-inputted data and acquired market information. It has the function of acquiring data in real time and performing analysis.

[0157] A "generative model" is an algorithm and program for generating three-dimensional designs of decorative items based on the user's emotional state and market data.

[0158] An "information collection" refers to a database structure where information on jewelry acquired from the market is stored. This database includes information such as the price, inventory, and type of jewelry.

[0159] "3D design" refers to design data for decorative plans that enables a three-dimensional visual representation presented to the user. This data indicates how decorative items should be arranged within the space.

[0160] "Emotion analysis" is the process of identifying a user's emotional state based on facial expression data obtained from a camera installed on the user's control device.

[0161] "Decorative items" is a general term for decorations such as flowers and objects used in celebratory events.

[0162] "Marketplace" refers to an external source of information that provides information on the types, prices, and inventory of decorative items.

[0163] This invention is a system for providing decoration plans based on user emotions. This system consists of an information processing device (server) and a terminal (operating device) for operating it. The following describes embodiments of this system.

[0164] Users input event layout information into a terminal. This terminal features a touchscreen and keyboard, allowing for easy data entry. The terminal converts the data to the required format and sends it to the information processing device. The software used includes a JSON format conversion library.

[0165] The information processing device accesses APIs of external information sources to obtain real-time information on jewelry from the market. Using a RESTful API, the retrieved information is parsed in JSON format and stored in an information collection. This information includes the type of jewelry, price, and inventory information.

[0166] Next, the device's camera is used to capture the user's facial expressions, and emotion analysis is performed. Image analysis libraries such as OpenCV are used to identify emotions such as joy, surprise, and relaxation from the user's facial expressions.

[0167] The information processing device inputs the results of sentiment analysis and market-derived data into a generating AI model. As a prompt, it instructs the model to generate a decoration plan that takes the user's emotions and budget into consideration. The generating AI model then generates multiple 3D designs to present to the user.

[0168] Finally, the generated 3D design is displayed to the user via a terminal. The user can select the best design from the displayed decoration plans and send the selection information to the information processing device for final confirmation and adjustment. This selection is made using a touchscreen or mouse input.

[0169] As an example of a prompt, entering "Generate a design that creates a relaxed atmosphere as a decoration plan for a celebratory event when the user is in a calm emotional state" makes it possible to present the optimal decoration plan that matches the user's wishes.

[0170] This system makes it possible to provide personalized decoration plans that are tailored to the individual feelings of each user.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] The user inputs information about the celebratory event's layout into a terminal. This input includes seating arrangements, locations for decorations, and desired themes. The terminal converts this data into JSON format and sends it to the server. Specifically, the user interface allows them to visually confirm the flow of movement and set the necessary information.

[0174] Step 2:

[0175] The server accesses an external marketplace API to retrieve real-time information on jewelry. The input consists of requests received from the marketplace API, containing data including the type of jewelry, price, and inventory information. The server parses this data and stores it in an information repository. Specifically, it retrieves data via a RESTful API and extracts the necessary information.

[0176] Step 3:

[0177] The system captures the user's facial expressions using the camera on their device. Real-time facial imagery is obtained as input. Software on the device processes the image data using image analysis libraries such as OpenCV to identify the user's emotional state. The output generates emotional data as analysis results. Specifically, emotions such as joy, surprise, and relaxation are expressed numerically.

[0178] Step 4:

[0179] The server inputs emotion analysis results and market information into a generating AI model to create 3D designs for decorative items. Inputs include user emotion data, event layout data, and market information. The server uses prompts to instruct the generating AI model, which then outputs multiple 3D designs based on these prompts. Specifically, it might execute commands such as, "When the user is relaxed, generate a design with soft color tones."

[0180] Step 5:

[0181] The generated 3D design is presented to the user via the terminal. The input is 3D design data obtained from the server, and the output is visual data displayed in the user interface. The user selects the optimal decoration plan from the displayed designs and sends this selection information from the terminal to the server. Specifically, the user checks the design details on the screen and uses selection buttons to determine the option that suits them best.

[0182] (Application Example 2)

[0183] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0184] In wedding planning, there is a problem in obtaining personalized configuration proposals that accurately reflect the user's emotions. Conventional systems often provide uniform configuration plans without adequately considering the user's feelings, making it difficult to meet user expectations. Furthermore, it is difficult to provide optimal designs that take into account real-time market material information.

[0185] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0186] In this invention, the server includes means for the user to input design information for a meeting place, means for the server to acquire market material information in real time and store it in a database, and means for the server to identify the user's emotional state using an emotion analysis engine. This makes it possible to automatically generate personalized three-dimensional designs that reflect material information and are optimal for the user's emotional state.

[0187] A "user" is an entity that uses this system to input design information for a meeting place and obtain a personalized design plan.

[0188] "Meeting place design information" refers to the physical layout and configuration information of a specific location entered by the user.

[0189] A "server" is a central processing unit that manages information input by users and market component material information, and generates design plans based on that information.

[0190] "Market material composition information" refers to information such as the types, prices, and inventory of materials obtained from a specific market, and is used to generate design plans.

[0191] An "emotion analysis engine" is a system component that uses facial expression analysis technology to analyze the emotional state of a user.

[0192] "Three-dimensional design" refers to a three-dimensional configuration plan generated by the server based on user input information and emotional state.

[0193] A "generative AI model" is an artificial intelligence algorithm that automatically generates three-dimensional designs based on user-specific information and market data.

[0194] The system that realizes this invention consists of a user input device (such as a smartphone or head-mounted display), a server, and an external data source.

[0195] Users transmit design information for meeting places to a server via their input device. The server receives this information, acquires market material information in real time, and automatically stores it in a database. The server also uses an emotion analysis engine via a camera attached to the input device to identify the user's emotional state from their facial expressions.

[0196] The server uses a generative AI model to create a personalized 3D design based on the acquired information and emotional state. This design reflects the user's emotions and is displayed visually. The generated design is sent to the user's input device, enabling a virtual experience.

[0197] This system uses OpenCV and Dlib as software for facial expression analysis, and Python, TensorFlow, and Keras for data processing and calculations. Unity 3D and Blender are used for 3D design generation.

[0198] As a concrete example, a user launches an application on their smartphone and smiles at the camera. The system then interprets the smile, detects the emotion of "joy," and suggests a bright and lively design. This process happens in real time, allowing the user to see the options immediately.

[0199] An example of a prompt message is: "Build an application that identifies emotions from a user's facial expressions, generates a wedding floral arrangement design based on those emotions, and makes it possible to experience it in real time in a virtual space."

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] The user inputs design information for the meeting place into an input device (e.g., smartphone, head-mounted display). This input information is sent to a server. The server receives the input design information, converts it to the appropriate format, and stores it in a database.

[0203] Step 2:

[0204] The server retrieves market material information in real time via APIs to external data sources. This material information includes type, price, and stock status, and the server stores it in a database. This information is then used for 3D design generation.

[0205] Step 3:

[0206] The system uses a camera on the user's input device to capture the user's facial expressions in real time. The device collects the facial expression data and sends it to a server. The server analyzes this facial expression data using an emotion analysis engine to identify the user's emotional state (e.g., "joy," "surprise," etc.). Libraries such as OpenCV and Dlib are used for emotion analysis.

[0207] Step 4:

[0208] The server generates a 3D design using a generative AI model based on acquired design information, material information, and emotion data. The generative AI model is implemented using TensorFlow and Keras, and constructs the optimal design based on each individual element. The resulting design is visually appealing.

[0209] Step 5:

[0210] The generated 3D design is sent from the server to the user's input device. The device displays this design visually in real time, allowing the user to review and select the design through a virtual experience. The design is displayed using Unity 3D or Blender.

[0211] Step 6:

[0212] The user selects their preferred plan from the proposed designs. This selection information is sent to the server via the user's input device, and the server stores the selected plan in a database. The stored information is used for later review and adjustment.

[0213] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0214] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0215] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0219] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0220] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0221] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0222] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0223] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0224] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0225] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0226] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0227] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0228] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0229] This invention provides a system for efficiently selecting wedding venue decoration plans. Specific embodiments of the system are shown below.

[0230] The user begins by entering the layout information of the venue where their wedding will be held into the terminal. This layout information is provided as 3D model data, floor plans, etc. The terminal then sends the entered layout information to the server. This information is used as the basic data for the 3D floral arrangement simulation described later.

[0231] Next, the server collects real-time information on floral materials from the market. This is done using APIs provided by existing flower markets and includes data such as the type of flower, price, inventory information, and even seasonality. Based on this information, the server prepares to provide the optimal floral arrangement plan within the user's budget.

[0232] The server uses a generation AI model to generate 3D floral arrangement designs based on venue layout information entered by the user and acquired market data. This AI model is designed to suggest the most suitable floral arrangements while considering the venue's shape and atmosphere, as well as the user's budget.

[0233] Users can visually confirm 3D designs of floral arrangements sent from the server via their devices. The system offers floral arrangement options at various price points, i.e., "pine, bamboo, and plum" plans, allowing users to select the design they most desire based on the visual information.

[0234] To give a specific example, if a user chooses wedding venue A and requests a mid-range decoration plan within their budget, they send a 3D layout of the venue from their device to the server. After the server obtains market information, it uses AI to combine the most suitable mid-range floral materials for that layout and generates a 3D design. The user can then review the design on their device and select the one they are satisfied with.

[0235] In this way, the system provides a stress-free environment where users can select high-quality, budget-friendly interior floral plans through simple and intuitive operation.

[0236] The following describes the processing flow.

[0237] Step 1:

[0238] The user enters information about the venue layout for their wedding into the terminal. The terminal converts this information into the correct format and prepares to send it to the server.

[0239] Step 2:

[0240] The server receives the transmitted venue layout information and saves it to the database. This information is then used for subsequent 3D modeling.

[0241] Step 3:

[0242] The server obtains real-time flower information through an external flower market API. This information includes flower type, price, and availability.

[0243] Step 4:

[0244] The server uses an AI model generated based on venue layout information and market data to create multiple 3D floral arrangement designs tailored to the user's budget.

[0245] Step 5:

[0246] The server sends the generated floral design to the terminal and presents it to the user. The terminal displays this visually so that the user can confirm it.

[0247] Step 6:

[0248] The user uses their device to select their desired floral arrangement plan from the presented designs and sends that selection to the server.

[0249] Step 7:

[0250] The server saves the user's selected plan in a database, making it available later for detailed discussions and ordering procedures.

[0251] (Example 1)

[0252] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0253] In modern event planning, selecting decorations is often accompanied by detailed requests and budget constraints. There is a need to develop a system that can efficiently select the optimal decoration plan while addressing these demands and allowing for visual confirmation. Traditional methods require manual selection from a vast number of options, which is time-consuming and labor-intensive, often resulting in unsatisfactory outcomes for users.

[0254] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0255] In this invention, the server includes means for the user to input event venue layout information, means for the information processing device to immediately acquire information on decorative items from supply sources and store it in a data storage device, and means for the information processing device to use a generated artificial intelligence model to generate a three-dimensional design of decorative items based on the layout information input by the user and the acquired supply source data. This allows the user to quickly check decoration plans that suit their budget and preferences and select the optimal plan.

[0256] "Users" refer to individuals or organizations that operate the system to input event venue layout information and select decoration plans.

[0257] An "event venue" refers to a place where special events such as weddings and parties are held, and it is the space for which layout information is entered.

[0258] "Layout information" refers to data that details the layout, size, shape, and other characteristics of the event venue.

[0259] An "information processing device" refers to a device that has the function of acquiring and storing information on decorative items from a supply source, and processes the data within the system to generate a three-dimensional design.

[0260] "Supply source" refers to an external information provider that provides real-time information on decorative items.

[0261] "Jewelry information" refers to detailed data related to jewelry, such as the type of jewelry, price, availability, and seasonality.

[0262] A "data storage device" refers to a storage device used to store acquired information.

[0263] The term "generated artificial intelligence model" refers to a learning model designed to perform three-dimensional design according to the user's requirements.

[0264] "Three-dimensional design" refers to a three-dimensional digital model that visually represents how decorative items will be arranged.

[0265] A "display device" refers to a device used by users to visually confirm three-dimensional designs.

[0266] "Plan" refers to decorative plans that are prepared with different budget ranges and design options.

[0267] The following describes embodiments for carrying out the invention.

[0268] The user first inputs the layout information of the event venue into a terminal. This information is provided in the form of a 3D model or floor plan. The terminal sends the entered layout information to the server, which then receives the basic data.

[0269] The server retrieves information on decorative items from markets and suppliers. This process uses APIs provided by existing suppliers to collect data such as the type of decorative item, price, inventory information, and seasonality. This data is stored in a data storage device within the server and used in subsequent processes.

[0270] Next, the server uses a generative AI model to generate 3D designs of decorative items based on the placement information entered by the user and the acquired market data. This generative AI model considers shape, atmosphere, budget, etc., and proposes the optimal combination of decorative items. The AI ​​model receives the prompt "Based on the 3D layout of the event venue, please propose beautiful decorative designs within the price range desired by the user" as input and creates multiple design proposals.

[0271] The generated 3D design is sent from the server to the user's display device. The user can use the display device to visually confirm the proposed design. The user compares the various price ranges offered, such as "Pine, Bamboo, and Plum," and selects their preferred plan.

[0272] This system allows users to efficiently select decorations that fit their budget and preferences, shortening the selection process. This enables users to prepare for events effectively and quickly.

[0273] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0274] Step 1:

[0275] The user inputs the event venue layout information into a terminal. This information is input as 3D model data or floor plan. The terminal converts the input layout information into a data package and sends it to the server. Here, the input is the layout information, and the output is a data package converted into a data format usable by the server.

[0276] Step 2:

[0277] The server registers the placement information received from the terminal into the database. This information is used as the basic data for 3D design. The server converts the information to conform to its internal format and saves it to the database. The input is a data package of placement information, and the output is the placement information stored in the database.

[0278] Step 3:

[0279] The server obtains ornament information through an external supply source API. This information includes the type, price, inventory, and seasonality of the ornaments. The server sends requests to each API endpoint, organizes the obtained data, and stores it in the database. The input is the API response data, and the output is the organized ornament information.

[0280] Step 4:

[0281] The server generates a three-dimensional design using a generative AI model. The server uses the layout information and ornament information stored in the database as inputs, provides the AI model with the prompt sentence "Please propose a beautiful decoration design within the price range desired by the user based on the 3D layout of the event venue.", and generates multiple design proposals from the AI model. The input is the prompt sentence and the basic data, and the output is the generated three-dimensional design of the ornament.

[0282] Step 5:

[0283] The server sends the generated three-dimensional design to the user's display device. The user visually checks multiple designs using this information. The server converts the data into a format that can be displayed on the terminal and sends the information to the user. The input here is the three-dimensional design data, and the output is the data sent to the user's display device.

[0284] Step 6:

[0285] The user makes a selection from the visually checked design proposals. The selection information is sent from the terminal to the server, and the server records it. The user clicks on the preferred design on the selection screen and presses the confirmation button. The input is the design selected by the user, and the output is the recorded selection information.

[0286] (Application Example 1)

[0287] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0288] In the layout of a space and the selection of ornaments, it is a difficult task to efficiently propose an optimal decoration plan while balancing design and budget. In the conventional method, there are limitations in the time and accuracy of manually devising a space design, and cost management is also complicated. There is a need for a system that solves this problem and allows users to easily select a design.

[0289] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0290] In this invention, the server includes means for inputting layout information in a space, means for acquiring real-time market item information and storing it in a data storage, and means for generating a 3D design of ornaments based on the input layout information and the acquired market data using a generation AI model. As a result, the user can efficiently and effectively select an optimal decoration plan, visually confirm it, and then select a design.

[0291] The "layout information in a space" is information indicating the positions and layouts of items and ornaments in a specific physical space by the user.

[0292] The "market item information" is real-time data including the types, prices, inventory status, seasonality, etc. of items in a specific market.

[0293] The "data storage" is a storage device or area that stores the acquired data and enables retrieval and operations as needed.

[0294] The "generation AI model" is an artificial intelligence algorithm used to automatically generate an optimal design or design based on the input data.

[0295] A "visualization device" is a device used to display information or data so that humans can visually confirm it; examples include monitors and display devices.

[0296] "Selection information" refers to data about a specific item or plan that the user chose from among several options presented.

[0297] "Resource range" refers to the range of items and budget available to the user, and the conditions under which choices are made based on this range.

[0298] "Options" refer to multiple plans or options presented to the user, allowing the user to choose the one that best suits them.

[0299] The system that realizes this application is a platform that generates optimal 3D designs for decorative items by utilizing market item information based on spatial placement information entered by the user. The main elements of the system include a user terminal, a server, and a generating AI model.

[0300] Users input spatial layout information using devices such as smartphones and tablets. This information is detailed through descriptions and floor plans. The device sends this information to the server, which then retrieves market item information in real time. Market information includes data such as item type, price, inventory, and seasonality, and is retrieved via an API. The server stores this data in data storage.

[0301] The server uses a generative AI model (e.g., a model created with TensorFlow) to generate an optimal 3D design for the ornament based on acquired spatial placement information and market data. The generated design is sent to the user's visualization device, such as smart glasses or a head-mounted display, for a realistic visual representation. Based on this visualization, the user can consider and select from different options.

[0302] As a specific example, consider a case where a store owner wants to update the in-store display according to the season to make a new product stand out. The owner inputs the layout information of the store into a terminal, and the server generates a decoration design based on the latest flower material data obtained from the market. Then, the owner confirms the proposed multiple display designs through a visualization device and selects the most attractive one. This selection is fed back to the server at any time and reflected in the final decision.

[0303] Examples of prompt sentences include "I want to change the in-store display to a spring style. Please generate a fresh and fashionable design centered around cherry blossoms."

[0304] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0305] Step 1:

[0306] The user uses a terminal to input the layout information in the space. This input includes a floor plan and detailed descriptions. The input information is sent to the server in digital form. As output, the layout information data is stored in the server.

[0307] Step 2:

[0308] The server obtains the item information in the market in real time through an external API. The obtained data includes the type, price, inventory, seasonality, etc. of the items. The obtained information is stored in the data storage. The output here is a dataset of market item information.

[0309] Step 3:

[0310] <​​ Step 4:

[0312] The server sends the generated 3D design to the user's visualization device. The user visually confirms the 3D design through that device. The output is a realistic 3D design displayed on the visualization device.

[0313] Step 5:

[0314] The user selects a different plan based on the presented 3D design. The selected information is sent back to the server, which stores the selection information in its database. The output is the selection information data, which will be reflected in future design proposals.

[0315] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0316] This invention is a system for effectively selecting floral arrangements for weddings, providing floral designs that take into account the user's emotions. Embodiments of this system are described below.

[0317] First, the user enters the layout information of their chosen wedding venue into the terminal. The terminal formats the entered information appropriately and sends it to the server. The server uses this data as the basis for the floral design incorporating the emotion engine described later.

[0318] Next, the server uses an API from an external flower market to collect real-time information on floral materials. This information includes flower types, prices, and availability, and is used to select the most suitable floral materials that can be suggested within the user's budget.

[0319] A crucial component, the emotion engine, performs real-time facial expression analysis through the camera on the user's device. The emotion engine analyzes the user's facial expression data to identify emotional states such as joy or surprise. This makes it possible to provide a floral arrangement plan that is optimally suited to the user's emotions.

[0320] The server uses an AI model based on collected market information and sentiment analysis results to generate multiple 3D floral arrangement designs. The generated designs are presented to the user's visual system via the terminal, offered as choices that evoke joy and emotion.

[0321] For example, if a user expresses a relaxed mood through their facial expressions on their wedding day, the emotion engine analyzes this and instructs the server to generate a calming floral design. As a result, the user is presented with a floral arrangement plan that creates a relaxed atmosphere.

[0322] In this way, this system goes beyond mere visual effects, supporting more personalized wedding preparations by offering floral arrangement suggestions that resonate with the user's emotions. Users can select the optimal plan based on emotion-based feedback.

[0323] The following describes the processing flow.

[0324] Step 1:

[0325] The user enters the wedding venue layout information into the terminal. The terminal formats this data and sends it to the server.

[0326] Step 2:

[0327] The server saves the received layout information to a database. This information serves as the basic data necessary for generating the 3D design.

[0328] Step 3:

[0329] The server obtains real-time flower material information using APIs from partnered external flower markets. This ensures that the latest market data is available.

[0330] Step 4:

[0331] A camera installed on the user's device captures the user's facial expressions in real time. The device then sends this facial expression data to a server.

[0332] Step 5:

[0333] The server uses an emotion engine to analyze the user's facial expression data. It determines the user's emotional state and generates appropriate emotion tags.

[0334] Step 6:

[0335] The server uses an AI model to generate multiple 3D floral arrangement designs based on the analyzed emotion tags and market data.

[0336] Step 7:

[0337] The server sends the generated 3D design to the terminal. The terminal visually presents it to the user for confirmation.

[0338] Step 8:

[0339] The user selects their desired plan from the designs presented on their device. The selection information is sent to the server.

[0340] Step 9:

[0341] The server saves the selected plan to a database, which is then used for future order processing and feedback collection.

[0342] (Example 2)

[0343] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0344] Selecting decorations for celebratory events often results in uniform designs, as it's difficult to fully consider the feelings and wishes of the participants. Furthermore, finding the optimal decoration plan within a budget requires considerable time and effort. There is a need to solve this problem and provide a more personalized decoration experience.

[0345] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0346] This invention includes a server that acquires ornament information from the market in real time and stores it in an information collection, a means for generating a three-dimensional design of ornaments based on placement information input by the user and acquired market data using a generative model, and a means for an operating device to analyze the user's facial expressions and provide emotion-based feedback to the information processing device. This makes it possible to generate personalized ornament plans that take the user's emotions into account.

[0347] A "user" is defined as the entity that uses the operating device to select and customize the decoration plan for a celebratory event.

[0348] A "control device" is a computer device used by users to input data and confirm displayed information. This device is also equipped with a camera, which is used to analyze the user's emotional state.

[0349] An "information processing device" is a central processing unit that generates and manages decoration plans based on user-inputted data and acquired market information. It has the function of acquiring data in real time and performing analysis.

[0350] A "generative model" is an algorithm and program for generating three-dimensional designs of decorative items based on the user's emotional state and market data.

[0351] An "information collection" refers to a database structure where information on jewelry acquired from the market is stored. This database includes information such as the price, inventory, and type of jewelry.

[0352] "3D design" refers to design data for decorative plans that enables a three-dimensional visual representation presented to the user. This data indicates how decorative items should be arranged within the space.

[0353] "Emotion analysis" is the process of identifying a user's emotional state based on facial expression data obtained from a camera installed on the user's control device.

[0354] "Decorative items" is a general term for decorations such as flowers and objects used in celebratory events.

[0355] "Marketplace" refers to an external source of information that provides information on the types, prices, and inventory of decorative items.

[0356] This invention is a system for providing decoration plans based on user emotions. This system consists of an information processing device (server) and a terminal (operating device) for operating it. The following describes embodiments of this system.

[0357] Users input event layout information into a terminal. This terminal features a touchscreen and keyboard, allowing for easy data entry. The terminal converts the data to the required format and sends it to the information processing device. The software used includes a JSON format conversion library.

[0358] The information processing device accesses APIs of external information sources to obtain real-time information on jewelry from the market. Using a RESTful API, the retrieved information is parsed in JSON format and stored in an information collection. This information includes the type of jewelry, price, and inventory information.

[0359] Next, the device's camera is used to capture the user's facial expressions, and emotion analysis is performed. Image analysis libraries such as OpenCV are used to identify emotions such as joy, surprise, and relaxation from the user's facial expressions.

[0360] The information processing device inputs the results of sentiment analysis and market-derived data into a generating AI model. As a prompt, it instructs the model to generate a decoration plan that takes the user's emotions and budget into consideration. The generating AI model then generates multiple 3D designs to present to the user.

[0361] Finally, the generated 3D design is displayed to the user via a terminal. The user can select the best design from the displayed decoration plans and send the selection information to the information processing device for final confirmation and adjustment. This selection is made using a touchscreen or mouse input.

[0362] As an example of a prompt, entering "Generate a design that creates a relaxed atmosphere as a decoration plan for a celebratory event when the user is in a calm emotional state" makes it possible to present the optimal decoration plan that matches the user's wishes.

[0363] This system makes it possible to provide personalized decoration plans that are tailored to the individual feelings of each user.

[0364] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0365] Step 1:

[0366] The user inputs information about the celebratory event's layout into a terminal. This input includes seating arrangements, locations for decorations, and desired themes. The terminal converts this data into JSON format and sends it to the server. Specifically, the user interface allows them to visually confirm the flow of movement and set the necessary information.

[0367] Step 2:

[0368] The server accesses an external marketplace API to retrieve real-time information on jewelry. The input consists of requests received from the marketplace API, containing data including the type of jewelry, price, and inventory information. The server parses this data and stores it in an information repository. Specifically, it retrieves data via a RESTful API and extracts the necessary information.

[0369] Step 3:

[0370] The system captures the user's facial expressions using the camera on their device. Real-time facial imagery is obtained as input. Software on the device processes the image data using image analysis libraries such as OpenCV to identify the user's emotional state. The output generates emotional data as analysis results. Specifically, emotions such as joy, surprise, and relaxation are expressed numerically.

[0371] Step 4:

[0372] The server inputs emotion analysis results and market information into a generating AI model to create 3D designs for decorative items. Inputs include user emotion data, event layout data, and market information. The server uses prompts to instruct the generating AI model, which then outputs multiple 3D designs based on these prompts. Specifically, it might execute commands such as, "When the user is relaxed, generate a design with soft color tones."

[0373] Step 5:

[0374] The generated 3D design is presented to the user via the terminal. The input is 3D design data obtained from the server, and the output is visual data displayed in the user interface. The user selects the optimal decoration plan from the displayed designs and sends this selection information from the terminal to the server. Specifically, the user checks the design details on the screen and uses selection buttons to determine the option that suits them best.

[0375] (Application Example 2)

[0376] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0377] In wedding planning, there is a problem in obtaining personalized configuration proposals that accurately reflect the user's emotions. Conventional systems often provide uniform configuration plans without adequately considering the user's feelings, making it difficult to meet user expectations. Furthermore, it is difficult to provide optimal designs that take into account real-time market material information.

[0378] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0379] In this invention, the server includes means for the user to input design information for a meeting place, means for the server to acquire market material information in real time and store it in a database, and means for the server to identify the user's emotional state using an emotion analysis engine. This makes it possible to automatically generate personalized three-dimensional designs that reflect material information and are optimal for the user's emotional state.

[0380] A "user" is an entity that uses this system to input design information for a meeting place and obtain a personalized design plan.

[0381] "Meeting place design information" refers to the physical layout and configuration information of a specific location entered by the user.

[0382] A "server" is a central processing unit that manages information input by users and market component material information, and generates design plans based on that information.

[0383] "Market material composition information" refers to information such as the types, prices, and inventory of materials obtained from a specific market, and is used to generate design plans.

[0384] An "emotion analysis engine" is a system component that uses facial expression analysis technology to analyze the emotional state of a user.

[0385] "Three-dimensional design" refers to a three-dimensional configuration plan generated by the server based on user input information and emotional state.

[0386] A "generative AI model" is an artificial intelligence algorithm that automatically generates three-dimensional designs based on user-specific information and market data.

[0387] The system that realizes this invention consists of a user input device (such as a smartphone or head-mounted display), a server, and an external data source.

[0388] Users transmit design information for meeting places to a server via their input device. The server receives this information, acquires market material information in real time, and automatically stores it in a database. The server also uses an emotion analysis engine via a camera attached to the input device to identify the user's emotional state from their facial expressions.

[0389] The server uses a generative AI model to create a personalized 3D design based on the acquired information and emotional state. This design reflects the user's emotions and is displayed visually. The generated design is sent to the user's input device, enabling a virtual experience.

[0390] This system uses OpenCV and Dlib as software for facial expression analysis, and Python, TensorFlow, and Keras for data processing and calculations. Unity 3D and Blender are used for 3D design generation.

[0391] As a concrete example, a user launches an application on their smartphone and smiles at the camera. The system then interprets the smile, detects the emotion of "joy," and suggests a bright and lively design. This process happens in real time, allowing the user to see the options immediately.

[0392] An example of a prompt message is: "Build an application that identifies emotions from a user's facial expressions, generates a wedding floral arrangement design based on those emotions, and makes it possible to experience it in real time in a virtual space."

[0393] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0394] Step 1:

[0395] The user inputs design information for the meeting place into an input device (e.g., smartphone, head-mounted display). This input information is sent to a server. The server receives the input design information, converts it to the appropriate format, and stores it in a database.

[0396] Step 2:

[0397] The server retrieves market material information in real time via APIs to external data sources. This material information includes type, price, and stock status, and the server stores it in a database. This information is then used for 3D design generation.

[0398] Step 3:

[0399] The system uses a camera on the user's input device to capture the user's facial expressions in real time. The device collects the facial expression data and sends it to a server. The server analyzes this facial expression data using an emotion analysis engine to identify the user's emotional state (e.g., "joy," "surprise," etc.). Libraries such as OpenCV and Dlib are used for emotion analysis.

[0400] Step 4:

[0401] The server generates a 3D design using a generative AI model based on acquired design information, material information, and emotion data. The generative AI model is implemented using TensorFlow and Keras, and constructs the optimal design based on each individual element. The resulting design is visually appealing.

[0402] Step 5:

[0403] The generated 3D design is sent from the server to the user's input device. The device displays this design visually in real time, allowing the user to review and select the design through a virtual experience. The design is displayed using Unity 3D or Blender.

[0404] Step 6:

[0405] The user selects their preferred plan from the proposed designs. This selection information is sent to the server via the user's input device, and the server stores the selected plan in a database. The stored information is used for later review and adjustment.

[0406] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0407] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0408] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0409] [Third Embodiment]

[0410] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0411] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0412] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0413] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0414] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0415] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0416] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0417] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0418] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0419] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0420] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0421] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0422] This invention provides a system for efficiently selecting wedding venue decoration plans. Specific embodiments of the system are shown below.

[0423] The user begins by entering the layout information of the venue where their wedding will be held into the terminal. This layout information is provided as 3D model data, floor plans, etc. The terminal then sends the entered layout information to the server. This information is used as the basic data for the 3D floral arrangement simulation described later.

[0424] Next, the server collects real-time information on floral materials from the market. This is done using APIs provided by existing flower markets and includes data such as the type of flower, price, inventory information, and even seasonality. Based on this information, the server prepares to provide the optimal floral arrangement plan within the user's budget.

[0425] The server uses a generation AI model to generate 3D floral arrangement designs based on venue layout information entered by the user and acquired market data. This AI model is designed to suggest the most suitable floral arrangements while considering the venue's shape and atmosphere, as well as the user's budget.

[0426] Users can visually confirm 3D designs of floral arrangements sent from the server via their devices. The system offers floral arrangement options at various price points, i.e., "pine, bamboo, and plum" plans, allowing users to select the design they most desire based on the visual information.

[0427] To give a specific example, if a user chooses wedding venue A and requests a mid-range decoration plan within their budget, they send a 3D layout of the venue from their device to the server. After the server obtains market information, it uses AI to combine the most suitable mid-range floral materials for that layout and generates a 3D design. The user can then review the design on their device and select the one they are satisfied with.

[0428] In this way, the system provides a stress-free environment where users can select high-quality, budget-friendly interior floral plans through simple and intuitive operation.

[0429] The following describes the processing flow.

[0430] Step 1:

[0431] The user enters information about the venue layout for their wedding into the terminal. The terminal converts this information into the correct format and prepares to send it to the server.

[0432] Step 2:

[0433] The server receives the transmitted venue layout information and saves it to the database. This information is then used for subsequent 3D modeling.

[0434] Step 3:

[0435] The server obtains real-time flower information through an external flower market API. This information includes flower type, price, and availability.

[0436] Step 4:

[0437] The server uses an AI model generated based on venue layout information and market data to create multiple 3D floral arrangement designs tailored to the user's budget.

[0438] Step 5:

[0439] The server sends the generated floral design to the terminal and presents it to the user. The terminal displays this visually so that the user can confirm it.

[0440] Step 6:

[0441] The user uses their device to select their desired floral arrangement plan from the presented designs and sends that selection to the server.

[0442] Step 7:

[0443] The server saves the user's selected plan in a database, making it available later for detailed discussions and ordering procedures.

[0444] (Example 1)

[0445] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0446] In modern event planning, selecting decorations is often accompanied by detailed requests and budget constraints. There is a need to develop a system that can efficiently select the optimal decoration plan while addressing these demands and allowing for visual confirmation. Traditional methods require manual selection from a vast number of options, which is time-consuming and labor-intensive, often resulting in unsatisfactory outcomes for users.

[0447] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0448] In this invention, the server includes means for the user to input event venue layout information, means for the information processing device to immediately acquire information on decorative items from supply sources and store it in a data storage device, and means for the information processing device to use a generated artificial intelligence model to generate a three-dimensional design of decorative items based on the layout information input by the user and the acquired supply source data. This allows the user to quickly check decoration plans that suit their budget and preferences and select the optimal plan.

[0449] "Users" refer to individuals or organizations that operate the system to input event venue layout information and select decoration plans.

[0450] An "event venue" refers to a place where special events such as weddings and parties are held, and it is the space for which layout information is entered.

[0451] "Layout information" refers to data that details the layout, size, shape, and other characteristics of the event venue.

[0452] An "information processing device" refers to a device that has the function of acquiring and storing information on decorative items from a supply source, and processes the data within the system to generate a three-dimensional design.

[0453] "Supply source" refers to an external information provider that provides real-time information on decorative items.

[0454] "Jewelry information" refers to detailed data related to jewelry, such as the type of jewelry, price, availability, and seasonality.

[0455] A "data storage device" refers to a storage device used to store acquired information.

[0456] The term "generated artificial intelligence model" refers to a learning model designed to perform three-dimensional design according to the user's requirements.

[0457] "Three-dimensional design" refers to a three-dimensional digital model that visually represents how decorative items will be arranged.

[0458] A "display device" refers to a device used by users to visually confirm three-dimensional designs.

[0459] "Plan" refers to decorative plans that are prepared with different budget ranges and design options.

[0460] The following describes embodiments for carrying out the invention.

[0461] The user first inputs the layout information of the event venue into a terminal. This information is provided in the form of a 3D model or floor plan. The terminal sends the entered layout information to the server, which then receives the basic data.

[0462] The server retrieves information on decorative items from markets and suppliers. This process uses APIs provided by existing suppliers to collect data such as the type of decorative item, price, inventory information, and seasonality. This data is stored in a data storage device within the server and used in subsequent processes.

[0463] Next, the server uses a generative AI model to generate 3D designs of decorative items based on the placement information entered by the user and the acquired market data. This generative AI model considers shape, atmosphere, budget, etc., and proposes the optimal combination of decorative items. The AI ​​model receives the prompt "Based on the 3D layout of the event venue, please propose beautiful decorative designs within the price range desired by the user" as input and creates multiple design proposals.

[0464] The generated 3D design is sent from the server to the user's display device. The user can use the display device to visually confirm the proposed design. The user compares the various price ranges offered, such as "Pine, Bamboo, and Plum," and selects their preferred plan.

[0465] This system allows users to efficiently select decorations that fit their budget and preferences, shortening the selection process. This enables users to prepare for events effectively and quickly.

[0466] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0467] Step 1:

[0468] The user inputs the event venue layout information into a terminal. This information is input as 3D model data or floor plan. The terminal converts the input layout information into a data package and sends it to the server. Here, the input is the layout information, and the output is a data package converted into a data format usable by the server.

[0469] Step 2:

[0470] The server registers the placement information received from the terminal into the database. This information is used as the basic data for 3D design. The server converts the information to conform to its internal format and saves it to the database. The input is a data package of placement information, and the output is the placement information stored in the database.

[0471] Step 3:

[0472] The server retrieves jewelry information through external source APIs. This information includes the type of jewelry, price, inventory, and seasonality. The server sends requests to each API endpoint, organizes the obtained data, and stores it in a database. The input is API response data, and the output is the organized jewelry information.

[0473] Step 4:

[0474] The server generates 3D designs using a generative AI model. The server takes placement and decoration information stored in the database as input and provides the AI ​​model with the prompt "Based on the 3D layout of the event venue, please propose beautiful decoration designs within the user's desired price range." The AI ​​model then generates multiple design proposals. The input consists of the prompt and basic data, and the output is the generated 3D design of the decorations.

[0475] Step 5:

[0476] The server sends the generated 3D design to the user's display device. The user uses this information to visually review multiple designs. The server converts the data into a format viewable on the terminal and delivers the information to the user. Here, the input is the 3D design data, and the output is the data sent to the user's display device.

[0477] Step 6:

[0478] The user selects a design from visually reviewed options. The selection information is sent from the terminal to the server, which records it. The user clicks on their preferred design on the selection screen and presses the confirm button. The input is the user's selected design, and the output is the recorded selection information.

[0479] (Application Example 1)

[0480] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0481] Balancing design aesthetics with budget while efficiently proposing the optimal decoration plan for a space is a challenging task. Traditional methods involve manually designing spaces, which has limitations in terms of time and accuracy, and cost management is also cumbersome. A system is needed to solve these problems and allow users to easily select designs.

[0482] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0483] In this invention, the server includes means for inputting spatial arrangement information, means for acquiring market item information in real time and storing it in data storage, and means for generating a 3D design of the decorative item based on the input spatial arrangement information and acquired market data using a generative AI model. This allows the user to efficiently and effectively select the optimal decorative plan and choose a design after visual confirmation.

[0484] "In-spatial placement information" refers to information that allows a user to indicate the location and layout of items or decorations within a specific physical space.

[0485] "Market goods information" refers to real-time data including the types of goods, prices, inventory levels, and seasonality of goods in a specific market.

[0486] "Data storage" refers to a storage device or area that stores acquired data and allows it to be searched and manipulated as needed.

[0487] A "generative AI model" is an artificial intelligence algorithm used to automatically generate optimal designs and layouts based on input data.

[0488] A "visualization device" is a device used to display information or data so that humans can visually confirm it; examples include monitors and display devices.

[0489] "Selection information" refers to data about a specific item or plan that the user chose from among several options presented.

[0490] "Resource range" refers to the range of items and budget available to the user, and the conditions under which choices are made based on this range.

[0491] "Options" refer to multiple plans or options presented to the user, allowing the user to choose the one that best suits them.

[0492] The system that realizes this application is a platform that generates optimal 3D designs for decorative items by utilizing market item information based on spatial placement information entered by the user. The main elements of the system include a user terminal, a server, and a generating AI model.

[0493] Users input spatial layout information using devices such as smartphones and tablets. This information is detailed through descriptions and floor plans. The device sends this information to the server, which then retrieves market item information in real time. Market information includes data such as item type, price, inventory, and seasonality, and is retrieved via an API. The server stores this data in data storage.

[0494] The server uses a generative AI model (e.g., a model created with TensorFlow) to generate an optimal 3D design for the ornament based on acquired spatial placement information and market data. The generated design is sent to the user's visualization device, such as smart glasses or a head-mounted display, for a realistic visual representation. Based on this visualization, the user can consider and select from different options.

[0495] As a concrete example, consider a case where a store owner wants to update the in-store display to reflect the season in order to highlight new products. The owner inputs the store's layout information into a terminal, and the server generates decorative designs based on the latest floral material data obtained from the market. The owner then reviews several proposed display designs through a visualization device and selects the most appealing one. This selection is fed back to the server in real time and reflected in the final decision.

[0496] Examples of prompt messages include: "I'd like to change the in-store display to a spring theme. Please generate a refreshing and stylish design centered around cherry blossoms."

[0497] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0498] Step 1:

[0499] The user uses a terminal to input spatial layout information. This input includes floor plans and detailed descriptions. The input information is sent to the server in digital format. As output, the layout information data is stored on the server.

[0500] Step 2:

[0501] The server retrieves market item information in real time via an external API. This retrieved data includes item type, price, inventory, seasonality, and other information. The retrieved information is stored in data storage. The output here is a dataset of market item information.

[0502] Step 3:

[0503] The server uses a generating AI model to combine input placement information and market information to generate 3D designs for decorative items. The AI ​​model calculates the optimal placement of items using placement information data and item data, and outputs it as 3D data.

[0504] Step 4:

[0505] The server sends the generated 3D design to the user's visualization device. The user visually confirms the 3D design through that device. The output is a realistic 3D design displayed on the visualization device.

[0506] Step 5:

[0507] The user selects a different plan based on the presented 3D design. The selected information is sent back to the server, which stores the selection information in its database. The output is the selection information data, which will be reflected in future design proposals.

[0508] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0509] This invention is a system for effectively selecting floral arrangements for weddings, providing floral designs that take into account the user's emotions. Embodiments of this system are described below.

[0510] First, the user enters the layout information of their chosen wedding venue into the terminal. The terminal formats the entered information appropriately and sends it to the server. The server uses this data as the basis for the floral design incorporating the emotion engine described later.

[0511] Next, the server uses an API from an external flower market to collect real-time information on floral materials. This information includes flower types, prices, and availability, and is used to select the most suitable floral materials that can be suggested within the user's budget.

[0512] A crucial component, the emotion engine, performs real-time facial expression analysis through the camera on the user's device. The emotion engine analyzes the user's facial expression data to identify emotional states such as joy or surprise. This makes it possible to provide a floral arrangement plan that is optimally suited to the user's emotions.

[0513] The server uses an AI model based on collected market information and sentiment analysis results to generate multiple 3D floral arrangement designs. The generated designs are presented to the user's visual system via the terminal, offered as choices that evoke joy and emotion.

[0514] For example, if a user expresses a relaxed mood through their facial expressions on their wedding day, the emotion engine analyzes this and instructs the server to generate a calming floral design. As a result, the user is presented with a floral arrangement plan that creates a relaxed atmosphere.

[0515] In this way, this system goes beyond mere visual effects, supporting more personalized wedding preparations by offering floral arrangement suggestions that resonate with the user's emotions. Users can select the optimal plan based on emotion-based feedback.

[0516] The following describes the processing flow.

[0517] Step 1:

[0518] The user enters the wedding venue layout information into the terminal. The terminal formats this data and sends it to the server.

[0519] Step 2:

[0520] The server saves the received layout information to a database. This information serves as the basic data necessary for generating the 3D design.

[0521] Step 3:

[0522] The server obtains real-time flower material information using APIs from partnered external flower markets. This ensures that the latest market data is available.

[0523] Step 4:

[0524] A camera installed on the user's device captures the user's facial expressions in real time. The device then sends this facial expression data to a server.

[0525] Step 5:

[0526] The server uses an emotion engine to analyze the user's facial expression data. It determines the user's emotional state and generates appropriate emotion tags.

[0527] Step 6:

[0528] The server uses an AI model to generate multiple 3D floral arrangement designs based on the analyzed emotion tags and market data.

[0529] Step 7:

[0530] The server sends the generated 3D design to the terminal. The terminal visually presents it to the user for confirmation.

[0531] Step 8:

[0532] The user selects their desired plan from the designs presented on their device. The selection information is sent to the server.

[0533] Step 9:

[0534] The server saves the selected plan to a database, which is then used for future order processing and feedback collection.

[0535] (Example 2)

[0536] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0537] Selecting decorations for celebratory events often results in uniform designs, as it's difficult to fully consider the feelings and wishes of the participants. Furthermore, finding the optimal decoration plan within a budget requires considerable time and effort. There is a need to solve this problem and provide a more personalized decoration experience.

[0538] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0539] This invention includes a server that acquires ornament information from the market in real time and stores it in an information collection, a means for generating a three-dimensional design of ornaments based on placement information input by the user and acquired market data using a generative model, and a means for an operating device to analyze the user's facial expressions and provide emotion-based feedback to the information processing device. This makes it possible to generate personalized ornament plans that take the user's emotions into account.

[0540] A "user" is defined as the entity that uses the operating device to select and customize the decoration plan for a celebratory event.

[0541] A "control device" is a computer device used by users to input data and confirm displayed information. This device is also equipped with a camera, which is used to analyze the user's emotional state.

[0542] An "information processing device" is a central processing unit that generates and manages decoration plans based on user-inputted data and acquired market information. It has the function of acquiring data in real time and performing analysis.

[0543] A "generative model" is an algorithm and program for generating three-dimensional designs of decorative items based on the user's emotional state and market data.

[0544] An "information collection" refers to a database structure where information on jewelry acquired from the market is stored. This database includes information such as the price, inventory, and type of jewelry.

[0545] "3D design" refers to design data for decorative plans that enables a three-dimensional visual representation presented to the user. This data indicates how decorative items should be arranged within the space.

[0546] "Emotion analysis" is the process of identifying a user's emotional state based on facial expression data obtained from a camera installed on the user's control device.

[0547] "Decorative items" is a general term for decorations such as flowers and objects used in celebratory events.

[0548] "Marketplace" refers to an external source of information that provides information on the types, prices, and inventory of decorative items.

[0549] This invention is a system for providing decoration plans based on user emotions. This system consists of an information processing device (server) and a terminal (operating device) for operating it. The following describes embodiments of this system.

[0550] Users input event layout information into a terminal. This terminal features a touchscreen and keyboard, allowing for easy data entry. The terminal converts the data to the required format and sends it to the information processing device. The software used includes a JSON format conversion library.

[0551] The information processing device accesses APIs of external information sources to obtain real-time information on jewelry from the market. Using a RESTful API, the retrieved information is parsed in JSON format and stored in an information collection. This information includes the type of jewelry, price, and inventory information.

[0552] Next, the device's camera is used to capture the user's facial expressions, and emotion analysis is performed. Image analysis libraries such as OpenCV are used to identify emotions such as joy, surprise, and relaxation from the user's facial expressions.

[0553] The information processing device inputs the results of sentiment analysis and market-derived data into a generating AI model. As a prompt, it instructs the model to generate a decoration plan that takes the user's emotions and budget into consideration. The generating AI model then generates multiple 3D designs to present to the user.

[0554] Finally, the generated 3D design is displayed to the user via a terminal. The user can select the best design from the displayed decoration plans and send the selection information to the information processing device for final confirmation and adjustment. This selection is made using a touchscreen or mouse input.

[0555] As an example of a prompt, entering "Generate a design that creates a relaxed atmosphere as a decoration plan for a celebratory event when the user is in a calm emotional state" makes it possible to present the optimal decoration plan that matches the user's wishes.

[0556] This system makes it possible to provide personalized decoration plans that are tailored to the individual feelings of each user.

[0557] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0558] Step 1:

[0559] The user inputs information about the celebratory event's layout into a terminal. This input includes seating arrangements, locations for decorations, and desired themes. The terminal converts this data into JSON format and sends it to the server. Specifically, the user interface allows them to visually confirm the flow of movement and set the necessary information.

[0560] Step 2:

[0561] The server accesses an external marketplace API to retrieve real-time information on jewelry. The input consists of requests received from the marketplace API, containing data including the type of jewelry, price, and inventory information. The server parses this data and stores it in an information repository. Specifically, it retrieves data via a RESTful API and extracts the necessary information.

[0562] Step 3:

[0563] The system captures the user's facial expressions using the camera on their device. Real-time facial imagery is obtained as input. Software on the device processes the image data using image analysis libraries such as OpenCV to identify the user's emotional state. The output generates emotional data as analysis results. Specifically, emotions such as joy, surprise, and relaxation are expressed numerically.

[0564] Step 4:

[0565] The server inputs emotion analysis results and market information into a generating AI model to create 3D designs for decorative items. Inputs include user emotion data, event layout data, and market information. The server uses prompts to instruct the generating AI model, which then outputs multiple 3D designs based on these prompts. Specifically, it might execute commands such as, "When the user is relaxed, generate a design with soft color tones."

[0566] Step 5:

[0567] The generated 3D design is presented to the user via the terminal. The input is 3D design data obtained from the server, and the output is visual data displayed in the user interface. The user selects the optimal decoration plan from the displayed designs and sends this selection information from the terminal to the server. Specifically, the user checks the design details on the screen and uses selection buttons to determine the option that suits them best.

[0568] (Application Example 2)

[0569] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0570] In wedding planning, there is a problem in obtaining personalized configuration proposals that accurately reflect the user's emotions. Conventional systems often provide uniform configuration plans without adequately considering the user's feelings, making it difficult to meet user expectations. Furthermore, it is difficult to provide optimal designs that take into account real-time market material information.

[0571] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0572] In this invention, the server includes means for the user to input design information for a meeting place, means for the server to acquire market material information in real time and store it in a database, and means for the server to identify the user's emotional state using an emotion analysis engine. This makes it possible to automatically generate personalized three-dimensional designs that reflect material information and are optimal for the user's emotional state.

[0573] A "user" is an entity that uses this system to input design information for a meeting place and obtain a personalized design plan.

[0574] "Meeting place design information" refers to the physical layout and configuration information of a specific location entered by the user.

[0575] A "server" is a central processing unit that manages information input by users and market component material information, and generates design plans based on that information.

[0576] "Market material composition information" refers to information such as the types, prices, and inventory of materials obtained from a specific market, and is used to generate design plans.

[0577] An "emotion analysis engine" is a system component that uses facial expression analysis technology to analyze the emotional state of a user.

[0578] "Three-dimensional design" refers to a three-dimensional configuration plan generated by the server based on user input information and emotional state.

[0579] A "generative AI model" is an artificial intelligence algorithm that automatically generates three-dimensional designs based on user-specific information and market data.

[0580] The system that realizes this invention consists of a user input device (such as a smartphone or head-mounted display), a server, and an external data source.

[0581] Users transmit design information for meeting places to a server via their input device. The server receives this information, acquires market material information in real time, and automatically stores it in a database. The server also uses an emotion analysis engine via a camera attached to the input device to identify the user's emotional state from their facial expressions.

[0582] The server uses a generative AI model to create a personalized 3D design based on the acquired information and emotional state. This design reflects the user's emotions and is displayed visually. The generated design is sent to the user's input device, enabling a virtual experience.

[0583] This system uses OpenCV and Dlib as software for facial expression analysis, and Python, TensorFlow, and Keras for data processing and calculations. Unity 3D and Blender are used for 3D design generation.

[0584] As a concrete example, a user launches an application on their smartphone and smiles at the camera. The system then interprets the smile, detects the emotion of "joy," and suggests a bright and lively design. This process happens in real time, allowing the user to see the options immediately.

[0585] An example of a prompt message is: "Build an application that identifies emotions from a user's facial expressions, generates a wedding floral arrangement design based on those emotions, and makes it possible to experience it in real time in a virtual space."

[0586] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0587] Step 1:

[0588] The user inputs design information for the meeting place into an input device (e.g., smartphone, head-mounted display). This input information is sent to a server. The server receives the input design information, converts it to the appropriate format, and stores it in a database.

[0589] Step 2:

[0590] The server retrieves market material information in real time via APIs to external data sources. This material information includes type, price, and stock status, and the server stores it in a database. This information is then used for 3D design generation.

[0591] Step 3:

[0592] The system uses a camera on the user's input device to capture the user's facial expressions in real time. The device collects the facial expression data and sends it to a server. The server analyzes this facial expression data using an emotion analysis engine to identify the user's emotional state (e.g., "joy," "surprise," etc.). Libraries such as OpenCV and Dlib are used for emotion analysis.

[0593] Step 4:

[0594] The server generates a 3D design using a generative AI model based on acquired design information, material information, and emotion data. The generative AI model is implemented using TensorFlow and Keras, and constructs the optimal design based on each individual element. The resulting design is visually appealing.

[0595] Step 5:

[0596] The generated 3D design is sent from the server to the user's input device. The device displays this design visually in real time, allowing the user to review and select the design through a virtual experience. The design is displayed using Unity 3D or Blender.

[0597] Step 6:

[0598] The user selects their preferred plan from the proposed designs. This selection information is sent to the server via the user's input device, and the server stores the selected plan in a database. The stored information is used for later review and adjustment.

[0599] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0600] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0601] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0602] [Fourth Embodiment]

[0603] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0604] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0605] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0606] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0607] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0608] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0609] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0610] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors in the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0611] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0612] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0613] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0614] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0615] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0616] This invention provides a system for efficiently selecting wedding venue decoration plans. Specific embodiments of the system are shown below.

[0617] The user begins by entering the layout information of the venue where their wedding will be held into the terminal. This layout information is provided as 3D model data, floor plans, etc. The terminal then sends the entered layout information to the server. This information is used as the basic data for the 3D floral arrangement simulation described later.

[0618] Next, the server collects real-time information on floral materials from the market. This is done using APIs provided by existing flower markets and includes data such as the type of flower, price, inventory information, and even seasonality. Based on this information, the server prepares to provide the optimal floral arrangement plan within the user's budget.

[0619] The server uses a generation AI model to generate 3D floral arrangement designs based on venue layout information entered by the user and acquired market data. This AI model is designed to suggest the most suitable floral arrangements while considering the venue's shape and atmosphere, as well as the user's budget.

[0620] Users can visually confirm 3D designs of floral arrangements sent from the server via their devices. The system offers floral arrangement options at various price points, i.e., "pine, bamboo, and plum" plans, allowing users to select the design they most desire based on the visual information.

[0621] To give a specific example, if a user chooses wedding venue A and requests a mid-range decoration plan within their budget, they send a 3D layout of the venue from their device to the server. After the server obtains market information, it uses AI to combine the most suitable mid-range floral materials for that layout and generates a 3D design. The user can then review the design on their device and select the one they are satisfied with.

[0622] In this way, the system provides a stress-free environment where users can select high-quality, budget-friendly interior floral plans through simple and intuitive operation.

[0623] The following describes the processing flow.

[0624] Step 1:

[0625] The user enters information about the venue layout for their wedding into the terminal. The terminal converts this information into the correct format and prepares to send it to the server.

[0626] Step 2:

[0627] The server receives the transmitted venue layout information and saves it to the database. This information is then used for subsequent 3D modeling.

[0628] Step 3:

[0629] The server obtains real-time flower information through an external flower market API. This information includes flower type, price, and availability.

[0630] Step 4:

[0631] The server uses an AI model generated based on venue layout information and market data to create multiple 3D floral arrangement designs tailored to the user's budget.

[0632] Step 5:

[0633] The server sends the generated floral design to the terminal and presents it to the user. The terminal displays this visually so that the user can confirm it.

[0634] Step 6:

[0635] The user uses their device to select their desired floral arrangement plan from the presented designs and sends that selection to the server.

[0636] Step 7:

[0637] The server saves the user's selected plan in a database, making it available later for detailed discussions and ordering procedures.

[0638] (Example 1)

[0639] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0640] In modern event planning, selecting decorations is often accompanied by detailed requests and budget constraints. There is a need to develop a system that can efficiently select the optimal decoration plan while addressing these demands and allowing for visual confirmation. Traditional methods require manual selection from a vast number of options, which is time-consuming and labor-intensive, often resulting in unsatisfactory outcomes for users.

[0641] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0642] In this invention, the server includes means for the user to input event venue layout information, means for the information processing device to immediately acquire information on decorative items from supply sources and store it in a data storage device, and means for the information processing device to use a generated artificial intelligence model to generate a three-dimensional design of decorative items based on the layout information input by the user and the acquired supply source data. This allows the user to quickly check decoration plans that suit their budget and preferences and select the optimal plan.

[0643] "Users" refer to individuals or organizations that operate the system to input event venue layout information and select decoration plans.

[0644] An "event venue" refers to a place where special events such as weddings and parties are held, and it is the space for which layout information is entered.

[0645] "Layout information" refers to data that details the layout, size, shape, and other characteristics of the event venue.

[0646] An "information processing device" refers to a device that has the function of acquiring and storing information on decorative items from a supply source, and processes the data within the system to generate a three-dimensional design.

[0647] "Supply source" refers to an external information provider that provides real-time information on decorative items.

[0648] "Jewelry information" refers to detailed data related to jewelry, such as the type of jewelry, price, availability, and seasonality.

[0649] A "data storage device" refers to a storage device used to store acquired information.

[0650] The term "generated artificial intelligence model" refers to a learning model designed to perform three-dimensional design according to the user's requirements.

[0651] "Three-dimensional design" refers to a three-dimensional digital model that visually represents how decorative items will be arranged.

[0652] A "display device" refers to a device used by users to visually confirm three-dimensional designs.

[0653] "Plan" refers to decorative plans that are prepared with different budget ranges and design options.

[0654] The following describes embodiments for carrying out the invention.

[0655] The user first inputs the layout information of the event venue into a terminal. This information is provided in the form of a 3D model or floor plan. The terminal sends the entered layout information to the server, which then receives the basic data.

[0656] The server retrieves information on decorative items from markets and suppliers. This process uses APIs provided by existing suppliers to collect data such as the type of decorative item, price, inventory information, and seasonality. This data is stored in a data storage device within the server and used in subsequent processes.

[0657] Next, the server uses a generative AI model to generate 3D designs of decorative items based on the placement information entered by the user and the acquired market data. This generative AI model considers shape, atmosphere, budget, etc., and proposes the optimal combination of decorative items. The AI ​​model receives the prompt "Based on the 3D layout of the event venue, please propose beautiful decorative designs within the price range desired by the user" as input and creates multiple design proposals.

[0658] The generated 3D design is sent from the server to the user's display device. The user can use the display device to visually confirm the proposed design. The user compares the various price ranges offered, such as "Pine, Bamboo, and Plum," and selects their preferred plan.

[0659] This system allows users to efficiently select decorations that fit their budget and preferences, shortening the selection process. This enables users to prepare for events effectively and quickly.

[0660] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0661] Step 1:

[0662] The user inputs the event venue layout information into a terminal. This information is input as 3D model data or floor plan. The terminal converts the input layout information into a data package and sends it to the server. Here, the input is the layout information, and the output is a data package converted into a data format usable by the server.

[0663] Step 2:

[0664] The server registers the placement information received from the terminal into the database. This information is used as the basic data for 3D design. The server converts the information to conform to its internal format and saves it to the database. The input is a data package of placement information, and the output is the placement information stored in the database.

[0665] Step 3:

[0666] The server retrieves jewelry information through external source APIs. This information includes the type of jewelry, price, inventory, and seasonality. The server sends requests to each API endpoint, organizes the obtained data, and stores it in a database. The input is API response data, and the output is the organized jewelry information.

[0667] Step 4:

[0668] The server generates 3D designs using a generative AI model. The server takes placement and decoration information stored in the database as input and provides the AI ​​model with the prompt "Based on the 3D layout of the event venue, please propose beautiful decoration designs within the user's desired price range." The AI ​​model then generates multiple design proposals. The input consists of the prompt and basic data, and the output is the generated 3D design of the decorations.

[0669] Step 5:

[0670] The server sends the generated 3D design to the user's display device. The user uses this information to visually review multiple designs. The server converts the data into a format viewable on the terminal and delivers the information to the user. Here, the input is the 3D design data, and the output is the data sent to the user's display device.

[0671] Step 6:

[0672] The user selects a design from visually reviewed options. The selection information is sent from the terminal to the server, which records it. The user clicks on their preferred design on the selection screen and presses the confirm button. The input is the user's selected design, and the output is the recorded selection information.

[0673] (Application Example 1)

[0674] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0675] Balancing design aesthetics with budget while efficiently proposing the optimal decoration plan for a space is a challenging task. Traditional methods involve manually designing spaces, which has limitations in terms of time and accuracy, and cost management is also cumbersome. A system is needed to solve these problems and allow users to easily select designs.

[0676] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0677] In this invention, the server includes means for inputting spatial arrangement information, means for acquiring market item information in real time and storing it in data storage, and means for generating a 3D design of the decorative item based on the input spatial arrangement information and acquired market data using a generative AI model. This allows the user to efficiently and effectively select the optimal decorative plan and choose a design after visual confirmation.

[0678] "In-spatial placement information" refers to information that allows a user to indicate the location and layout of items or decorations within a specific physical space.

[0679] "Market goods information" refers to real-time data including the types of goods, prices, inventory levels, and seasonality of goods in a specific market.

[0680] "Data storage" refers to a storage device or area that stores acquired data and allows it to be searched and manipulated as needed.

[0681] A "generative AI model" is an artificial intelligence algorithm used to automatically generate optimal designs and layouts based on input data.

[0682] A "visualization device" is a device used to display information or data so that humans can visually confirm it; examples include monitors and display devices.

[0683] "Selection information" refers to data about a specific item or plan that the user chose from among several options presented.

[0684] "Resource range" refers to the range of items and budget available to the user, and the conditions under which choices are made based on this range.

[0685] "Options" refer to multiple plans or options presented to the user, allowing the user to choose the one that best suits them.

[0686] The system that realizes this application is a platform that generates optimal 3D designs for decorative items by utilizing market item information based on spatial placement information entered by the user. The main elements of the system include a user terminal, a server, and a generating AI model.

[0687] Users input spatial layout information using devices such as smartphones and tablets. This information is detailed through descriptions and floor plans. The device sends this information to the server, which then retrieves market item information in real time. Market information includes data such as item type, price, inventory, and seasonality, and is retrieved via an API. The server stores this data in data storage.

[0688] The server uses a generative AI model (e.g., a model created with TensorFlow) to generate an optimal 3D design for the ornament based on acquired spatial placement information and market data. The generated design is sent to the user's visualization device, such as smart glasses or a head-mounted display, for a realistic visual representation. Based on this visualization, the user can consider and select from different options.

[0689] As a concrete example, consider a case where a store owner wants to update the in-store display to reflect the season in order to highlight new products. The owner inputs the store's layout information into a terminal, and the server generates decorative designs based on the latest floral material data obtained from the market. The owner then reviews several proposed display designs through a visualization device and selects the most appealing one. This selection is fed back to the server in real time and reflected in the final decision.

[0690] Examples of prompt messages include: "I'd like to change the in-store display to a spring theme. Please generate a refreshing and stylish design centered around cherry blossoms."

[0691] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0692] Step 1:

[0693] The user uses a terminal to input spatial layout information. This input includes floor plans and detailed descriptions. The input information is sent to the server in digital format. As output, the layout information data is stored on the server.

[0694] Step 2:

[0695] The server retrieves market item information in real time via an external API. This retrieved data includes item type, price, inventory, seasonality, and other information. The retrieved information is stored in data storage. The output here is a dataset of market item information.

[0696] Step 3:

[0697] The server uses a generating AI model to combine input placement information and market information to generate 3D designs for decorative items. The AI ​​model calculates the optimal placement of items using placement information data and item data, and outputs it as 3D data.

[0698] Step 4:

[0699] The server sends the generated 3D design to the user's visualization device. The user visually confirms the 3D design through that device. The output is a realistic 3D design displayed on the visualization device.

[0700] Step 5:

[0701] The user selects a different plan based on the presented 3D design. The selected information is sent back to the server, which stores the selection information in its database. The output is the selection information data, which will be reflected in future design proposals.

[0702] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0703] This invention is a system for effectively selecting floral arrangements for weddings, providing floral designs that take into account the user's emotions. Embodiments of this system are described below.

[0704] First, the user enters the layout information of their chosen wedding venue into the terminal. The terminal formats the entered information appropriately and sends it to the server. The server uses this data as the basis for the floral design incorporating the emotion engine described later.

[0705] Next, the server uses an API from an external flower market to collect real-time information on floral materials. This information includes flower types, prices, and availability, and is used to select the most suitable floral materials that can be suggested within the user's budget.

[0706] A crucial component, the emotion engine, performs real-time facial expression analysis through the camera on the user's device. The emotion engine analyzes the user's facial expression data to identify emotional states such as joy or surprise. This makes it possible to provide a floral arrangement plan that is optimally suited to the user's emotions.

[0707] The server uses an AI model based on collected market information and sentiment analysis results to generate multiple 3D floral arrangement designs. The generated designs are presented to the user's visual system via the terminal, offered as choices that evoke joy and emotion.

[0708] For example, if a user expresses a relaxed mood through their facial expressions on their wedding day, the emotion engine analyzes this and instructs the server to generate a calming floral design. As a result, the user is presented with a floral arrangement plan that creates a relaxed atmosphere.

[0709] In this way, this system goes beyond mere visual effects, supporting more personalized wedding preparations by offering floral arrangement suggestions that resonate with the user's emotions. Users can select the optimal plan based on emotion-based feedback.

[0710] The following describes the processing flow.

[0711] Step 1:

[0712] The user enters the wedding venue layout information into the terminal. The terminal formats this data and sends it to the server.

[0713] Step 2:

[0714] The server saves the received layout information to a database. This information serves as the basic data necessary for generating the 3D design.

[0715] Step 3:

[0716] The server obtains real-time flower material information using APIs from partnered external flower markets. This ensures that the latest market data is available.

[0717] Step 4:

[0718] A camera installed on the user's device captures the user's facial expressions in real time. The device then sends this facial expression data to a server.

[0719] Step 5:

[0720] The server uses an emotion engine to analyze the user's facial expression data. It determines the user's emotional state and generates appropriate emotion tags.

[0721] Step 6:

[0722] The server uses an AI model to generate multiple 3D floral arrangement designs based on the analyzed emotion tags and market data.

[0723] Step 7:

[0724] The server sends the generated 3D design to the terminal. The terminal visually presents it to the user for confirmation.

[0725] Step 8:

[0726] The user selects their desired plan from the designs presented on their device. The selection information is sent to the server.

[0727] Step 9:

[0728] The server saves the selected plan to a database, which is then used for future order processing and feedback collection.

[0729] (Example 2)

[0730] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0731] Selecting decorations for celebratory events often results in uniform designs, as it's difficult to fully consider the feelings and wishes of the participants. Furthermore, finding the optimal decoration plan within a budget requires considerable time and effort. There is a need to solve this problem and provide a more personalized decoration experience.

[0732] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0733] This invention includes a server that acquires ornament information from the market in real time and stores it in an information collection, a means for generating a three-dimensional design of ornaments based on placement information input by the user and acquired market data using a generative model, and a means for an operating device to analyze the user's facial expressions and provide emotion-based feedback to the information processing device. This makes it possible to generate personalized ornament plans that take the user's emotions into account.

[0734] A "user" is defined as the entity that uses the operating device to select and customize the decoration plan for a celebratory event.

[0735] A "control device" is a computer device used by users to input data and confirm displayed information. This device is also equipped with a camera, which is used to analyze the user's emotional state.

[0736] An "information processing device" is a central processing unit that generates and manages decoration plans based on user-inputted data and acquired market information. It has the function of acquiring data in real time and performing analysis.

[0737] A "generative model" is an algorithm and program for generating three-dimensional designs of decorative items based on the user's emotional state and market data.

[0738] An "information collection" refers to a database structure where information on jewelry acquired from the market is stored. This database includes information such as the price, inventory, and type of jewelry.

[0739] "3D design" refers to design data for decorative plans that enables a three-dimensional visual representation presented to the user. This data indicates how decorative items should be arranged within the space.

[0740] "Emotion analysis" is the process of identifying a user's emotional state based on facial expression data obtained from a camera installed on the user's control device.

[0741] "Decorative items" is a general term for decorations such as flowers and objects used in celebratory events.

[0742] "Marketplace" refers to an external source of information that provides information on the types, prices, and inventory of decorative items.

[0743] This invention is a system for providing decoration plans based on user emotions. This system consists of an information processing device (server) and a terminal (operating device) for operating it. The following describes embodiments of this system.

[0744] Users input event layout information into a terminal. This terminal features a touchscreen and keyboard, allowing for easy data entry. The terminal converts the data to the required format and sends it to the information processing device. The software used includes a JSON format conversion library.

[0745] The information processing device accesses APIs of external information sources to obtain real-time information on jewelry from the market. Using a RESTful API, the retrieved information is parsed in JSON format and stored in an information collection. This information includes the type of jewelry, price, and inventory information.

[0746] Next, the device's camera is used to capture the user's facial expressions, and emotion analysis is performed. Image analysis libraries such as OpenCV are used to identify emotions such as joy, surprise, and relaxation from the user's facial expressions.

[0747] The information processing device inputs the results of sentiment analysis and market-derived data into a generating AI model. As a prompt, it instructs the model to generate a decoration plan that takes the user's emotions and budget into consideration. The generating AI model then generates multiple 3D designs to present to the user.

[0748] Finally, the generated 3D design is displayed to the user via a terminal. The user can select the best design from the displayed decoration plans and send the selection information to the information processing device for final confirmation and adjustment. This selection is made using a touchscreen or mouse input.

[0749] As an example of a prompt, entering "Generate a design that creates a relaxed atmosphere as a decoration plan for a celebratory event when the user is in a calm emotional state" makes it possible to present the optimal decoration plan that matches the user's wishes.

[0750] This system makes it possible to provide personalized decoration plans that are tailored to the individual feelings of each user.

[0751] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0752] Step 1:

[0753] The user inputs information about the celebratory event's layout into a terminal. This input includes seating arrangements, locations for decorations, and desired themes. The terminal converts this data into JSON format and sends it to the server. Specifically, the user interface allows them to visually confirm the flow of movement and set the necessary information.

[0754] Step 2:

[0755] The server accesses an external marketplace API to retrieve real-time information on jewelry. The input consists of requests received from the marketplace API, containing data including the type of jewelry, price, and inventory information. The server parses this data and stores it in an information repository. Specifically, it retrieves data via a RESTful API and extracts the necessary information.

[0756] Step 3:

[0757] The system captures the user's facial expressions using the camera on their device. Real-time facial imagery is obtained as input. Software on the device processes the image data using image analysis libraries such as OpenCV to identify the user's emotional state. The output generates emotional data as analysis results. Specifically, emotions such as joy, surprise, and relaxation are expressed numerically.

[0758] Step 4:

[0759] The server inputs emotion analysis results and market information into a generating AI model to create 3D designs for decorative items. Inputs include user emotion data, event layout data, and market information. The server uses prompts to instruct the generating AI model, which then outputs multiple 3D designs based on these prompts. Specifically, it might execute commands such as, "When the user is relaxed, generate a design with soft color tones."

[0760] Step 5:

[0761] The generated 3D design is presented to the user via the terminal. The input is 3D design data obtained from the server, and the output is visual data displayed in the user interface. The user selects the optimal decoration plan from the displayed designs and sends this selection information from the terminal to the server. Specifically, the user checks the design details on the screen and uses selection buttons to determine the option that suits them best.

[0762] (Application Example 2)

[0763] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0764] In wedding planning, there is a problem in obtaining personalized configuration proposals that accurately reflect the user's emotions. Conventional systems often provide uniform configuration plans without adequately considering the user's feelings, making it difficult to meet user expectations. Furthermore, it is difficult to provide optimal designs that take into account real-time market material information.

[0765] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0766] In this invention, the server includes means for the user to input design information for a meeting place, means for the server to acquire market material information in real time and store it in a database, and means for the server to identify the user's emotional state using an emotion analysis engine. This makes it possible to automatically generate personalized three-dimensional designs that reflect material information and are optimal for the user's emotional state.

[0767] A "user" is an entity that uses this system to input design information for a meeting place and obtain a personalized design plan.

[0768] "Meeting place design information" refers to the physical layout and configuration information of a specific location entered by the user.

[0769] A "server" is a central processing unit that manages information input by users and market component material information, and generates design plans based on that information.

[0770] "Market material composition information" refers to information such as the types, prices, and inventory of materials obtained from a specific market, and is used to generate design plans.

[0771] An "emotion analysis engine" is a system component that uses facial expression analysis technology to analyze the emotional state of a user.

[0772] "Three-dimensional design" refers to a three-dimensional configuration plan generated by the server based on user input information and emotional state.

[0773] A "generative AI model" is an artificial intelligence algorithm that automatically generates three-dimensional designs based on user-specific information and market data.

[0774] The system that realizes this invention consists of a user input device (such as a smartphone or head-mounted display), a server, and an external data source.

[0775] Users transmit design information for meeting places to a server via their input device. The server receives this information, acquires market material information in real time, and automatically stores it in a database. The server also uses an emotion analysis engine via a camera attached to the input device to identify the user's emotional state from their facial expressions.

[0776] The server uses a generative AI model to create a personalized 3D design based on the acquired information and emotional state. This design reflects the user's emotions and is displayed visually. The generated design is sent to the user's input device, enabling a virtual experience.

[0777] This system uses OpenCV and Dlib as software for facial expression analysis, and Python, TensorFlow, and Keras for data processing and calculations. Unity 3D and Blender are used for 3D design generation.

[0778] As a concrete example, a user launches an application on their smartphone and smiles at the camera. The system then interprets the smile, detects the emotion of "joy," and suggests a bright and lively design. This process happens in real time, allowing the user to see the options immediately.

[0779] An example of a prompt message is: "Build an application that identifies emotions from a user's facial expressions, generates a wedding floral arrangement design based on those emotions, and makes it possible to experience it in real time in a virtual space."

[0780] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0781] Step 1:

[0782] The user inputs design information for the meeting place into an input device (e.g., smartphone, head-mounted display). This input information is sent to a server. The server receives the input design information, converts it to the appropriate format, and stores it in a database.

[0783] Step 2:

[0784] The server retrieves market material information in real time via APIs to external data sources. This material information includes type, price, and stock status, and the server stores it in a database. This information is then used for 3D design generation.

[0785] Step 3:

[0786] The system uses a camera on the user's input device to capture the user's facial expressions in real time. The device collects the facial expression data and sends it to a server. The server analyzes this facial expression data using an emotion analysis engine to identify the user's emotional state (e.g., "joy," "surprise," etc.). Libraries such as OpenCV and Dlib are used for emotion analysis.

[0787] Step 4:

[0788] The server generates a 3D design using a generative AI model based on acquired design information, material information, and emotion data. The generative AI model is implemented using TensorFlow and Keras, and constructs the optimal design based on each individual element. The resulting design is visually appealing.

[0789] Step 5:

[0790] The generated 3D design is sent from the server to the user's input device. The device displays this design visually in real time, allowing the user to review and select the design through a virtual experience. The design is displayed using Unity 3D or Blender.

[0791] Step 6:

[0792] The user selects their preferred plan from the proposed designs. This selection information is sent to the server via the user's input device, and the server stores the selected plan in a database. The stored information is used for later review and adjustment.

[0793] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0794] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0795] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0796] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0797] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0798] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0799] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0800] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0801] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0802] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0803] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0804] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0805] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0806] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0807] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0808] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0809] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0810] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0811] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0812] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0813] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0814] The following is further disclosed regarding the embodiments described above.

[0815] (Claim 1)

[0816] A means for users to input information about the layout of the wedding venue,

[0817] A means for the server to acquire market flower material information in real time and store it in a database,

[0818] A means for generating 3D designs of decorative flowers using a server-generated AI model based on layout information entered by the user and acquired market data,

[0819] A means of sending the generated 3D design to the user's device and displaying it visually,

[0820] A system including means for a user to select a different plan and send that selection information to a server.

[0821] (Claim 2)

[0822] The system according to claim 1, wherein the server automatically generates multiple options in different price ranges according to the user's budget.

[0823] (Claim 3)

[0824] The system according to claim 1, wherein the server stores the selected plan and provides information for final confirmation and adjustment.

[0825] "Example 1"

[0826] (Claim 1)

[0827] A means for users to input information about the layout of the event venue,

[0828] A means by which an information processing device instantly acquires information on the supply source of decorative items and stores it in a data storage device,

[0829] A means for generating a three-dimensional design of an ornament using an artificial intelligence model generated by an information processing device, based on placement information input by the user and acquired source data,

[0830] A means for transmitting the generated 3D design to the user's display device and outputting it visually,

[0831] A means for a user to select a different plan and transmit that selection information to an information processing device,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, wherein the information processing device automatically generates multiple options in different price ranges according to the user's budget.

[0835] (Claim 3)

[0836] The system according to claim 1, wherein the information processing device stores the selected plan and provides information for final confirmation and adjustment.

[0837] "Application Example 1"

[0838] (Claim 1)

[0839] A means of inputting spatial arrangement information,

[0840] A means by which a server acquires market item information in real time and stores it in data storage,

[0841] A means for generating a 3D design of an ornament using a server-generated AI model based on input placement information and acquired market data,

[0842] A means of transmitting the generated 3D design to the user's visualization device and representing it visually,

[0843] A means for a user to select a different option and send that selection information to the server,

[0844] A system that includes this.

[0845] (Claim 2)

[0846] The system according to claim 1, wherein the server automatically generates multiple options in different price ranges according to the user's resource scope.

[0847] (Claim 3)

[0848] The system according to claim 1, wherein the server stores the selected plan and provides information for final confirmation and adjustment.

[0849] "Example 2 of combining an emotion engine"

[0850] (Claim 1)

[0851] A means for users to input placement information for the celebratory event,

[0852] A means for an information processing device to acquire information on decorative items from the market in real time and store it in an information collection,

[0853] An information processing device uses a generation model to generate a three-dimensional design of an ornament based on placement information input by the user and acquired market data, and

[0854] A means for transmitting the generated 3D design to the user's control device and displaying it visually,

[0855] A means for a user to select different options and transmit that selection information to an information processing device,

[0856] A means by which an operating device analyzes the user's facial expressions and provides emotion-based feedback to an information processing device,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, wherein the information processing device automatically generates multiple options suitable for different price ranges and emotions, according to the user's budget range and emotion analysis results.

[0860] (Claim 3)

[0861] The system according to claim 1, wherein the information processing device stores the selected plan and provides information for final confirmation and adjustment.

[0862] "Application example 2 when combining with an emotional engine"

[0863] (Claim 1)

[0864] A means for users to input design information for the meeting place,

[0865] A means for the server to acquire market component material information in real time and store it in a database,

[0866] The server uses an emotion analysis engine to identify the user's emotional state,

[0867] A means for generating a three-dimensional design using a server-generated AI model, based on design information input by the user, acquired market data, and sentiment analysis results.

[0868] A means for transmitting the generated three-dimensional design to the user's device and displaying it visually,

[0869] A system including means for a user to select a different plan and send that selection information to a server.

[0870] (Claim 2)

[0871] The system according to claim 1, wherein the server automatically generates multiple options in different price ranges according to the user's budget.

[0872] (Claim 3)

[0873] The system according to claim 1, wherein the server stores the selected plan and provides information for final confirmation and adjustment. [Explanation of Symbols]

[0874] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to input information about the layout of the wedding venue, A means for the server to acquire market flower material information in real time and store it in a database, A means for generating 3D designs of decorative flowers using a server-generated AI model based on layout information entered by the user and acquired market data, A means of sending the generated 3D design to the user's device and displaying it visually, A system including means for a user to select a different plan and send that selection information to a server.

2. The system according to claim 1, wherein the server automatically generates multiple options in different price ranges according to the user's budget.

3. The system according to claim 1, wherein the server saves the selected plan and provides information for final confirmation and adjustment.

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