system

Abstract

Provide a system. A user input means; an acquisition means for acquiring room size and style information from the input means; a generating means for generating an optimal furniture layout based on the room size and style information acquired by the acquiring means; a search means for searching for furniture information from an online shopping platform based on the layout information generated by the generation means; an acquisition means for acquiring the furniture information acquired by the search means; a display means for displaying the furniture information and furniture layout acquired by the acquisition means on a user terminal; A system including:

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Many users today find it difficult to plan the optimal furniture layout to fit the dimensions and style of their room. It's also not easy to find the right furniture and purchase it at an affordable price. Given this background, there is a need for a system that can suggest furniture layouts that fit the dimensions and style of a room without spending a lot of time and effort, and easily find available furniture based on that. [Means for solving the problem]

[0005] The system generates an optimal furniture layout based on the dimensions and style information of a room entered by the user. Furthermore, it searches for furniture information from online shopping platforms based on the generated layout information and suggests affordable furniture.

[0006] The system includes the following means:

[0007] User input method

[0008] Acquisition method for obtaining room dimensions and style information

[0009] Generator for generating optimal furniture layouts based on room dimensions and style information

[0010] A search means for searching furniture information from an online shopping platform based on the generated layout information

[0011] Display means for displaying the acquired furniture information and furniture layout on the user terminal

[0012] This allows users to easily find the best furniture arrangement for their room and purchase that furniture at an affordable price.

[0013] "User input means" refers to the means by which a user inputs room size and style information.

[0014] The "acquisition means" is a means for acquiring room size and style information from the user's input means.

[0015] The "generating means" is a means for generating an optimal furniture layout based on the room size and style information acquired by the acquiring means.

[0016] The "search means" is a means for searching for furniture information from the online shopping platform based on the layout information generated by the generation means.

[0017] The "display means" is a means for displaying the furniture information acquired by the acquisition means and the furniture layout generated by the generation means on the user terminal.

[0018] An "online shopping platform" refers to a website or app that allows you to purchase products over the internet. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram illustrating a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a 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.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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.

[0033] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] The present invention provides a system that generates an optimal furniture layout based on the dimensions and style information of a user's room and suggests furniture that can be purchased at an affordable price from an online shopping platform. The system is mainly configured as follows.

[0041] System Configuration

[0042] 1. User input method

[0043] The user uses an input form provided on the terminal to input the dimensions (for example, length, width, height) and style (modern, classic, etc.) of the room.

[0044] 2. Acquisition method

[0045] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[0046] 3. Generation means

[0047] The server executes an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[0048] 4. Search Methods

[0049] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[0050] 5. Display means

[0051] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[0052] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[0053] Program processing overview

[0054] User Input

[0055] The user enters the room information (dimensions, style) into the terminal using the input form. The entered data is converted into JSON format and sent to the server.

[0056] Data reception and analysis

[0057] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[0058] Layout Generation

[0059] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (for example, placing the sofa at position X=1, Y=1).

[0060] Furniture Search

[0061] The server searches for furniture using the API of the online shopping platform based on the generated layout information, and obtains the name, price, and purchase link for each piece of furniture.

[0062] Consolidating and sending results

[0063] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[0064] Displaying the results

[0065] The device receives the data sent from the server, analyzes it, and then displays the results to the user in a visual format, providing the user with a furniture layout diagram and each furniture option (with name, price, and purchase link).

[0066] Specific examples

[0067] If a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[0068] 1. The user inputs the length, width, height and style of the room.

[0069] 2. The terminal converts the input data into JSON format and sends it to the server.

[0070] 3. The server analyzes the received data and generates the optimal furniture layout.

[0071] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[0072] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[0073] 6. The device analyzes the received data and displays the results visually to the user.

[0074] The system allows users to easily find the furniture layout that best suits their room and purchase that furniture at an affordable price.

[0075] The processing flow will be explained below.

[0076] Step 1:

[0077] The user inputs the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form on the terminal.

[0078] Step 2:

[0079] The terminal converts the user input data into JSON format.

[0080] example:

[0081] json

[0082] {

[0083] "length": 5,

[0084] "width": 4,

[0085] "height": 3,

[0086] "style": "modern"

[0087] }

[0088] Step 3:

[0089] The terminal sends the data converted into JSON format to the server via an HTTP request.

[0090] Step 4:

[0091] The server receives and analyzes the JSON data sent from the device.

[0092] Step 5:

[0093] The server runs an algorithm to generate the optimal furniture layout based on the received data, calculating the placement of each piece of furniture based on the room dimensions and style information.

[0094] example:

[0095] json

[0096] {

[0097] "sofa": {"x": 1, "y": 1},

[0098] "table": {"x": 2, "y": 2},

[0099] "bed": {"x": 3, "y": 3}

[0100] }

[0101] Step 6:

[0102] The server sends furniture search requests to the APIs of multiple online shopping platforms based on the generated layout information. It creates search queries that include the names and characteristics of the furniture.

[0103] example:

[0104] Example request:

[0105] json

[0106] {

[0107] "query": "modern sofa",

[0108] "max_price": 30000

[0109] }

[0110] Step 7:

[0111] The server receives and analyzes the API responses from each platform.

[0112] Step 8:

[0113] The server formats the acquired furniture information and integrates it with the generated furniture layout information.

[0114] example:

[0115] json

[0116] {

[0117] "layout": {

[0118] "sofa": {"x": 1, "y": 1},

[0119] "table": {"x": 2, "y": 2},

[0120] "bed": {"x": 3, "y": 3}

[0121] },

[0122] "furniture": [

[0123] {"name": "Modern sofa", "price": 20000, "url": "https: / / example.com / sofa"},

[0124] {"name": "Glass Table", "price": 15000, "url": "https: / / example.com / table"},

[0125] {"name": "Comfortable Bed", "price": 30000, "url": "https: / / example.com / bed"}

[0126] ]

[0127] }

[0128] Step 9:

[0129] The server sends the formatted data in JSON format to the terminal.

[0130] Step 10:

[0131] The terminal analyzes the received JSON data and displays it to the user in a visually easy-to-understand format.

[0132] Step 11:

[0133] The user checks the proposed furniture layout and purchase link on the terminal and purchases the furniture as necessary.

[0134] Example 1

[0135] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0136] Conventionally, it is very time-consuming and requires specialized knowledge for users to manually design the optimal furniture layout that matches the dimensions and style of the room and then search for the appropriate furniture. Therefore, there is a need for a system that can efficiently generate the optimal layout and allow users to easily select and purchase the appropriate furniture.

[0137] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0138] In this invention, the server includes a user input means, an acquisition means for acquiring room size and style information from the input means, a means for converting the acquired room size and style information into JSON format and transmitting the converted information to the server, a generation means for the server to generate an optimal furniture layout based on the acquired room size and style information, a search means for searching for furniture information from an API of an online shopping platform based on the layout information generated by the generation means, a acquisition means for acquiring the furniture information acquired by the search means, a means for integrating the acquired furniture information and the generated furniture layout and transmitting the combined data to a terminal in JSON format, and a display means for analyzing the data received by the terminal and displaying the combined data to the user in a visual format. This allows users to efficiently generate optimal furniture layouts and easily select and purchase appropriate furniture.

[0139] "User input means" is an interface provided on the terminal for the user to input room size and style information.

[0140] "Acquisition means" refers to the function that acquires room dimensions and style information from the user's input means and converts it into JSON format.

[0141] "JSON format" is a data structure in JavaScript (registered trademark) Object Notation format, and is a method of expressing data in text format.

[0142] A "server" is a computer device that receives, analyzes, and processes data sent from an input means.

[0143] "Generator" refers to the functionality of the server that runs an algorithm to generate an optimal furniture layout based on room dimensions and style information.

[0144] The "search means" is a function for searching furniture information using the API of the online shopping platform based on the generated layout information.

[0145] An "online shopping platform" is a web service that provides product information and sells products via the Internet.

[0146] "API" stands for Application Programming Interface, and is an interface that allows software to provide and call functions to other software.

[0147] The "acquisition means" is a function that receives and processes furniture information acquired by the search means (used for a purpose different from the above-mentioned "acquisition means").

[0148] The "integration means" is a function that combines the generated furniture layout information and the acquired furniture information into a single data format (JSON format).

[0149] "Transmission means" refers to a function for transmitting the integrated data to the terminal.

[0150] The "analysis means" is a function that allows the terminal to process the JSON data received from the server and understand its structure.

[0151] "Display means" is a function of the terminal for visually presenting analyzed data to the user.

[0152] The present invention provides a system for generating an optimal furniture layout by a user inputting room dimensions and style information, and for suggesting affordable furniture from an online shopping platform based on the optimal furniture layout. The system includes the following means and processing steps:

[0153] System configuration

[0154] The system mainly consists of user input means, acquisition means, generation means, search means, integration means, transmission means, and display means. Specifically, the following hardware and software are used:

[0155] Hardware

[0156] User terminal: PC, tablet, smartphone, etc. Provides input and display means.

[0157] Server: A remotely located high-performance computer, cloud service, etc. that receives, analyzes, generates, searches, integrates, and transmits data.

[0158] software

[0159] Input Form: An HTML form that runs in a web browser, allowing users to enter room dimensions and style information.

[0160] JSON conversion library: A data format conversion library using JavaScript or other programming languages.

[0161] Server application: Implemented using Python's Flask framework, etc. Performs data analysis, layout generation, and API communication.

[0162] API: An API provided by an online shopping platform (e.g., Amazon) that acts as a search engine.

[0163] Presentation library: Visual presentation using HTML, CSS, and JavaScript.

[0164] Data processing and calculation

[0165] User Input

[0166] The user uses an input form on the terminal to input the dimensions of the room (e.g., 5 meters x 4 meters x 3 meters) and the style (e.g., modern), and the terminal acquires the input data.

[0167] Sending and Receiving Data

[0168] The device converts the acquired data into JSON format and sends it to the server. The server parses the received JSON data. For example, it receives data in the format {"length": 5, "width": 4, "height": 3, "style": "modern"}.

[0169] Generate layout

[0170] The server generates an optimal furniture layout based on the analyzed data. Specifically, a generation algorithm implemented in Python calculates the placement of each piece of furniture based on the room dimensions. For example, the sofa might be placed in the upper left corner of the room, and the table in the center.

[0171] Furniture Search

[0172] Based on the generated layout information, the server searches for furniture using the API of the online shopping platform, sending an HTTP request to the API endpoint to obtain the name, price, and purchase link of the appropriate furniture.

[0173] Consolidating and sending results

[0174] The server combines the acquired furniture information with the generated furniture layout information and sends it back to the device as JSON format data. For example, it generates data like this: {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}

[0175] Displaying the results

[0176] The device parses the JSON data received from the server and presents it visually to the user, for example, using HTML and JavaScript to display a furniture layout diagram and each furniture option (name, price, purchase link).

[0177] Specific examples

[0178] If a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[0179] 1. The user inputs the length, width, height, and style of the room.

[0180] 2. The device converts the input data into JSON format and sends it to the server. For example, it sends the following data: {"length": 5, "width": 4, "height": 3, "style": "modern"}.

[0181] 3. The server analyzes the received data and generates an optimal furniture layout, for example, placing the sofa at position X=1, Y=1.

[0182] 4. Based on the generated layout information, the server searches for furniture information from an online shopping platform through API, for example, searching for a modern-style sofa.

[0183] 5. The server combines the furniture information it has acquired with the generated layout information and sends it to the device as JSON data. For example, it generates the following data: {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}

[0184] 6. The device analyzes the received data and displays the results visually to the user, for example, using HTML and JavaScript to display a furniture layout diagram and a link to purchase.

[0185] Prompt Sentence Examples

[0186] "Based on the following information, design a program to generate a furniture layout diagram, search for suitable furniture from an online shopping platform based on this diagram, and provide its name, price, and purchase link."

[0187] Room dimensions: 5 meters long, 4 meters wide, 3 meters high

[0188] Style: Modern

[0189] Example output:

[0190] Layout diagram: Sofa placed at X=1, Y=1

[0191] Furniture information: Name: "Modern Sofa", Price: "199.99 USD", Purchase link: "http: / / example.com / sofa"

[0192] This invention allows users to easily understand the furniture layout that is suitable for their room and select and purchase that furniture at an affordable price.

[0193] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0194] Step 1:

[0195] The user uses the input form displayed on the device's web browser to input the dimensions (length, width, height) and style (modern, etc.) of the room. Specifically, the user enters numbers or text in each input field and presses the submit button. This acquires the input data.

[0196] Input: Room dimensions (length, width, height) and style information

[0197] Output: Input data (dimensions and style information)

[0198] Step 2:

[0199] The terminal converts the data entered by the user into JSON format. A JavaScript library (e.g., JSON.stringify()) is used to convert the data. After conversion, a JSON object such as {"length": 5, "width": 4, "height": 3, "style": "modern"} is generated.

[0200] Input: Data entered by the user

[0201] Output: JSON format data

[0202] Step 3:

[0203] The device sends the data converted to JSON format to the server as an HTTP POST request using an Ajax request or the fetch API.

[0204] Input: Data converted to JSON format

[0205] Output: Request sent to the server

[0206] Step 4:

[0207] The server parses the received JSON data. For example, using the Python Flask framework, the data is retrieved using the request.get_json() method. The parsed data is converted into an internal data structure (e.g., dictionary format).

[0208] Input: JSON data sent from the terminal

[0209] Output: Internal data structure (dictionary format)

[0210] Step 5:

[0211] The server then generates an optimal furniture layout based on the analyzed data, using a Python algorithm to calculate the position of each piece of furniture based on the room's dimensions and style information, such as placing a sofa in the upper left corner of the room and a table in the center.

[0212] Input: Room dimensions and style information

[0213] Output: Furniture layout information

[0214] Step 6:

[0215] The server searches for furniture using the API of an online shopping platform based on the generated furniture layout information, and sends an HTTP request to the API endpoint to obtain the name, price, and purchase link of each piece of furniture.

[0216] Input: Furniture layout information

[0217] Output: Furniture information (name, price, purchase link)

[0218] Step 7:

[0219] The server combines the generated layout information with the acquired furniture information and stores them in a single JSON format data, such as {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}.

[0220] Input: Furniture layout information and acquired furniture information

[0221] Output: Consolidated JSON format data

[0222] Step 8:

[0223] The server sends the consolidated JSON format data to the terminal, which returns the data as an HTTP response.

[0224] Input: Consolidated JSON format data

[0225] Output: The response sent to the device

[0226] Step 9:

[0227] The device parses the received JSON data and converts it into an object using a JavaScript library (e.g., JSON.parse()). The parsed data is treated as an internal data structure.

[0228] Input: JSON data sent from the server

[0229] Output: Internal data structure (object format)

[0230] Step 10:

[0231] The device displays the visual results to the user based on the analyzed data. Using HTML and JavaScript, the layout diagram of the furniture and options for each piece of furniture (name, price, purchase link) are displayed on the screen. Specifically, the layout diagram is drawn using Canvas and SVG elements, and information about each piece of furniture is displayed as text elements.

[0232] Input: Internal data structure (object format)

[0233] Output: The visual result that is displayed to the user

[0234] (Application example 1)

[0235] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0236] Conventional furniture layout suggestion systems have the problem that even if users input the dimensions and style of a room, it is difficult to check in real time how the furniture will actually look. Also, even if furniture information is obtained from an online shopping platform, users cannot check the layout before purchasing, which can lead to problems such as the result being different from expectations after purchase.

[0237] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0238] In this invention, the server includes a user input means, an acquisition means, a generation means, a search means, an acquisition means, a display means, and a means for checking the furniture arrangement status in real time on a smart device, thereby enabling a user to generate an optimal furniture layout by inputting room dimensions and style information, and to decide on a purchase while checking furniture information suggested by the online shopping platform in real time.

[0239] "User input" is an interface through which a user inputs room size and style information.

[0240] The "acquisition means" is a means for transmitting the room size and style information input by the user to the server.

[0241] The "generator" is a means for executing an algorithm that generates an optimal furniture layout based on acquired room dimension and style information.

[0242] The "search means" is a means for searching furniture information from the online shopping platform based on the generated furniture layout information.

[0243] The "display means" is a means for visually presenting the acquired furniture information and the generated furniture layout on the user terminal.

[0244] "Means for checking the furniture arrangement status in real time on a smart device" refers to a means for visually checking the furniture arrangement status in a room in real time using a device such as a smartphone or smart glasses.

[0245] The present invention is a system that generates an optimal furniture layout based on room dimensions and style information and suggests furniture that can be purchased from an online shopping platform. The system includes user input means, acquisition means, generation means, search means, and display means, and further includes a means for checking the furniture arrangement status in real time using a smart device.

[0246] System Configuration

[0247] 1. User input method

[0248] The user uses an input form provided on the terminal to input the dimensions (e.g., length, width, height) and style (e.g., modern, classic) of the room.

[0249] 2. Acquisition method

[0250] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[0251] 3. Generation means

[0252] The server runs an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[0253] 4. Search Methods

[0254] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[0255] 5. Display means

[0256] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[0257] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[0258] 6. Real-time verification method

[0259] Users can use smart devices (e.g., smartphones, smart glasses) to check the furniture layout in real time in the actual room, allowing them to visually check the furniture layout and make adjustments as necessary.

[0260] Program processing overview

[0261] Data reception and analysis

[0262] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[0263] Layout Generation

[0264] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (e.g., placing the sofa at position X=1, Y=1).

[0265] Furniture Search

[0266] The server searches for furniture using the API of the online shopping platform based on the generated layout information, and obtains the name, price, and purchase link for each piece of furniture.

[0267] Consolidating and sending results

[0268] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[0269] Displaying the results

[0270] The device receives the data sent from the server, analyzes it, and then displays the results to the user in a visual format, providing the user with a furniture layout diagram and each furniture option (with name, price, and purchase link).

[0271] Real-time confirmation

[0272] The smart device displays the generated furniture layout in the actual room in real time, allowing the user to visually check the arrangement.

[0273] Specific examples

[0274] If the user inputs the room information as "length: 5m, width: 4m, height: 3m" and the style as "modern", the system will go through the following steps:

[0275] 1. The user inputs the dimensions and style of the room.

[0276] 2. The terminal converts the input data into JSON format and sends it to the server.

[0277] 3. The server analyzes the received data and generates the optimal furniture layout.

[0278] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[0279] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[0280] 6. The device analyzes the received data and displays the results visually to the user.

[0281] 7. The user can use their smart device to view the furniture arrangement in the room in real time.

[0282] Prompt Sentence Examples

[0283] "Generate the optimal furniture layout based on the room information entered by the user, 'Dimensions: 5m x 4m x 3m, Style: Modern', and retrieve and integrate furniture information (name, price, purchase link) available for purchase from online stores."

[0284] This system allows users to easily determine the furniture layout that best suits their room and visually check the layout before making an online purchase, thereby reducing the gap between expectations and reality after purchase and providing a more satisfying shopping experience.

[0285] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0286] Step 1:

[0287] The user enters the room dimensions (e.g., length, width, height) and style information (e.g., modern, classic) using an input form provided on the device. The input form can be accessed through a web browser or a mobile application.

[0288] Input: Room dimensions and style information

[0289] Output: A data object based on the user's input

[0290] Step 2:

[0291] The device converts the input room dimensions and style information into JSON format data and sends this data to the server. The conversion is performed using a front-end script (e.g., JavaScript).

[0292] Input: User-entered room dimensions and style information

[0293] Output: JSON format data

[0294] Specific operation: Converting data format and sending an HTTP request to the server

[0295] Step 3:

[0296] The server receives the JSON data sent from the device and parses it using a server-side script (e.g., Python, Flask).

[0297] Input: JSON data sent from the terminal

[0298] Output: Parsed room dimensions and style information

[0299] Specific operation: Parsing and extracting JSON data

[0300] Step 4:

[0301] The server runs an algorithm to generate an optimal furniture layout based on the analyzed room dimensions and style information. The algorithm takes the room dimensions as input and calculates the optimal placement of each piece of furniture.

[0302] Input: Parsed room dimensions and style information

[0303] Output: Optimal furniture layout information (e.g. furniture name and placement position)

[0304] Specific operation: Execution of layout generation algorithm

[0305] Step 5:

[0306] The server searches for furniture information using the API of the online shopping platform based on the generated furniture layout information, sending an API request to obtain the name, price, purchase link, etc. of the relevant furniture.

[0307] Input: Optimal furniture layout information

[0308] Output: Retrieved furniture information

[0309] Specific behavior: Generating API requests and parsing responses

[0310] Step 6:

[0311] The server integrates the generated furniture layout information with the acquired furniture information and sends it back to the terminal as JSON format data. The integration process is performed by a server-side script (e.g., Python).

[0312] Input: Optimal furniture layout information and retrieved furniture information

[0313] Output: Consolidated JSON data

[0314] Specific behavior: Data merging and format conversion

[0315] Step 7:

[0316] The device receives the aggregated data sent from the server and displays the results to the user in a visual format, including a furniture layout diagram of the room and each furniture option with its name, price, and a purchase link.

[0317] Input: Aggregated data sent from the server

[0318] Output: Visual display results

[0319] Specific behavior: Analyzing data and displaying it in the interface

[0320] Step 8:

[0321] Users can use smart devices (e.g., smartphones, smart glasses) to check the furniture arrangement in a room in real time. This function is realized using Augmented Reality (AR) technology.

[0322] Input: Room dimensions, style information, and generated furniture layout

[0323] Output: Real-time display of furniture layout

[0324] Specific operation: Displaying furniture in real space using AR technology

[0325] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0326] The present invention combines a system that generates an optimal furniture layout based on the dimensions and style information of a user's room and suggests furniture that can be purchased at an affordable price from an online shopping platform with an emotion engine that recognizes the user's emotions. Each component of the system and its operation will be described in detail below.

[0327] System Configuration

[0328] 1. User input method

[0329] The user uses an input form on the terminal to input the room dimensions (length, width, height) and style (modern, classic, etc.).

[0330] 2. Acquisition method

[0331] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[0332] 3. Generation means

[0333] The server executes an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[0334] 4. Search Methods

[0335] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[0336] 5. Display means

[0337] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[0338] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[0339] 6. Emotion Engine

[0340] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[0341] The server adjusts the furniture layout to be generated and the type of furniture to be suggested based on the user's emotions identified by the emotion engine.

[0342] Program processing overview

[0343] User Input

[0344] The user enters the room information (dimensions, style) into the terminal using the input form. The entered data is converted into JSON format and sent to the server.

[0345] Data reception and analysis

[0346] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[0347] Layout Generation

[0348] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (for example, placing the sofa at position X=1, Y=1).

[0349] Emotion Recognition and Analysis

[0350] The device analyzes the user's facial expressions and voice using an emotion engine to identify the user's emotions.

[0351] Furniture Search

[0352] The server searches for furniture using the API of the online shopping platform based on the generated layout information, obtains the name, price, and purchase link for each piece of furniture, and adjusts the suggestions based on the user's sentiment.

[0353] Consolidating and sending results

[0354] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[0355] Displaying the results

[0356] The device receives the JSON data sent from the server, analyzes it, and displays it to the user in a visually easy-to-understand format, providing the user with a furniture layout diagram and options for each piece of furniture (with name, price, and purchase link).

[0357] Specific examples

[0358] For example, if a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[0359] 1. The user inputs the length, width, height and style of the room.

[0360] 2. The terminal converts the input data into JSON format and sends it to the server.

[0361] 3. The server analyzes the received data and generates the optimal furniture layout.

[0362] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[0363] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[0364] 6. The terminal analyzes the received data and displays it to the user in a visually easy-to-understand format.

[0365] 7. The device analyzes the user's facial expressions and voice to recognize their emotions.

[0366] 8. The server adjusts the suggestions based on the perceived sentiment.

[0367] 9. The user checks the proposed furniture layout and purchase link on the device and purchases the furniture if necessary.

[0368] The system allows users to find optimal furniture placement and purchasing options based on their emotional state.

[0369] The processing flow will be explained below.

[0370] Step 1:

[0371] The user inputs the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form on the terminal.

[0372] Step 2:

[0373] The terminal converts the user input data into JSON format.

[0374] example:

[0375] json

[0376] {

[0377] "length": 5,

[0378] "width": 4,

[0379] "height": 3,

[0380] "style": "modern"

[0381] }

[0382] Step 3:

[0383] The terminal sends the data converted into JSON format to the server via an HTTP request.

[0384] Step 4:

[0385] The server receives and analyzes the JSON data sent from the device.

[0386] Step 5:

[0387] The server runs an algorithm to generate the optimal furniture layout based on the received data, calculating the placement of each piece of furniture based on the room dimensions and style information.

[0388] example:

[0389] json

[0390] {

[0391] "sofa": {"x": 1, "y": 1},

[0392] "table": {"x": 2, "y": 2},

[0393] "bed": {"x": 3, "y": 3}

[0394] }

[0395] Step 6:

[0396] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[0397] example:

[0398] Emotion engine result: "happy"

[0399] Step 7:

[0400] The server receives emotion data from the emotion engine and adjusts the furniture layout to suit the user's needs. For example, if the user feels sad, the server will suggest brightly colored furniture.

[0401] Step 8:

[0402] The server sends furniture search requests to the APIs of multiple online shopping platforms based on the generated layout information. It creates search queries that include the names and characteristics of the furniture.

[0403] example:

[0404] Example request:

[0405] json

[0406] {

[0407] "query": "modern sofa",

[0408] "max_price": 30000

[0409] }

[0410] Step 9:

[0411] The server receives and analyzes the API responses from each platform.

[0412] Step 10:

[0413] The server formats the acquired furniture information and integrates it with the generated furniture layout information.

[0414] example:

[0415] json

[0416] {

[0417] "layout": {

[0418] "sofa": {"x": 1, "y": 1},

[0419] "table": {"x": 2, "y": 2},

[0420] "bed": {"x": 3, "y": 3}

[0421] },

[0422] "furniture": [

[0423] {"name": "Modern sofa", "price": 20000, "url": "https: / / example.com / sofa"},

[0424] {"name": "Glass Table", "price": 15000, "url": "https: / / example.com / table"},

[0425] {"name": "Comfortable Bed", "price": 30000, "url": "https: / / example.com / bed"}

[0426] ]

[0427] }

[0428] Step 11:

[0429] The server sends the formatted data in JSON format to the terminal.

[0430] Step 12:

[0431] The device parses the received JSON data and displays it to the user in a visually easy-to-understand format, providing the user with a furniture layout diagram and options for each piece of furniture (with name, price, and purchase link).

[0432] Step 13:

[0433] The user checks the proposed furniture layout and purchase link on the terminal and purchases the furniture as necessary.

[0434] Example 2

[0435] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0436] Conventional furniture layout suggestion systems simply provide optimal layouts based on the dimensions and style of a room, but lack the ability to adjust the suggestions based on the user's emotional state. As a result, users often feel dissatisfied with the proposed furniture layout. To solve this problem, a system is needed that can suggest furniture and layouts that reflect the user's emotional state.

[0437] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user input means, an acquisition means for acquiring room dimension and style information from the input means, a generation means for generating an optimal furniture layout based on the room dimension and style information acquired by the acquisition means, a search means for searching for furniture information from an online shopping platform based on the layout information generated by the generation means, an acquisition means for acquiring the furniture information acquired by the search means, a display means for displaying the furniture information and furniture layout acquired by the acquisition means on the user terminal, an emotion recognition means for the terminal to recognize the user's emotion in real time, and an adjustment means for adjusting the generated furniture layout or the proposed furniture based on the emotion recognized by the emotion recognition means. This makes it possible to propose an optimal furniture layout and furniture that reflects the user's emotional state.

[0438] A "user input means" is a device that provides an interface for a user to input room dimensions and style information.

[0439] The "acquisition means" is a method or device for collecting data obtained from the user's input means and proceeding to the next step.

[0440] The "generation means" refers to an algorithm or program that calculates and generates an optimal furniture layout based on the data obtained by the acquisition means.

[0441] The "search means" refers to a method or device for searching for furniture information on the online shopping platform based on the layout information generated by the generation means.

[0442] The "display means" is a method or device for visually displaying the furniture information collected by the acquisition means and the furniture layout information generated on the user terminal.

[0443] An "emotion recognition means" is a method or equipment for capturing a user's facial expressions and voice in real time and analyzing them to identify the user's emotions.

[0444] The "adjustment means" is a method or apparatus that adjusts the generated furniture layout or suggested furniture based on the user's emotions identified by the emotion recognition means.

[0445] The present invention combines a system that generates an optimal furniture layout based on the user's room dimensions and style information and suggests furniture that can be purchased at an affordable price from an online shopping platform with an emotion engine that recognizes the user's emotions.

[0446] System Configuration

[0447] 1. User input method

[0448] The user uses an input form on the terminal to input the room dimensions (length, width, height) and style (e.g., modern, classic).

[0449] 2. Acquisition method

[0450] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[0451] 3. Generation means

[0452] The server executes an algorithm for generating an optimal furniture layout based on the room dimensions and style information acquired by the acquisition means. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[0453] 4. Search Methods

[0454] The server searches for furniture on the online shopping platform based on the generated furniture layout information and obtains matching furniture information using an API.

[0455] 5. Display means

[0456] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[0457] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[0458] 6. Emotion recognition means

[0459] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[0460] 7. Adjustment means

[0461] The server adjusts the furniture layout to be generated and the type of furniture to be proposed based on the user's emotion identified by the emotion recognition means.

[0462] System Operation Overview

[0463] User Input

[0464] The user inputs the dimensions and style of the room into a form on the browser. For example, the user inputs "room length: 5 meters, width: 4 meters, height: 3 meters, style: modern."

[0465] Data reception and analysis

[0466] The terminal converts the data entered by the user into JSON format and sends it to the server, which receives and analyzes the data.

[0467] Layout Generation

[0468] The server generates the optimal furniture layout based on the analyzed data. For example, the server calculates a specific layout such as "placing the sofa longitudinally and placing the table in the center."

[0469] Emotion Recognition and Analysis

[0470] The device uses a camera and microphone to capture the user's facial expressions and voice in real time, and analyzes them with an emotion engine. As a result, emotions such as "joy" are identified.

[0471] Furniture Search

[0472] Based on the optimal furniture layout, the server retrieves matching furniture information from online shopping platforms, such as a modern sofa or a wooden table, via API, and obtains the name, price, and purchase link.

[0473] Consolidating and sending results

[0474] The server combines the generated layout information and the acquired furniture information and sends it to the device as new JSON data. The device then analyzes the received data and visually displays a furniture layout diagram and furniture options.

[0475] Specific examples

[0476] For example, if a user enters the dimensions of a room as "5m x 4m x 3m" and the style as "Modern," the system will perform the following steps:

[0477] 1. The user inputs the dimensions and style of the room.

[0478] 2. The terminal converts the input data into JSON format and sends it to the server.

[0479] 3. The server receives and analyzes the data.

[0480] 4. The server generates the optimal furniture layout.

[0481] 5. The device recognizes the user's emotions and sends the analysis results to the server.

[0482] 6. Based on the generated layout information, the server searches for furniture information from the online shopping platform via API.

[0483] 7. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal.

[0484] 8. The device analyzes the received data and displays it to the user in a visually understandable format.

[0485] Examples of prompt statements

[0486] Examples of prompts to be input to a generative AI model include:

[0487] "Suggest the best furniture layout based on the room dimensions and style, and adjust it according to the user's emotions. Room information is: Length: 5 meters, Width: 4 meters, Height: 3 meters, Style: Modern. User's emotions: Joy."

[0488] keyword

[0489] Generative AI model, prompt sentence, furniture layout, emotion engine, online shopping platform, room dimensions, room style, furniture suggestions, user input

[0490] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0491] Step 1:

[0492] The user enters the dimensions (length, width, height) and style (e.g., modern, classic) of the room into an input form on the device. The input data is formatted in JSON format.

[0493] Specific behavior: The user enters the following into a form on the browser: "Room length: 5 meters, width: 4 meters, height: 3 meters, style: modern." The device converts this data into JSON format ({ "length": 5, "width": 4, "height": 3, "style": "modern"}).

[0494] Input: User input of dimensions and styles

[0495] Output: Input information in JSON data format

[0496] Step 2:

[0497] The device sends the JSON data generated in step 1 to the server.

[0498] Specific behavior: The device sends JSON data to the server using an HTTP POST request.

[0499] Input: JSON data generated in step 1

[0500] Output: Send data to the server

[0501] Step 3:

[0502] The server receives and parses the JSON data.

[0503] What it does: The server parses the received JSON data and extracts the room's length, width, height, and style information.

[0504] Input: JSON data sent in step 2

[0505] Output: Parsed room information (length, width, height, style)

[0506] Step 4:

[0507] The server generates the optimal furniture layout based on the analyzed data.

[0508] How it works: The server uses an algorithm to calculate the placement of each piece of furniture and generate a layout, for example placing a sofa along the length of the room and a table in the center.

[0509] Input: Room information parsed in step 3

[0510] Output: Generated furniture layout information

[0511] Step 5:

[0512] The device captures the user's facial expressions and voice in real time and sends them to the emotion engine.

[0513] Specific operation: The device uses the camera and microphone to capture the user's facial expressions and voice, which are then analyzed by the emotion engine.

[0514] Input: Real-time captured facial expression and voice data

[0515] Output: Identified emotion information (e.g., joy, surprise)

[0516] Step 6:

[0517] The server adjusts the furniture layout and suggested furniture based on the analysis results from the emotion recognition means.

[0518] Specific behavior: The server adjusts the furniture arrangement and type based on the identified emotion (e.g., "joy"), for example, preferentially suggesting brightly colored furniture.

[0519] Input: Emotion information identified in step 5

[0520] Output: Adjusted furniture layout and suggested furniture information

[0521] Step 7:

[0522] The server uses the API of the online shopping platform to search for furniture information based on the adjusted layout information.

[0523] Specific operation: The server uses the API to obtain the furniture name, price, purchase link, etc. For example, search for "modern sofa" or "wooden table."

[0524] Input: Furniture layout information adjusted in step 6

[0525] Output: Retrieved furniture information (name, price, purchase link)

[0526] Step 8:

[0527] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal in JSON format.

[0528] Specific operation: The server integrates the layout information and furniture information, generates new JSON data, and sends it to the terminal.

[0529] Input: Furniture information obtained in step 7 and furniture layout information adjusted in step 6

[0530] Output: Consolidated JSON data

[0531] Step 9:

[0532] The device parses the received JSON data and displays it to the user in a visually easy-to-understand format.

[0533] Specific operation: The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links). The user can check the furniture layout and furniture information on the screen.

[0534] Input: JSON data sent in step 8

[0535] Output: Visually displayed furniture layout and furniture information

[0536] keyword

[0537] Generative AI model, prompt sentence

[0538] (Application example 2)

[0539] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0540] Conventional furniture layout generation systems simply propose optimal furniture layouts without considering the user's emotional state. This prevents flexible proposals based on the user's emotions and preferences, and fails to increase user satisfaction. Furthermore, there is a lack of systems that allow users to easily purchase the proposed furniture through online shopping. This makes the process of users finding and purchasing the furniture that best suits them cumbersome.

[0541] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for generating an optimal furniture layout based on the dimensions and style information of the user's room, means for searching for furniture information from an online shopping platform, means for displaying the acquired furniture information and furniture layout on the user terminal, means for capturing facial expressions and voice and identifying emotions, and means for adjusting the furniture layout and suggested furniture information based on the identified emotional information. This enables flexible furniture layout and suggestions based on the user's emotional state, providing a smooth purchasing process through online shopping.

[0542] "Input means" refers to a device or interface through which a user inputs room size and style information.

[0543] The "acquisition means" is a device or system having a function for acquiring and analyzing the room dimension and style information sent from the input means.

[0544] The "generator" is an algorithm or device that generates an optimal furniture layout based on the room dimensions and style information acquired by the acquirer.

[0545] The "search means" is a device or system having a function for searching furniture information from an online shopping platform based on the layout information generated by the generation means.

[0546] The "display means" refers to a device or software for displaying the acquired furniture information and furniture layout on a user terminal.

[0547] An "emotion recognition means" is a technology or device that captures a user's facial expressions and voice and identifies emotions from them.

[0548] The "adjustment means" is a device or system that has the function of correcting or optimizing the generated furniture layout or the proposed furniture information based on the emotion information identified by the emotion recognition means.

[0549] An "online shopping platform" is a website or application that allows users to search for, view, and purchase products over the Internet.

[0550] "Furniture layout" refers to the position information and layout diagram of furniture arranged based on the dimensions and style information of the room.

[0551] "Furniture information" refers to detailed information such as the name, price, size, and purchase link of the furniture obtained from the online shopping platform.

[0552] A "terminal" is an electronic device used by a user to enter data or display results, and includes smartphones, tablets, and personal computers.

[0553] The present invention is a system that generates an optimal furniture layout based on the dimensions and style information of a user's room, and suggests suitable furniture from an online shopping platform. It also has the ability to identify the user's emotional state and adjust the furniture layout and suggestions accordingly.

[0554] System configuration:

[0555] Input methods:

[0556] Users use devices such as smartphones, tablets, and computers to enter the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form.

[0557] Acquisition method:

[0558] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[0559] Generation means:

[0560] The server runs an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information, which includes calculating the placement of furniture.

[0561] Search by:

[0562] The server searches for furniture information from the online shopping platform based on the generated furniture layout information and obtains matching furniture information using an API.

[0563] Display means:

[0564] The server combines the acquired furniture information with the generated furniture layout information and sends it to the device as JSON format data. The device then analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[0565] Emotion recognition means:

[0566] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine, which identifies the user's emotions (e.g., joy, surprise, sadness, etc.).

[0567] Adjustment means:

[0568] The server adjusts the furniture layout to be generated and the type of furniture to be suggested based on the user's emotions identified by the emotion engine.

[0569] Hardware and software used:

[0570] Hardware: Smartphone, tablet, computer camera and microphone

[0571] Software: Emotion recognition engine (ai_emotion_recognition), furniture layout generation algorithm (furniture_layout_generator), online shopping search API (online_shopping_api)

[0572] Data processing and calculation details:

[0573] 1. The server receives and analyzes the room dimensions and style information sent from the terminal.

[0574] 2. The server runs an algorithm that generates the optimal furniture layout based on the analysis results.

[0575] 3. The server uses an API to obtain compatible furniture information from the online shopping platform based on the generated furniture layout information.

[0576] 4. The device captures the user's facial expression and voice data and uses an emotion recognition engine to identify emotions.

[0577] 5. The server adjusts the generated furniture layout and suggestions based on the analysis results of the emotion recognition engine.

[0578] Examples:

[0579] For example, if a user enters the following room information:

[0580] "My room measures 5 meters long, 4 meters wide, and 3 meters high. I want to fill it with modern-style furniture."

[0581] The system goes through the following steps:

[0582] 1. The user inputs the room dimensions and style.

[0583] 2. The terminal converts the input data into JSON format and sends it to the server.

[0584] 3. The server analyzes the received data and generates the optimal furniture layout.

[0585] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[0586] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[0587] 6. The device analyzes the received data and displays it to the user in a visually understandable format.

[0588] 7. The device analyzes the user's facial expressions and voice to recognize their emotions.

[0589] 8. The server adjusts the suggestions based on the perceived sentiment.

[0590] This allows users to find the best furniture arrangement and purchasing options based on their emotional state.

[0591] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0592] Step 1:

[0593] The user enters the dimensions (length, width, height) and style (modern, classic, etc.) of a room into an input form on the device. The input data is converted into JSON format. The input is information about the physical characteristics and design style of the room.

[0594] Step 2:

[0595] The device sends the user input data in JSON format to the server, which parses the data and extracts the room dimensions and style information. This step checks the consistency and completeness of the input data.

[0596] Step 3:

[0597] The server runs an algorithm to generate an optimal furniture layout based on the room dimensions and style information. The algorithm calculates the placement position of each piece of furniture and generates a furniture layout plan that matches the room dimensions. The output is layout information showing the placement positions of the furniture.

[0598] Step 4:

[0599] The server uses the API to search for furniture information from an online shopping platform based on the generated furniture layout information. The input is the generated layout information, and the output is the searched multiple furniture options (name, price, purchase link, etc.).

[0600] Step 5:

[0601] The server combines the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data. This process determines the furniture configuration to be proposed to the user.

[0602] Step 6:

[0603] The device receives and parses the JSON data sent from the server. After parsing, it displays a furniture layout diagram and furniture options (with names, prices, and purchase links) in a visually easy-to-understand format to the user. At this point, the user can review the proposed furniture.

[0604] Step 7:

[0605] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The input is the user's facial expressions and voice data, and the output is analyzed emotional information (e.g., joy, surprise, sadness, etc.).

[0606] Step 8:

[0607] The server adjusts the generated furniture layout and furniture suggestions based on the emotional information identified by the emotion engine. This adjustment determines the suggestions that are optimized for the user's emotional state. The final output is a furniture layout and furniture options that are adjusted based on the emotional information.

[0608] This clarifies the specific processing and operations of each step, making it possible to propose optimal furniture that takes into account the user's emotional state.

[0609] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0610] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0611] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0612] [Second embodiment]

[0613] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0614] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0615] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0616] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0617] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0618] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0619] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0620] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0621] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0622] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0623] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0624] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0625] The present invention provides a system that generates an optimal furniture layout based on the dimensions and style information of a user's room and suggests furniture that can be purchased at an affordable price from an online shopping platform. The system is mainly configured as follows.

[0626] System Configuration

[0627] 1. User input method

[0628] The user uses an input form provided on the terminal to input the dimensions (for example, length, width, height) and style (modern, classic, etc.) of the room.

[0629] 2. Acquisition method

[0630] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[0631] 3. Generation means

[0632] The server executes an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[0633] 4. Search Methods

[0634] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[0635] 5. Display means

[0636] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[0637] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[0638] Program processing overview

[0639] User Input

[0640] The user enters the room information (dimensions, style) into the terminal using the input form. The entered data is converted into JSON format and sent to the server.

[0641] Data reception and analysis

[0642] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[0643] Layout Generation

[0644] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (for example, placing the sofa at position X=1, Y=1).

[0645] Furniture Search

[0646] The server searches for furniture using the API of the online shopping platform based on the generated layout information, and obtains the name, price, and purchase link for each piece of furniture.

[0647] Consolidating and sending results

[0648] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[0649] Displaying the results

[0650] The device receives the data sent from the server, analyzes it, and then displays the results to the user in a visual format, providing the user with a furniture layout diagram and each furniture option (with name, price, and purchase link).

[0651] Specific examples

[0652] If a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[0653] 1. The user inputs the length, width, height and style of the room.

[0654] 2. The terminal converts the input data into JSON format and sends it to the server.

[0655] 3. The server analyzes the received data and generates the optimal furniture layout.

[0656] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[0657] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[0658] 6. The device analyzes the received data and displays the results visually to the user.

[0659] The system allows users to easily find the furniture layout that best suits their room and purchase that furniture at an affordable price.

[0660] The processing flow will be explained below.

[0661] Step 1:

[0662] The user inputs the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form on the terminal.

[0663] Step 2:

[0664] The terminal converts the user input data into JSON format.

[0665] example:

[0666] json

[0667] {

[0668] "length": 5,

[0669] "width": 4,

[0670] "height": 3,

[0671] "style": "modern"

[0672] }

[0673] Step 3:

[0674] The terminal sends the data converted into JSON format to the server via an HTTP request.

[0675] Step 4:

[0676] The server receives and analyzes the JSON data sent from the device.

[0677] Step 5:

[0678] The server runs an algorithm to generate the optimal furniture layout based on the received data, calculating the placement of each piece of furniture based on the room dimensions and style information.

[0679] example:

[0680] json

[0681] {

[0682] "sofa": {"x": 1, "y": 1},

[0683] "table": {"x": 2, "y": 2},

[0684] "bed": {"x": 3, "y": 3}

[0685] }

[0686] Step 6:

[0687] The server sends furniture search requests to the APIs of multiple online shopping platforms based on the generated layout information. It creates search queries that include the names and characteristics of the furniture.

[0688] example:

[0689] Example request:

[0690] json

[0691] {

[0692] "query": "modern sofa",

[0693] "max_price": 30000

[0694] }

[0695] Step 7:

[0696] The server receives and analyzes the API responses from each platform.

[0697] Step 8:

[0698] The server formats the acquired furniture information and integrates it with the generated furniture layout information.

[0699] example:

[0700] json

[0701] {

[0702] "layout": {

[0703] "sofa": {"x": 1, "y": 1},

[0704] "table": {"x": 2, "y": 2},

[0705] "bed": {"x": 3, "y": 3}

[0706] },

[0707] "furniture": [

[0708] {"name": "Modern sofa", "price": 20000, "url": "https: / / example.com / sofa"},

[0709] {"name": "Glass Table", "price": 15000, "url": "https: / / example.com / table"},

[0710] {"name": "Comfortable Bed", "price": 30000, "url": "https: / / example.com / bed"}

[0711] ]

[0712] }

[0713] Step 9:

[0714] The server sends the formatted data in JSON format to the terminal.

[0715] Step 10:

[0716] The terminal analyzes the received JSON data and displays it to the user in a visually easy-to-understand format.

[0717] Step 11:

[0718] The user checks the proposed furniture layout and purchase link on the terminal and purchases the furniture as necessary.

[0719] Example 1

[0720] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0721] Conventionally, it is very time-consuming and requires specialized knowledge for users to manually design the optimal furniture layout that matches the dimensions and style of the room and then search for the appropriate furniture. Therefore, there is a need for a system that can efficiently generate the optimal layout and allow users to easily select and purchase the appropriate furniture.

[0722] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0723] In this invention, the server includes a user input means, an acquisition means for acquiring room size and style information from the input means, a means for converting the acquired room size and style information into JSON format and transmitting the converted information to the server, a generation means for the server to generate an optimal furniture layout based on the acquired room size and style information, a search means for searching for furniture information from an API of an online shopping platform based on the layout information generated by the generation means, a acquisition means for acquiring the furniture information acquired by the search means, a means for integrating the acquired furniture information and the generated furniture layout and transmitting the combined data to a terminal in JSON format, and a display means for analyzing the data received by the terminal and displaying the combined data to the user in a visual format. This allows users to efficiently generate optimal furniture layouts and easily select and purchase appropriate furniture.

[0724] "User input means" is an interface provided on the terminal for the user to input room size and style information.

[0725] "Acquisition means" refers to the function that acquires room dimensions and style information from the user's input means and converts it into JSON format.

[0726] "JSON format" is a data structure in JavaScript Object Notation format, which is a method of expressing data in text format.

[0727] A "server" is a computer device that receives, analyzes, and processes data sent from an input means.

[0728] "Generator" refers to the functionality of the server that runs an algorithm to generate an optimal furniture layout based on room dimensions and style information.

[0729] The "search means" is a function for searching furniture information using the API of the online shopping platform based on the generated layout information.

[0730] An "online shopping platform" is a web service that provides product information and sells products via the Internet.

[0731] "API" stands for Application Programming Interface, and is an interface that allows software to provide and call functions to other software.

[0732] The "acquisition means" is a function that receives and processes furniture information acquired by the search means (used for a purpose different from the above-mentioned "acquisition means").

[0733] The "integration means" is a function that combines the generated furniture layout information and the acquired furniture information into a single data format (JSON format).

[0734] "Transmission means" refers to a function for transmitting the integrated data to the terminal.

[0735] The "analysis means" is a function that allows the terminal to process the JSON data received from the server and understand its structure.

[0736] "Display means" is a function of the terminal for visually presenting analyzed data to the user.

[0737] The present invention provides a system for generating an optimal furniture layout by a user inputting room dimensions and style information, and for suggesting affordable furniture from an online shopping platform based on the optimal furniture layout. The system includes the following means and processing steps:

[0738] System configuration

[0739] The system mainly consists of user input means, acquisition means, generation means, search means, integration means, transmission means, and display means. Specifically, the following hardware and software are used:

[0740] Hardware

[0741] User terminal: PC, tablet, smartphone, etc. Provides input and display means.

[0742] Server: A remotely located high-performance computer, cloud service, etc. that receives, analyzes, generates, searches, integrates, and transmits data.

[0743] software

[0744] Input Form: An HTML form that runs in a web browser, allowing users to enter room dimensions and style information.

[0745] JSON conversion library: A data format conversion library using JavaScript or other programming languages.

[0746] Server application: Implemented using Python's Flask framework, etc. Performs data analysis, layout generation, and API communication.

[0747] API: An API provided by an online shopping platform (e.g., Amazon) that acts as a search engine.

[0748] Presentation library: Visual presentation using HTML, CSS, and JavaScript.

[0749] Data processing and calculation

[0750] User Input

[0751] The user uses an input form on the terminal to input the dimensions of the room (e.g., 5 meters x 4 meters x 3 meters) and the style (e.g., modern), and the terminal acquires the input data.

[0752] Sending and Receiving Data

[0753] The device converts the acquired data into JSON format and sends it to the server. The server parses the received JSON data. For example, it receives data in the format {"length": 5, "width": 4, "height": 3, "style": "modern"}.

[0754] Generate layout

[0755] The server generates an optimal furniture layout based on the analyzed data. Specifically, a generation algorithm implemented in Python calculates the placement of each piece of furniture based on the room dimensions. For example, the sofa might be placed in the upper left corner of the room, and the table in the center.

[0756] Furniture Search

[0757] Based on the generated layout information, the server searches for furniture using the API of the online shopping platform, sending an HTTP request to the API endpoint to obtain the name, price, and purchase link of the appropriate furniture.

[0758] Consolidating and sending results

[0759] The server combines the acquired furniture information with the generated furniture layout information and sends it back to the device as JSON format data. For example, it generates data like this: {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}

[0760] Displaying the results

[0761] The device parses the JSON data received from the server and presents it visually to the user, for example, using HTML and JavaScript to display a furniture layout diagram and each furniture option (name, price, purchase link).

[0762] Specific examples

[0763] If a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[0764] 1. The user inputs the length, width, height, and style of the room.

[0765] 2. The device converts the input data into JSON format and sends it to the server. For example, it sends the following data: {"length": 5, "width": 4, "height": 3, "style": "modern"}.

[0766] 3. The server analyzes the received data and generates an optimal furniture layout, for example, placing the sofa at position X=1, Y=1.

[0767] 4. Based on the generated layout information, the server searches for furniture information from an online shopping platform through API, for example, searching for a modern-style sofa.

[0768] 5. The server combines the furniture information it has acquired with the generated layout information and sends it to the device as JSON data. For example, it generates the following data: {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}

[0769] 6. The device analyzes the received data and displays the results visually to the user, for example, using HTML and JavaScript to display a furniture layout diagram and a link to purchase.

[0770] Prompt Sentence Examples

[0771] "Based on the following information, design a program to generate a furniture layout diagram, search for suitable furniture from an online shopping platform based on this diagram, and provide its name, price, and purchase link."

[0772] Room dimensions: 5 meters long, 4 meters wide, 3 meters high

[0773] Style: Modern

[0774] Example output:

[0775] Layout diagram: Sofa placed at X=1, Y=1

[0776] Furniture information: Name: "Modern Sofa", Price: "199.99 USD", Purchase link: "http: / / example.com / sofa"

[0777] This invention allows users to easily understand the furniture layout that is suitable for their room and select and purchase that furniture at an affordable price.

[0778] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0779] Step 1:

[0780] The user uses the input form displayed on the device's web browser to input the dimensions (length, width, height) and style (modern, etc.) of the room. Specifically, the user enters numbers or text in each input field and presses the submit button. This acquires the input data.

[0781] Input: Room dimensions (length, width, height) and style information

[0782] Output: Input data (dimensions and style information)

[0783] Step 2:

[0784] The terminal converts the data entered by the user into JSON format. A JavaScript library (e.g., JSON.stringify()) is used to convert the data. After conversion, a JSON object such as {"length": 5, "width": 4, "height": 3, "style": "modern"} is generated.

[0785] Input: Data entered by the user

[0786] Output: JSON format data

[0787] Step 3:

[0788] The device sends the data converted to JSON format to the server as an HTTP POST request using an Ajax request or the fetch API.

[0789] Input: Data converted to JSON format

[0790] Output: Request sent to the server

[0791] Step 4:

[0792] The server parses the received JSON data. For example, using the Python Flask framework, the data is retrieved using the request.get_json() method. The parsed data is converted into an internal data structure (e.g., dictionary format).

[0793] Input: JSON data sent from the terminal

[0794] Output: Internal data structure (dictionary format)

[0795] Step 5:

[0796] The server then generates an optimal furniture layout based on the analyzed data, using a Python algorithm to calculate the position of each piece of furniture based on the room's dimensions and style information, such as placing a sofa in the upper left corner of the room and a table in the center.

[0797] Input: Room dimensions and style information

[0798] Output: Furniture layout information

[0799] Step 6:

[0800] The server searches for furniture using the API of an online shopping platform based on the generated furniture layout information, and sends an HTTP request to the API endpoint to obtain the name, price, and purchase link of each piece of furniture.

[0801] Input: Furniture layout information

[0802] Output: Furniture information (name, price, purchase link)

[0803] Step 7:

[0804] The server combines the generated layout information with the acquired furniture information and stores them in a single JSON format data, such as {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}.

[0805] Input: Furniture layout information and acquired furniture information

[0806] Output: Consolidated JSON format data

[0807] Step 8:

[0808] The server sends the consolidated JSON format data to the terminal, which returns the data as an HTTP response.

[0809] Input: Consolidated JSON format data

[0810] Output: The response sent to the device

[0811] Step 9:

[0812] The device parses the received JSON data and converts it into an object using a JavaScript library (e.g., JSON.parse()). The parsed data is treated as an internal data structure.

[0813] Input: JSON data sent from the server

[0814] Output: Internal data structure (object format)

[0815] Step 10:

[0816] The device displays the visual results to the user based on the analyzed data. Using HTML and JavaScript, the layout diagram of the furniture and options for each piece of furniture (name, price, purchase link) are displayed on the screen. Specifically, the layout diagram is drawn using Canvas and SVG elements, and information about each piece of furniture is displayed as text elements.

[0817] Input: Internal data structure (object format)

[0818] Output: The visual result that is displayed to the user

[0819] (Application example 1)

[0820] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0821] Conventional furniture layout suggestion systems have the problem that even if users input the dimensions and style of a room, it is difficult to check in real time how the furniture will actually look. Also, even if furniture information is obtained from an online shopping platform, users cannot check the layout before purchasing, which can lead to problems such as the result being different from expectations after purchase.

[0822] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0823] In this invention, the server includes a user input means, an acquisition means, a generation means, a search means, an acquisition means, a display means, and a means for checking the furniture arrangement status in real time on a smart device, thereby enabling a user to generate an optimal furniture layout by inputting room dimensions and style information, and to decide on a purchase while checking furniture information suggested by the online shopping platform in real time.

[0824] "User input" is an interface through which a user inputs room size and style information.

[0825] The "acquisition means" is a means for transmitting the room size and style information input by the user to the server.

[0826] The "generator" is a means for executing an algorithm that generates an optimal furniture layout based on acquired room dimension and style information.

[0827] The "search means" is a means for searching furniture information from the online shopping platform based on the generated furniture layout information.

[0828] The "display means" is a means for visually presenting the acquired furniture information and the generated furniture layout on the user terminal.

[0829] "Means for checking the furniture arrangement status in real time on a smart device" refers to a means for visually checking the furniture arrangement status in a room in real time using a device such as a smartphone or smart glasses.

[0830] The present invention is a system that generates an optimal furniture layout based on room dimensions and style information and suggests furniture that can be purchased from an online shopping platform. The system includes user input means, acquisition means, generation means, search means, and display means, and further includes a means for checking the furniture arrangement status in real time using a smart device.

[0831] System Configuration

[0832] 1. User input method

[0833] The user uses an input form provided on the terminal to input the dimensions (e.g., length, width, height) and style (e.g., modern, classic) of the room.

[0834] 2. Acquisition method

[0835] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[0836] 3. Generation means

[0837] The server runs an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[0838] 4. Search Methods

[0839] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[0840] 5. Display means

[0841] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[0842] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[0843] 6. Real-time verification method

[0844] Users can use smart devices (e.g., smartphones, smart glasses) to check the furniture layout in real time in the actual room, allowing them to visually check the furniture layout and make adjustments as necessary.

[0845] Program processing overview

[0846] Data reception and analysis

[0847] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[0848] Layout Generation

[0849] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (e.g., placing the sofa at position X=1, Y=1).

[0850] Furniture Search

[0851] The server searches for furniture using the API of the online shopping platform based on the generated layout information, and obtains the name, price, and purchase link for each piece of furniture.

[0852] Consolidating and sending results

[0853] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[0854] Displaying the results

[0855] The device receives the data sent from the server, analyzes it, and then displays the results to the user in a visual format, providing the user with a furniture layout diagram and each furniture option (with name, price, and purchase link).

[0856] Real-time confirmation

[0857] The smart device displays the generated furniture layout in the actual room in real time, allowing the user to visually check the arrangement.

[0858] Specific examples

[0859] If the user inputs the room information as "length: 5m, width: 4m, height: 3m" and the style as "modern", the system will go through the following steps:

[0860] 1. The user inputs the dimensions and style of the room.

[0861] 2. The terminal converts the input data into JSON format and sends it to the server.

[0862] 3. The server analyzes the received data and generates the optimal furniture layout.

[0863] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[0864] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[0865] 6. The device analyzes the received data and displays the results visually to the user.

[0866] 7. The user can use their smart device to view the furniture arrangement in the room in real time.

[0867] Prompt Sentence Examples

[0868] "Generate the optimal furniture layout based on the room information entered by the user, 'Dimensions: 5m x 4m x 3m, Style: Modern', and retrieve and integrate furniture information (name, price, purchase link) available for purchase from online stores."

[0869] This system allows users to easily determine the furniture layout that best suits their room and visually check the layout before making an online purchase, thereby reducing the gap between expectations and reality after purchase and providing a more satisfying shopping experience.

[0870] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0871] Step 1:

[0872] The user enters the room dimensions (e.g., length, width, height) and style information (e.g., modern, classic) using an input form provided on the device. The input form can be accessed through a web browser or a mobile application.

[0873] Input: Room dimensions and style information

[0874] Output: A data object based on the user's input

[0875] Step 2:

[0876] The device converts the input room dimensions and style information into JSON format data and sends this data to the server. The conversion is performed using a front-end script (e.g., JavaScript).

[0877] Input: User-entered room dimensions and style information

[0878] Output: JSON format data

[0879] Specific operation: Converting data format and sending an HTTP request to the server

[0880] Step 3:

[0881] The server receives the JSON data sent from the device and parses it using a server-side script (e.g., Python, Flask).

[0882] Input: JSON data sent from the terminal

[0883] Output: Parsed room dimensions and style information

[0884] Specific operation: Parsing and extracting JSON data

[0885] Step 4:

[0886] The server runs an algorithm to generate an optimal furniture layout based on the analyzed room dimensions and style information. The algorithm takes the room dimensions as input and calculates the optimal placement of each piece of furniture.

[0887] Input: Parsed room dimensions and style information

[0888] Output: Optimal furniture layout information (e.g. furniture name and placement position)

[0889] Specific operation: Execution of layout generation algorithm

[0890] Step 5:

[0891] The server searches for furniture information using the API of the online shopping platform based on the generated furniture layout information, sending an API request to obtain the name, price, purchase link, etc. of the relevant furniture.

[0892] Input: Optimal furniture layout information

[0893] Output: Retrieved furniture information

[0894] Specific behavior: Generating API requests and parsing responses

[0895] Step 6:

[0896] The server integrates the generated furniture layout information with the acquired furniture information and sends it back to the terminal as JSON format data. The integration process is performed by a server-side script (e.g., Python).

[0897] Input: Optimal furniture layout information and retrieved furniture information

[0898] Output: Consolidated JSON data

[0899] Specific behavior: Data merging and format conversion

[0900] Step 7:

[0901] The device receives the aggregated data sent from the server and displays the results to the user in a visual format, including a furniture layout diagram of the room and each furniture option with its name, price, and a purchase link.

[0902] Input: Aggregated data sent from the server

[0903] Output: Visual display results

[0904] Specific behavior: Analyzing data and displaying it in the interface

[0905] Step 8:

[0906] Users can use smart devices (e.g., smartphones, smart glasses) to check the furniture arrangement in a room in real time. This function is realized using Augmented Reality (AR) technology.

[0907] Input: Room dimensions, style information, and generated furniture layout

[0908] Output: Real-time display of furniture layout

[0909] Specific operation: Displaying furniture in real space using AR technology

[0910] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0911] The present invention combines a system that generates an optimal furniture layout based on the dimensions and style information of a user's room and suggests furniture that can be purchased at an affordable price from an online shopping platform with an emotion engine that recognizes the user's emotions. Each component of the system and its operation will be described in detail below.

[0912] System Configuration

[0913] 1. User input method

[0914] The user uses an input form on the terminal to input the room dimensions (length, width, height) and style (modern, classic, etc.).

[0915] 2. Acquisition method

[0916] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[0917] 3. Generation means

[0918] The server executes an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[0919] 4. Search Methods

[0920] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[0921] 5. Display means

[0922] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[0923] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[0924] 6. Emotion Engine

[0925] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[0926] The server adjusts the furniture layout to be generated and the type of furniture to be suggested based on the user's emotions identified by the emotion engine.

[0927] Program processing overview

[0928] User Input

[0929] The user enters the room information (dimensions, style) into the terminal using the input form. The entered data is converted into JSON format and sent to the server.

[0930] Data reception and analysis

[0931] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[0932] Layout Generation

[0933] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (for example, placing the sofa at position X=1, Y=1).

[0934] Emotion Recognition and Analysis

[0935] The device analyzes the user's facial expressions and voice using an emotion engine to identify the user's emotions.

[0936] Furniture Search

[0937] The server searches for furniture using the API of the online shopping platform based on the generated layout information, obtains the name, price, and purchase link for each piece of furniture, and adjusts the suggestions based on the user's sentiment.

[0938] Consolidating and sending results

[0939] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[0940] Displaying the results

[0941] The device receives the JSON data sent from the server, analyzes it, and displays it to the user in a visually easy-to-understand format, providing the user with a furniture layout diagram and options for each piece of furniture (with name, price, and purchase link).

[0942] Specific examples

[0943] For example, if a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[0944] 1. The user inputs the length, width, height and style of the room.

[0945] 2. The terminal converts the input data into JSON format and sends it to the server.

[0946] 3. The server analyzes the received data and generates the optimal furniture layout.

[0947] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[0948] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[0949] 6. The terminal analyzes the received data and displays it to the user in a visually easy-to-understand format.

[0950] 7. The device analyzes the user's facial expressions and voice to recognize their emotions.

[0951] 8. The server adjusts the suggestions based on the perceived sentiment.

[0952] 9. The user checks the proposed furniture layout and purchase link on the device and purchases the furniture if necessary.

[0953] The system allows users to find optimal furniture placement and purchasing options based on their emotional state.

[0954] The processing flow will be explained below.

[0955] Step 1:

[0956] The user inputs the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form on the terminal.

[0957] Step 2:

[0958] The terminal converts the user input data into JSON format.

[0959] example:

[0960] json

[0961] {

[0962] "length": 5,

[0963] "width": 4,

[0964] "height": 3,

[0965] "style": "modern"

[0966] }

[0967] Step 3:

[0968] The terminal sends the data converted into JSON format to the server via an HTTP request.

[0969] Step 4:

[0970] The server receives and analyzes the JSON data sent from the device.

[0971] Step 5:

[0972] The server runs an algorithm to generate the optimal furniture layout based on the received data, calculating the placement of each piece of furniture based on the room dimensions and style information.

[0973] example:

[0974] json

[0975] {

[0976] "sofa": {"x": 1, "y": 1},

[0977] "table": {"x": 2, "y": 2},

[0978] "bed": {"x": 3, "y": 3}

[0979] }

[0980] Step 6:

[0981] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[0982] example:

[0983] Emotion engine result: "happy"

[0984] Step 7:

[0985] The server receives emotion data from the emotion engine and adjusts the furniture layout to suit the user's needs. For example, if the user feels sad, the server will suggest brightly colored furniture.

[0986] Step 8:

[0987] The server sends furniture search requests to the APIs of multiple online shopping platforms based on the generated layout information. It creates search queries that include the names and characteristics of the furniture.

[0988] example:

[0989] Example request:

[0990] json

[0991] {

[0992] "query": "modern sofa",

[0993] "max_price": 30000

[0994] }

[0995] Step 9:

[0996] The server receives and analyzes the API responses from each platform.

[0997] Step 10:

[0998] The server formats the acquired furniture information and integrates it with the generated furniture layout information.

[0999] example:

[1000] json

[1001] {

[1002] "layout": {

[1003] "sofa": {"x": 1, "y": 1},

[1004] "table": {"x": 2, "y": 2},

[1005] "bed": {"x": 3, "y": 3}

[1006] },

[1007] "furniture": [

[1008] {"name": "Modern sofa", "price": 20000, "url": "https: / / example.com / sofa"},

[1009] {"name": "Glass Table", "price": 15000, "url": "https: / / example.com / table"},

[1010] {"name": "Comfortable Bed", "price": 30000, "url": "https: / / example.com / bed"}

[1011] ]

[1012] }

[1013] Step 11:

[1014] The server sends the formatted data in JSON format to the terminal.

[1015] Step 12:

[1016] The device parses the received JSON data and displays it to the user in a visually easy-to-understand format, providing the user with a furniture layout diagram and options for each piece of furniture (with name, price, and purchase link).

[1017] Step 13:

[1018] The user checks the proposed furniture layout and purchase link on the terminal and purchases the furniture as necessary.

[1019] Example 2

[1020] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1021] Conventional furniture layout suggestion systems simply provide optimal layouts based on the dimensions and style of a room, but lack the ability to adjust the suggestions based on the user's emotional state. As a result, users often feel dissatisfied with the proposed furniture layout. To solve this problem, a system is needed that can suggest furniture and layouts that reflect the user's emotional state.

[1022] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user input means, an acquisition means for acquiring room dimension and style information from the input means, a generation means for generating an optimal furniture layout based on the room dimension and style information acquired by the acquisition means, a search means for searching for furniture information from an online shopping platform based on the layout information generated by the generation means, an acquisition means for acquiring the furniture information acquired by the search means, a display means for displaying the furniture information and furniture layout acquired by the acquisition means on the user terminal, an emotion recognition means for the terminal to recognize the user's emotion in real time, and an adjustment means for adjusting the generated furniture layout or the proposed furniture based on the emotion recognized by the emotion recognition means. This makes it possible to propose an optimal furniture layout and furniture that reflects the user's emotional state.

[1023] A "user input means" is a device that provides an interface for a user to input room dimensions and style information.

[1024] The "acquisition means" is a method or device for collecting data obtained from the user's input means and proceeding to the next step.

[1025] The "generation means" refers to an algorithm or program that calculates and generates an optimal furniture layout based on the data obtained by the acquisition means.

[1026] The "search means" refers to a method or device for searching for furniture information on the online shopping platform based on the layout information generated by the generation means.

[1027] The "display means" is a method or device for visually displaying the furniture information collected by the acquisition means and the furniture layout information generated on the user terminal.

[1028] An "emotion recognition means" is a method or equipment for capturing a user's facial expressions and voice in real time and analyzing them to identify the user's emotions.

[1029] The "adjustment means" is a method or apparatus that adjusts the generated furniture layout or suggested furniture based on the user's emotions identified by the emotion recognition means.

[1030] The present invention combines a system that generates an optimal furniture layout based on the user's room dimensions and style information and suggests furniture that can be purchased at an affordable price from an online shopping platform with an emotion engine that recognizes the user's emotions.

[1031] System Configuration

[1032] 1. User input method

[1033] The user uses an input form on the terminal to input the room dimensions (length, width, height) and style (e.g., modern, classic).

[1034] 2. Acquisition method

[1035] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[1036] 3. Generation means

[1037] The server executes an algorithm for generating an optimal furniture layout based on the room dimensions and style information acquired by the acquisition means. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[1038] 4. Search Methods

[1039] The server searches for furniture on the online shopping platform based on the generated furniture layout information and obtains matching furniture information using an API.

[1040] 5. Display means

[1041] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[1042] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[1043] 6. Emotion recognition means

[1044] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[1045] 7. Adjustment means

[1046] The server adjusts the furniture layout to be generated and the type of furniture to be proposed based on the user's emotion identified by the emotion recognition means.

[1047] System Operation Overview

[1048] User Input

[1049] The user inputs the dimensions and style of the room into a form on the browser. For example, the user inputs "room length: 5 meters, width: 4 meters, height: 3 meters, style: modern."

[1050] Data reception and analysis

[1051] The terminal converts the data entered by the user into JSON format and sends it to the server, which receives and analyzes the data.

[1052] Layout Generation

[1053] The server generates the optimal furniture layout based on the analyzed data. For example, the server calculates a specific layout such as "placing the sofa longitudinally and placing the table in the center."

[1054] Emotion Recognition and Analysis

[1055] The device uses a camera and microphone to capture the user's facial expressions and voice in real time, and analyzes them with an emotion engine. As a result, emotions such as "joy" are identified.

[1056] Furniture Search

[1057] Based on the optimal furniture layout, the server retrieves matching furniture information from online shopping platforms, such as a modern sofa or a wooden table, via API, and obtains the name, price, and purchase link.

[1058] Consolidating and sending results

[1059] The server combines the generated layout information and the acquired furniture information and sends it to the device as new JSON data. The device then analyzes the received data and visually displays a furniture layout diagram and furniture options.

[1060] Specific examples

[1061] For example, if a user enters the dimensions of a room as "5m x 4m x 3m" and the style as "Modern," the system will perform the following steps:

[1062] 1. The user inputs the dimensions and style of the room.

[1063] 2. The terminal converts the input data into JSON format and sends it to the server.

[1064] 3. The server receives and analyzes the data.

[1065] 4. The server generates the optimal furniture layout.

[1066] 5. The device recognizes the user's emotions and sends the analysis results to the server.

[1067] 6. Based on the generated layout information, the server searches for furniture information from the online shopping platform via API.

[1068] 7. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal.

[1069] 8. The device analyzes the received data and displays it to the user in a visually understandable format.

[1070] Examples of prompt statements

[1071] Examples of prompts to be input to a generative AI model include:

[1072] "Suggest the best furniture layout based on the room dimensions and style, and adjust it according to the user's emotions. Room information is: Length: 5 meters, Width: 4 meters, Height: 3 meters, Style: Modern. User's emotions: Joy."

[1073] keyword

[1074] Generative AI model, prompt sentence, furniture layout, emotion engine, online shopping platform, room dimensions, room style, furniture suggestions, user input

[1075] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1076] Step 1:

[1077] The user enters the dimensions (length, width, height) and style (e.g., modern, classic) of the room into an input form on the device. The input data is formatted in JSON format.

[1078] Specific behavior: The user enters the following into a form on the browser: "Room length: 5 meters, width: 4 meters, height: 3 meters, style: modern." The device converts this data into JSON format ({ "length": 5, "width": 4, "height": 3, "style": "modern"}).

[1079] Input: User input of dimensions and styles

[1080] Output: Input information in JSON data format

[1081] Step 2:

[1082] The device sends the JSON data generated in step 1 to the server.

[1083] Specific behavior: The device sends JSON data to the server using an HTTP POST request.

[1084] Input: JSON data generated in step 1

[1085] Output: Send data to the server

[1086] Step 3:

[1087] The server receives and parses the JSON data.

[1088] What it does: The server parses the received JSON data and extracts the room's length, width, height, and style information.

[1089] Input: JSON data sent in step 2

[1090] Output: Parsed room information (length, width, height, style)

[1091] Step 4:

[1092] The server generates the optimal furniture layout based on the analyzed data.

[1093] How it works: The server uses an algorithm to calculate the placement of each piece of furniture and generate a layout, for example placing a sofa along the length of the room and a table in the center.

[1094] Input: Room information parsed in step 3

[1095] Output: Generated furniture layout information

[1096] Step 5:

[1097] The device captures the user's facial expressions and voice in real time and sends them to the emotion engine.

[1098] Specific operation: The device uses the camera and microphone to capture the user's facial expressions and voice, which are then analyzed by the emotion engine.

[1099] Input: Real-time captured facial expression and voice data

[1100] Output: Identified emotion information (e.g., joy, surprise)

[1101] Step 6:

[1102] The server adjusts the furniture layout and suggested furniture based on the analysis results from the emotion recognition means.

[1103] Specific behavior: The server adjusts the furniture arrangement and type based on the identified emotion (e.g., "joy"), for example, preferentially suggesting brightly colored furniture.

[1104] Input: Emotion information identified in step 5

[1105] Output: Adjusted furniture layout and suggested furniture information

[1106] Step 7:

[1107] The server uses the API of the online shopping platform to search for furniture information based on the adjusted layout information.

[1108] Specific operation: The server uses the API to obtain the furniture name, price, purchase link, etc. For example, search for "modern sofa" or "wooden table."

[1109] Input: Furniture layout information adjusted in step 6

[1110] Output: Retrieved furniture information (name, price, purchase link)

[1111] Step 8:

[1112] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal in JSON format.

[1113] Specific operation: The server integrates the layout information and furniture information, generates new JSON data, and sends it to the terminal.

[1114] Input: Furniture information obtained in step 7 and furniture layout information adjusted in step 6

[1115] Output: Consolidated JSON data

[1116] Step 9:

[1117] The device parses the received JSON data and displays it to the user in a visually easy-to-understand format.

[1118] Specific operation: The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links). The user can check the furniture layout and furniture information on the screen.

[1119] Input: JSON data sent in step 8

[1120] Output: Visually displayed furniture layout and furniture information

[1121] keyword

[1122] Generative AI model, prompt sentence

[1123] (Application example 2)

[1124] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1125] Conventional furniture layout generation systems simply propose optimal furniture layouts without considering the user's emotional state. This prevents flexible proposals based on the user's emotions and preferences, and fails to increase user satisfaction. Furthermore, there is a lack of systems that allow users to easily purchase the proposed furniture through online shopping. This makes the process of users finding and purchasing the furniture that best suits them cumbersome.

[1126] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for generating an optimal furniture layout based on the dimensions and style information of the user's room, means for searching for furniture information from an online shopping platform, means for displaying the acquired furniture information and furniture layout on the user terminal, means for capturing facial expressions and voice and identifying emotions, and means for adjusting the furniture layout and suggested furniture information based on the identified emotional information. This enables flexible furniture layout and suggestions based on the user's emotional state, providing a smooth purchasing process through online shopping.

[1127] "Input means" refers to a device or interface through which a user inputs room size and style information.

[1128] The "acquisition means" is a device or system having a function for acquiring and analyzing the room dimension and style information sent from the input means.

[1129] The "generator" is an algorithm or device that generates an optimal furniture layout based on the room dimensions and style information acquired by the acquirer.

[1130] The "search means" is a device or system having a function for searching furniture information from an online shopping platform based on the layout information generated by the generation means.

[1131] The "display means" refers to a device or software for displaying the acquired furniture information and furniture layout on a user terminal.

[1132] An "emotion recognition means" is a technology or device that captures a user's facial expressions and voice and identifies emotions from them.

[1133] The "adjustment means" is a device or system that has the function of correcting or optimizing the generated furniture layout or the proposed furniture information based on the emotion information identified by the emotion recognition means.

[1134] An "online shopping platform" is a website or application that allows users to search for, view, and purchase products over the Internet.

[1135] "Furniture layout" refers to the position information and layout diagram of furniture arranged based on the dimensions and style information of the room.

[1136] "Furniture information" refers to detailed information such as the name, price, size, and purchase link of the furniture obtained from the online shopping platform.

[1137] A "terminal" is an electronic device used by a user to enter data or display results, and includes smartphones, tablets, and personal computers.

[1138] The present invention is a system that generates an optimal furniture layout based on the dimensions and style information of a user's room, and suggests suitable furniture from an online shopping platform. It also has the ability to identify the user's emotional state and adjust the furniture layout and suggestions accordingly.

[1139] System configuration:

[1140] Input methods:

[1141] Users use devices such as smartphones, tablets, and computers to enter the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form.

[1142] Acquisition method:

[1143] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[1144] Generation means:

[1145] The server runs an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information, which includes calculating the placement of furniture.

[1146] Search by:

[1147] The server searches for furniture information from the online shopping platform based on the generated furniture layout information and obtains matching furniture information using an API.

[1148] Display means:

[1149] The server combines the acquired furniture information with the generated furniture layout information and sends it to the device as JSON format data. The device then analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[1150] Emotion recognition means:

[1151] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine, which identifies the user's emotions (e.g., joy, surprise, sadness, etc.).

[1152] Adjustment means:

[1153] The server adjusts the furniture layout to be generated and the type of furniture to be suggested based on the user's emotions identified by the emotion engine.

[1154] Hardware and software used:

[1155] Hardware: Smartphone, tablet, computer camera and microphone

[1156] Software: Emotion recognition engine (ai_emotion_recognition), furniture layout generation algorithm (furniture_layout_generator), online shopping search API (online_shopping_api)

[1157] Data processing and calculation details:

[1158] 1. The server receives and analyzes the room dimensions and style information sent from the terminal.

[1159] 2. The server runs an algorithm that generates the optimal furniture layout based on the analysis results.

[1160] 3. The server uses an API to obtain compatible furniture information from the online shopping platform based on the generated furniture layout information.

[1161] 4. The device captures the user's facial expression and voice data and uses an emotion recognition engine to identify emotions.

[1162] 5. The server adjusts the generated furniture layout and suggestions based on the analysis results of the emotion recognition engine.

[1163] Examples:

[1164] For example, if a user enters the following room information:

[1165] "My room measures 5 meters long, 4 meters wide, and 3 meters high. I want to fill it with modern-style furniture."

[1166] The system goes through the following steps:

[1167] 1. The user inputs the room dimensions and style.

[1168] 2. The terminal converts the input data into JSON format and sends it to the server.

[1169] 3. The server analyzes the received data and generates the optimal furniture layout.

[1170] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[1171] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[1172] 6. The device analyzes the received data and displays it to the user in a visually understandable format.

[1173] 7. The device analyzes the user's facial expressions and voice to recognize their emotions.

[1174] 8. The server adjusts the suggestions based on the perceived sentiment.

[1175] This allows users to find the best furniture arrangement and purchasing options based on their emotional state.

[1176] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1177] Step 1:

[1178] The user enters the dimensions (length, width, height) and style (modern, classic, etc.) of a room into an input form on the device. The input data is converted into JSON format. The input is information about the physical characteristics and design style of the room.

[1179] Step 2:

[1180] The device sends the user input data in JSON format to the server, which parses the data and extracts the room dimensions and style information. This step checks the consistency and completeness of the input data.

[1181] Step 3:

[1182] The server runs an algorithm to generate an optimal furniture layout based on the room dimensions and style information. The algorithm calculates the placement position of each piece of furniture and generates a furniture layout plan that matches the room dimensions. The output is layout information showing the placement positions of the furniture.

[1183] Step 4:

[1184] The server uses the API to search for furniture information from an online shopping platform based on the generated furniture layout information. The input is the generated layout information, and the output is the searched multiple furniture options (name, price, purchase link, etc.).

[1185] Step 5:

[1186] The server combines the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data. This process determines the furniture configuration to be proposed to the user.

[1187] Step 6:

[1188] The device receives and parses the JSON data sent from the server. After parsing, it displays a furniture layout diagram and furniture options (with names, prices, and purchase links) in a visually easy-to-understand format to the user. At this point, the user can review the proposed furniture.

[1189] Step 7:

[1190] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The input is the user's facial expressions and voice data, and the output is analyzed emotional information (e.g., joy, surprise, sadness, etc.).

[1191] Step 8:

[1192] The server adjusts the generated furniture layout and furniture suggestions based on the emotional information identified by the emotion engine. This adjustment determines the suggestions that are optimized for the user's emotional state. The final output is a furniture layout and furniture options that are adjusted based on the emotional information.

[1193] This clarifies the specific processing and operations of each step, making it possible to propose optimal furniture that takes into account the user's emotional state.

[1194] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1195] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1196] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1197] [Third embodiment]

[1198] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1199] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1200] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1201] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1202] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1203] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1204] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1205] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1206] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1207] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1208] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1209] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[1210] The present invention provides a system that generates an optimal furniture layout based on the dimensions and style information of a user's room and suggests furniture that can be purchased at an affordable price from an online shopping platform. The system is mainly configured as follows.

[1211] System Configuration

[1212] 1. User input method

[1213] The user uses an input form provided on the terminal to input the dimensions (for example, length, width, height) and style (modern, classic, etc.) of the room.

[1214] 2. Acquisition method

[1215] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[1216] 3. Generation means

[1217] The server executes an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[1218] 4. Search Methods

[1219] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[1220] 5. Display means

[1221] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[1222] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[1223] Program processing overview

[1224] User Input

[1225] The user enters the room information (dimensions, style) into the terminal using the input form. The entered data is converted into JSON format and sent to the server.

[1226] Data reception and analysis

[1227] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[1228] Layout Generation

[1229] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (for example, placing the sofa at position X=1, Y=1).

[1230] Furniture Search

[1231] The server searches for furniture using the API of the online shopping platform based on the generated layout information, and obtains the name, price, and purchase link for each piece of furniture.

[1232] Consolidating and sending results

[1233] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[1234] Displaying the results

[1235] The device receives the data sent from the server, analyzes it, and then displays the results to the user in a visual format, providing the user with a furniture layout diagram and each furniture option (with name, price, and purchase link).

[1236] Specific examples

[1237] If a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[1238] 1. The user inputs the length, width, height and style of the room.

[1239] 2. The terminal converts the input data into JSON format and sends it to the server.

[1240] 3. The server analyzes the received data and generates the optimal furniture layout.

[1241] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[1242] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[1243] 6. The device analyzes the received data and displays the results visually to the user.

[1244] The system allows users to easily find the furniture layout that best suits their room and purchase that furniture at an affordable price.

[1245] The processing flow will be explained below.

[1246] Step 1:

[1247] The user inputs the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form on the terminal.

[1248] Step 2:

[1249] The terminal converts the user input data into JSON format.

[1250] example:

[1251] json

[1252] {

[1253] "length": 5,

[1254] "width": 4,

[1255] "height": 3,

[1256] "style": "modern"

[1257] }

[1258] Step 3:

[1259] The terminal sends the data converted into JSON format to the server via an HTTP request.

[1260] Step 4:

[1261] The server receives and analyzes the JSON data sent from the device.

[1262] Step 5:

[1263] The server runs an algorithm to generate the optimal furniture layout based on the received data, calculating the placement of each piece of furniture based on the room dimensions and style information.

[1264] example:

[1265] json

[1266] {

[1267] "sofa": {"x": 1, "y": 1},

[1268] "table": {"x": 2, "y": 2},

[1269] "bed": {"x": 3, "y": 3}

[1270] }

[1271] Step 6:

[1272] The server sends furniture search requests to the APIs of multiple online shopping platforms based on the generated layout information. It creates search queries that include the names and characteristics of the furniture.

[1273] example:

[1274] Example request:

[1275] json

[1276] {

[1277] "query": "modern sofa",

[1278] "max_price": 30000

[1279] }

[1280] Step 7:

[1281] The server receives and analyzes the API responses from each platform.

[1282] Step 8:

[1283] The server formats the acquired furniture information and integrates it with the generated furniture layout information.

[1284] example:

[1285] json

[1286] {

[1287] "layout": {

[1288] "sofa": {"x": 1, "y": 1},

[1289] "table": {"x": 2, "y": 2},

[1290] "bed": {"x": 3, "y": 3}

[1291] },

[1292] "furniture": [

[1293] {"name": "Modern sofa", "price": 20000, "url": "https: / / example.com / sofa"},

[1294] {"name": "Glass Table", "price": 15000, "url": "https: / / example.com / table"},

[1295] {"name": "Comfortable Bed", "price": 30000, "url": "https: / / example.com / bed"}

[1296] ]

[1297] }

[1298] Step 9:

[1299] The server sends the formatted data in JSON format to the terminal.

[1300] Step 10:

[1301] The terminal analyzes the received JSON data and displays it to the user in a visually easy-to-understand format.

[1302] Step 11:

[1303] The user checks the proposed furniture layout and purchase link on the terminal and purchases the furniture as necessary.

[1304] Example 1

[1305] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1306] Conventionally, it is very time-consuming and requires specialized knowledge for users to manually design the optimal furniture layout that matches the dimensions and style of the room and then search for the appropriate furniture. Therefore, there is a need for a system that can efficiently generate the optimal layout and allow users to easily select and purchase the appropriate furniture.

[1307] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1308] In this invention, the server includes a user input means, an acquisition means for acquiring room size and style information from the input means, a means for converting the acquired room size and style information into JSON format and transmitting the converted information to the server, a generation means for the server to generate an optimal furniture layout based on the acquired room size and style information, a search means for searching for furniture information from an API of an online shopping platform based on the layout information generated by the generation means, a acquisition means for acquiring the furniture information acquired by the search means, a means for integrating the acquired furniture information and the generated furniture layout and transmitting the combined data to a terminal in JSON format, and a display means for analyzing the data received by the terminal and displaying the combined data to the user in a visual format. This allows users to efficiently generate optimal furniture layouts and easily select and purchase appropriate furniture.

[1309] "User input means" is an interface provided on the terminal for the user to input room size and style information.

[1310] "Acquisition means" refers to the function that acquires room dimensions and style information from the user's input means and converts it into JSON format.

[1311] "JSON format" is a data structure in JavaScript Object Notation format, which is a method of expressing data in text format.

[1312] A "server" is a computer device that receives, analyzes, and processes data sent from an input means.

[1313] "Generator" refers to the functionality of the server that runs an algorithm to generate an optimal furniture layout based on room dimensions and style information.

[1314] The "search means" is a function for searching furniture information using the API of the online shopping platform based on the generated layout information.

[1315] An "online shopping platform" is a web service that provides product information and sells products via the Internet.

[1316] "API" stands for Application Programming Interface, and is an interface that allows software to provide and call functions to other software.

[1317] The "acquisition means" is a function that receives and processes furniture information acquired by the search means (used for a purpose different from the above-mentioned "acquisition means").

[1318] The "integration means" is a function that combines the generated furniture layout information and the acquired furniture information into a single data format (JSON format).

[1319] "Transmission means" refers to a function for transmitting the integrated data to the terminal.

[1320] The "analysis means" is a function that allows the terminal to process the JSON data received from the server and understand its structure.

[1321] "Display means" is a function of the terminal for visually presenting analyzed data to the user.

[1322] The present invention provides a system for generating an optimal furniture layout by a user inputting room dimensions and style information, and for suggesting affordable furniture from an online shopping platform based on the optimal furniture layout. The system includes the following means and processing steps:

[1323] System configuration

[1324] The system mainly consists of user input means, acquisition means, generation means, search means, integration means, transmission means, and display means. Specifically, the following hardware and software are used:

[1325] Hardware

[1326] User terminal: PC, tablet, smartphone, etc. Provides input and display means.

[1327] Server: A remotely located high-performance computer, cloud service, etc. that receives, analyzes, generates, searches, integrates, and transmits data.

[1328] software

[1329] Input Form: An HTML form that runs in a web browser, allowing users to enter room dimensions and style information.

[1330] JSON conversion library: A data format conversion library using JavaScript or other programming languages.

[1331] Server application: Implemented using Python's Flask framework, etc. Performs data analysis, layout generation, and API communication.

[1332] API: An API provided by an online shopping platform (e.g., Amazon) that acts as a search engine.

[1333] Presentation library: Visual presentation using HTML, CSS, and JavaScript.

[1334] Data processing and calculation

[1335] User Input

[1336] The user uses an input form on the terminal to input the dimensions of the room (e.g., 5 meters x 4 meters x 3 meters) and the style (e.g., modern), and the terminal acquires the input data.

[1337] Sending and Receiving Data

[1338] The device converts the acquired data into JSON format and sends it to the server. The server parses the received JSON data. For example, it receives data in the format {"length": 5, "width": 4, "height": 3, "style": "modern"}.

[1339] Generate layout

[1340] The server generates an optimal furniture layout based on the analyzed data. Specifically, a generation algorithm implemented in Python calculates the placement of each piece of furniture based on the room dimensions. For example, the sofa might be placed in the upper left corner of the room, and the table in the center.

[1341] Furniture Search

[1342] Based on the generated layout information, the server searches for furniture using the API of the online shopping platform, sending an HTTP request to the API endpoint to obtain the name, price, and purchase link of the appropriate furniture.

[1343] Consolidating and sending results

[1344] The server combines the acquired furniture information with the generated furniture layout information and sends it back to the device as JSON format data. For example, it generates data like this: {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}

[1345] Displaying the results

[1346] The device parses the JSON data received from the server and presents it visually to the user, for example, using HTML and JavaScript to display a furniture layout diagram and each furniture option (name, price, purchase link).

[1347] Specific examples

[1348] If a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[1349] 1. The user inputs the length, width, height, and style of the room.

[1350] 2. The device converts the input data into JSON format and sends it to the server. For example, it sends the following data: {"length": 5, "width": 4, "height": 3, "style": "modern"}.

[1351] 3. The server analyzes the received data and generates an optimal furniture layout, for example, placing the sofa at position X=1, Y=1.

[1352] 4. Based on the generated layout information, the server searches for furniture information from an online shopping platform through API, for example, searching for a modern-style sofa.

[1353] 5. The server combines the furniture information it has acquired with the generated layout information and sends it to the device as JSON data. For example, it generates the following data: {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}

[1354] 6. The device analyzes the received data and displays the results visually to the user, for example, using HTML and JavaScript to display a furniture layout diagram and a link to purchase.

[1355] Prompt Sentence Examples

[1356] "Based on the following information, design a program to generate a furniture layout diagram, search for suitable furniture from an online shopping platform based on this diagram, and provide its name, price, and purchase link."

[1357] Room dimensions: 5 meters long, 4 meters wide, 3 meters high

[1358] Style: Modern

[1359] Example output:

[1360] Layout diagram: Sofa placed at X=1, Y=1

[1361] Furniture information: Name: "Modern Sofa", Price: "199.99 USD", Purchase link: "http: / / example.com / sofa"

[1362] This invention allows users to easily understand the furniture layout that is suitable for their room and select and purchase that furniture at an affordable price.

[1363] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1364] Step 1:

[1365] The user uses the input form displayed on the device's web browser to input the dimensions (length, width, height) and style (modern, etc.) of the room. Specifically, the user enters numbers or text in each input field and presses the submit button. This acquires the input data.

[1366] Input: Room dimensions (length, width, height) and style information

[1367] Output: Input data (dimensions and style information)

[1368] Step 2:

[1369] The terminal converts the data entered by the user into JSON format. A JavaScript library (e.g., JSON.stringify()) is used to convert the data. After conversion, a JSON object such as {"length": 5, "width": 4, "height": 3, "style": "modern"} is generated.

[1370] Input: Data entered by the user

[1371] Output: JSON format data

[1372] Step 3:

[1373] The device sends the data converted to JSON format to the server as an HTTP POST request using an Ajax request or the fetch API.

[1374] Input: Data converted to JSON format

[1375] Output: Request sent to the server

[1376] Step 4:

[1377] The server parses the received JSON data. For example, using the Python Flask framework, the data is retrieved using the request.get_json() method. The parsed data is converted into an internal data structure (e.g., dictionary format).

[1378] Input: JSON data sent from the terminal

[1379] Output: Internal data structure (dictionary format)

[1380] Step 5:

[1381] The server then generates an optimal furniture layout based on the analyzed data, using a Python algorithm to calculate the position of each piece of furniture based on the room's dimensions and style information, such as placing a sofa in the upper left corner of the room and a table in the center.

[1382] Input: Room dimensions and style information

[1383] Output: Furniture layout information

[1384] Step 6:

[1385] The server searches for furniture using the API of an online shopping platform based on the generated furniture layout information, and sends an HTTP request to the API endpoint to obtain the name, price, and purchase link of each piece of furniture.

[1386] Input: Furniture layout information

[1387] Output: Furniture information (name, price, purchase link)

[1388] Step 7:

[1389] The server combines the generated layout information with the acquired furniture information and stores them in a single JSON format data, such as {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}.

[1390] Input: Furniture layout information and acquired furniture information

[1391] Output: Consolidated JSON format data

[1392] Step 8:

[1393] The server sends the consolidated JSON format data to the terminal, which returns the data as an HTTP response.

[1394] Input: Consolidated JSON format data

[1395] Output: The response sent to the device

[1396] Step 9:

[1397] The device parses the received JSON data and converts it into an object using a JavaScript library (e.g., JSON.parse()). The parsed data is treated as an internal data structure.

[1398] Input: JSON data sent from the server

[1399] Output: Internal data structure (object format)

[1400] Step 10:

[1401] The device displays the visual results to the user based on the analyzed data. Using HTML and JavaScript, the layout diagram of the furniture and options for each piece of furniture (name, price, purchase link) are displayed on the screen. Specifically, the layout diagram is drawn using Canvas and SVG elements, and information about each piece of furniture is displayed as text elements.

[1402] Input: Internal data structure (object format)

[1403] Output: The visual result that is displayed to the user

[1404] (Application example 1)

[1405] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1406] Conventional furniture layout suggestion systems have the problem that even if users input the dimensions and style of a room, it is difficult to check in real time how the furniture will actually look. Also, even if furniture information is obtained from an online shopping platform, users cannot check the layout before purchasing, which can lead to problems such as the result being different from expectations after purchase.

[1407] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1408] In this invention, the server includes a user input means, an acquisition means, a generation means, a search means, an acquisition means, a display means, and a means for checking the furniture arrangement status in real time on a smart device, thereby enabling a user to generate an optimal furniture layout by inputting room dimensions and style information, and to decide on a purchase while checking furniture information suggested by the online shopping platform in real time.

[1409] "User input" is an interface through which a user inputs room size and style information.

[1410] The "acquisition means" is a means for transmitting the room size and style information input by the user to the server.

[1411] The "generator" is a means for executing an algorithm that generates an optimal furniture layout based on acquired room dimension and style information.

[1412] The "search means" is a means for searching furniture information from the online shopping platform based on the generated furniture layout information.

[1413] The "display means" is a means for visually presenting the acquired furniture information and the generated furniture layout on the user terminal.

[1414] "Means for checking the furniture arrangement status in real time on a smart device" refers to a means for visually checking the furniture arrangement status in a room in real time using a device such as a smartphone or smart glasses.

[1415] The present invention is a system that generates an optimal furniture layout based on room dimensions and style information and suggests furniture that can be purchased from an online shopping platform. The system includes user input means, acquisition means, generation means, search means, and display means, and further includes a means for checking the furniture arrangement status in real time using a smart device.

[1416] System Configuration

[1417] 1. User input method

[1418] The user uses an input form provided on the terminal to input the dimensions (e.g., length, width, height) and style (e.g., modern, classic) of the room.

[1419] 2. Acquisition method

[1420] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[1421] 3. Generation means

[1422] The server runs an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[1423] 4. Search Methods

[1424] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[1425] 5. Display means

[1426] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[1427] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[1428] 6. Real-time verification method

[1429] Users can use smart devices (e.g., smartphones, smart glasses) to check the furniture layout in real time in the actual room, allowing them to visually check the furniture layout and make adjustments as necessary.

[1430] Program processing overview

[1431] Data reception and analysis

[1432] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[1433] Layout Generation

[1434] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (e.g., placing the sofa at position X=1, Y=1).

[1435] Furniture Search

[1436] The server searches for furniture using the API of the online shopping platform based on the generated layout information, and obtains the name, price, and purchase link for each piece of furniture.

[1437] Consolidating and sending results

[1438] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[1439] Displaying the results

[1440] The device receives the data sent from the server, analyzes it, and then displays the results to the user in a visual format, providing the user with a furniture layout diagram and each furniture option (with name, price, and purchase link).

[1441] Real-time confirmation

[1442] The smart device displays the generated furniture layout in the actual room in real time, allowing the user to visually check the arrangement.

[1443] Specific examples

[1444] If the user inputs the room information as "length: 5m, width: 4m, height: 3m" and the style as "modern", the system will go through the following steps:

[1445] 1. The user inputs the dimensions and style of the room.

[1446] 2. The terminal converts the input data into JSON format and sends it to the server.

[1447] 3. The server analyzes the received data and generates the optimal furniture layout.

[1448] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[1449] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[1450] 6. The device analyzes the received data and displays the results visually to the user.

[1451] 7. The user can use their smart device to view the furniture arrangement in the room in real time.

[1452] Prompt Sentence Examples

[1453] "Generate the optimal furniture layout based on the room information entered by the user, 'Dimensions: 5m x 4m x 3m, Style: Modern', and retrieve and integrate furniture information (name, price, purchase link) available for purchase from online stores."

[1454] This system allows users to easily determine the furniture layout that best suits their room and visually check the layout before making an online purchase, thereby reducing the gap between expectations and reality after purchase and providing a more satisfying shopping experience.

[1455] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1456] Step 1:

[1457] The user enters the room dimensions (e.g., length, width, height) and style information (e.g., modern, classic) using an input form provided on the device. The input form can be accessed through a web browser or a mobile application.

[1458] Input: Room dimensions and style information

[1459] Output: A data object based on the user's input

[1460] Step 2:

[1461] The device converts the input room dimensions and style information into JSON format data and sends this data to the server. The conversion is performed using a front-end script (e.g., JavaScript).

[1462] Input: User-entered room dimensions and style information

[1463] Output: JSON format data

[1464] Specific operation: Converting data format and sending an HTTP request to the server

[1465] Step 3:

[1466] The server receives the JSON data sent from the device and parses it using a server-side script (e.g., Python, Flask).

[1467] Input: JSON data sent from the terminal

[1468] Output: Parsed room dimensions and style information

[1469] Specific operation: Parsing and extracting JSON data

[1470] Step 4:

[1471] The server runs an algorithm to generate an optimal furniture layout based on the analyzed room dimensions and style information. The algorithm takes the room dimensions as input and calculates the optimal placement of each piece of furniture.

[1472] Input: Parsed room dimensions and style information

[1473] Output: Optimal furniture layout information (e.g. furniture name and placement position)

[1474] Specific operation: Execution of layout generation algorithm

[1475] Step 5:

[1476] The server searches for furniture information using the API of the online shopping platform based on the generated furniture layout information, sending an API request to obtain the name, price, purchase link, etc. of the relevant furniture.

[1477] Input: Optimal furniture layout information

[1478] Output: Retrieved furniture information

[1479] Specific behavior: Generating API requests and parsing responses

[1480] Step 6:

[1481] The server integrates the generated furniture layout information with the acquired furniture information and sends it back to the terminal as JSON format data. The integration process is performed by a server-side script (e.g., Python).

[1482] Input: Optimal furniture layout information and retrieved furniture information

[1483] Output: Consolidated JSON data

[1484] Specific behavior: Data merging and format conversion

[1485] Step 7:

[1486] The device receives the aggregated data sent from the server and displays the results to the user in a visual format, including a furniture layout diagram of the room and each furniture option with its name, price, and a purchase link.

[1487] Input: Aggregated data sent from the server

[1488] Output: Visual display results

[1489] Specific behavior: Analyzing data and displaying it in the interface

[1490] Step 8:

[1491] Users can use smart devices (e.g., smartphones, smart glasses) to check the furniture arrangement in a room in real time. This function is realized using Augmented Reality (AR) technology.

[1492] Input: Room dimensions, style information, and generated furniture layout

[1493] Output: Real-time display of furniture layout

[1494] Specific operation: Displaying furniture in real space using AR technology

[1495] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1496] The present invention combines a system that generates an optimal furniture layout based on the dimensions and style information of a user's room and suggests furniture that can be purchased at an affordable price from an online shopping platform with an emotion engine that recognizes the user's emotions. Each component of the system and its operation will be described in detail below.

[1497] System Configuration

[1498] 1. User input method

[1499] The user uses an input form on the terminal to input the room dimensions (length, width, height) and style (modern, classic, etc.).

[1500] 2. Acquisition method

[1501] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[1502] 3. Generation means

[1503] The server executes an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[1504] 4. Search Methods

[1505] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[1506] 5. Display means

[1507] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[1508] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[1509] 6. Emotion Engine

[1510] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[1511] The server adjusts the furniture layout to be generated and the type of furniture to be suggested based on the user's emotions identified by the emotion engine.

[1512] Program processing overview

[1513] User Input

[1514] The user enters the room information (dimensions, style) into the terminal using the input form. The entered data is converted into JSON format and sent to the server.

[1515] Data reception and analysis

[1516] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[1517] Layout Generation

[1518] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (for example, placing the sofa at position X=1, Y=1).

[1519] Emotion Recognition and Analysis

[1520] The device analyzes the user's facial expressions and voice using an emotion engine to identify the user's emotions.

[1521] Furniture Search

[1522] The server searches for furniture using the API of the online shopping platform based on the generated layout information, obtains the name, price, and purchase link for each piece of furniture, and adjusts the suggestions based on the user's sentiment.

[1523] Consolidating and sending results

[1524] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[1525] Displaying the results

[1526] The device receives the JSON data sent from the server, analyzes it, and displays it to the user in a visually easy-to-understand format, providing the user with a furniture layout diagram and options for each piece of furniture (with name, price, and purchase link).

[1527] Specific examples

[1528] For example, if a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[1529] 1. The user inputs the length, width, height and style of the room.

[1530] 2. The terminal converts the input data into JSON format and sends it to the server.

[1531] 3. The server analyzes the received data and generates the optimal furniture layout.

[1532] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[1533] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[1534] 6. The terminal analyzes the received data and displays it to the user in a visually easy-to-understand format.

[1535] 7. The device analyzes the user's facial expressions and voice to recognize their emotions.

[1536] 8. The server adjusts the suggestions based on the perceived sentiment.

[1537] 9. The user checks the proposed furniture layout and purchase link on the device and purchases the furniture if necessary.

[1538] The system allows users to find optimal furniture placement and purchasing options based on their emotional state.

[1539] The processing flow will be explained below.

[1540] Step 1:

[1541] The user inputs the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form on the terminal.

[1542] Step 2:

[1543] The terminal converts the user input data into JSON format.

[1544] example:

[1545] json

[1546] {

[1547] "length": 5,

[1548] "width": 4,

[1549] "height": 3,

[1550] "style": "modern"

[1551] }

[1552] Step 3:

[1553] The terminal sends the data converted into JSON format to the server via an HTTP request.

[1554] Step 4:

[1555] The server receives and analyzes the JSON data sent from the device.

[1556] Step 5:

[1557] The server runs an algorithm to generate the optimal furniture layout based on the received data, calculating the placement of each piece of furniture based on the room dimensions and style information.

[1558] example:

[1559] json

[1560] {

[1561] "sofa": {"x": 1, "y": 1},

[1562] "table": {"x": 2, "y": 2},

[1563] "bed": {"x": 3, "y": 3}

[1564] }

[1565] Step 6:

[1566] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[1567] example:

[1568] Emotion engine result: "happy"

[1569] Step 7:

[1570] The server receives emotion data from the emotion engine and adjusts the furniture layout to suit the user's needs. For example, if the user feels sad, the server will suggest brightly colored furniture.

[1571] Step 8:

[1572] The server sends furniture search requests to the APIs of multiple online shopping platforms based on the generated layout information. It creates search queries that include the names and characteristics of the furniture.

[1573] example:

[1574] Example request:

[1575] json

[1576] {

[1577] "query": "modern sofa",

[1578] "max_price": 30000

[1579] }

[1580] Step 9:

[1581] The server receives and analyzes the API responses from each platform.

[1582] Step 10:

[1583] The server formats the acquired furniture information and integrates it with the generated furniture layout information.

[1584] example:

[1585] json

[1586] {

[1587] "layout": {

[1588] "sofa": {"x": 1, "y": 1},

[1589] "table": {"x": 2, "y": 2},

[1590] "bed": {"x": 3, "y": 3}

[1591] },

[1592] "furniture": [

[1593] {"name": "Modern sofa", "price": 20000, "url": "https: / / example.com / sofa"},

[1594] {"name": "Glass Table", "price": 15000, "url": "https: / / example.com / table"},

[1595] {"name": "Comfortable Bed", "price": 30000, "url": "https: / / example.com / bed"}

[1596] ]

[1597] }

[1598] Step 11:

[1599] The server sends the formatted data in JSON format to the terminal.

[1600] Step 12:

[1601] The device parses the received JSON data and displays it to the user in a visually easy-to-understand format, providing the user with a furniture layout diagram and options for each piece of furniture (with name, price, and purchase link).

[1602] Step 13:

[1603] The user checks the proposed furniture layout and purchase link on the terminal and purchases the furniture as necessary.

[1604] Example 2

[1605] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1606] Conventional furniture layout suggestion systems simply provide optimal layouts based on the dimensions and style of a room, but lack the ability to adjust the suggestions based on the user's emotional state. As a result, users often feel dissatisfied with the proposed furniture layout. To solve this problem, a system is needed that can suggest furniture and layouts that reflect the user's emotional state.

[1607] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user input means, an acquisition means for acquiring room dimension and style information from the input means, a generation means for generating an optimal furniture layout based on the room dimension and style information acquired by the acquisition means, a search means for searching for furniture information from an online shopping platform based on the layout information generated by the generation means, an acquisition means for acquiring the furniture information acquired by the search means, a display means for displaying the furniture information and furniture layout acquired by the acquisition means on the user terminal, an emotion recognition means for the terminal to recognize the user's emotion in real time, and an adjustment means for adjusting the generated furniture layout or the proposed furniture based on the emotion recognized by the emotion recognition means. This makes it possible to propose an optimal furniture layout and furniture that reflects the user's emotional state.

[1608] A "user input means" is a device that provides an interface for a user to input room dimensions and style information.

[1609] The "acquisition means" is a method or device for collecting data obtained from the user's input means and proceeding to the next step.

[1610] The "generation means" refers to an algorithm or program that calculates and generates an optimal furniture layout based on the data obtained by the acquisition means.

[1611] The "search means" refers to a method or device for searching for furniture information on the online shopping platform based on the layout information generated by the generation means.

[1612] The "display means" is a method or device for visually displaying the furniture information collected by the acquisition means and the furniture layout information generated on the user terminal.

[1613] An "emotion recognition means" is a method or equipment for capturing a user's facial expressions and voice in real time and analyzing them to identify the user's emotions.

[1614] The "adjustment means" is a method or apparatus that adjusts the generated furniture layout or suggested furniture based on the user's emotions identified by the emotion recognition means.

[1615] The present invention combines a system that generates an optimal furniture layout based on the user's room dimensions and style information and suggests furniture that can be purchased at an affordable price from an online shopping platform with an emotion engine that recognizes the user's emotions.

[1616] System Configuration

[1617] 1. User input method

[1618] The user uses an input form on the terminal to input the room dimensions (length, width, height) and style (e.g., modern, classic).

[1619] 2. Acquisition method

[1620] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[1621] 3. Generation means

[1622] The server executes an algorithm for generating an optimal furniture layout based on the room dimensions and style information acquired by the acquisition means. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[1623] 4. Search Methods

[1624] The server searches for furniture on the online shopping platform based on the generated furniture layout information and obtains matching furniture information using an API.

[1625] 5. Display means

[1626] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[1627] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[1628] 6. Emotion recognition means

[1629] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[1630] 7. Adjustment means

[1631] The server adjusts the furniture layout to be generated and the type of furniture to be proposed based on the user's emotion identified by the emotion recognition means.

[1632] System Operation Overview

[1633] User Input

[1634] The user inputs the dimensions and style of the room into a form on the browser. For example, the user inputs "room length: 5 meters, width: 4 meters, height: 3 meters, style: modern."

[1635] Data reception and analysis

[1636] The terminal converts the data entered by the user into JSON format and sends it to the server, which receives and analyzes the data.

[1637] Layout Generation

[1638] The server generates the optimal furniture layout based on the analyzed data. For example, the server calculates a specific layout such as "placing the sofa longitudinally and placing the table in the center."

[1639] Emotion Recognition and Analysis

[1640] The device uses a camera and microphone to capture the user's facial expressions and voice in real time, and analyzes them with an emotion engine. As a result, emotions such as "joy" are identified.

[1641] Furniture Search

[1642] Based on the optimal furniture layout, the server retrieves matching furniture information from online shopping platforms, such as a modern sofa or a wooden table, via API, and obtains the name, price, and purchase link.

[1643] Consolidating and sending results

[1644] The server combines the generated layout information and the acquired furniture information and sends it to the device as new JSON data. The device then analyzes the received data and visually displays a furniture layout diagram and furniture options.

[1645] Specific examples

[1646] For example, if a user enters the dimensions of a room as "5m x 4m x 3m" and the style as "Modern," the system will perform the following steps:

[1647] 1. The user inputs the dimensions and style of the room.

[1648] 2. The terminal converts the input data into JSON format and sends it to the server.

[1649] 3. The server receives and analyzes the data.

[1650] 4. The server generates the optimal furniture layout.

[1651] 5. The device recognizes the user's emotions and sends the analysis results to the server.

[1652] 6. Based on the generated layout information, the server searches for furniture information from the online shopping platform via API.

[1653] 7. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal.

[1654] 8. The device analyzes the received data and displays it to the user in a visually understandable format.

[1655] Examples of prompt statements

[1656] Examples of prompts to be input to a generative AI model include:

[1657] "Suggest the best furniture layout based on the room dimensions and style, and adjust it according to the user's emotions. Room information is: Length: 5 meters, Width: 4 meters, Height: 3 meters, Style: Modern. User's emotions: Joy."

[1658] keyword

[1659] Generative AI model, prompt sentence, furniture layout, emotion engine, online shopping platform, room dimensions, room style, furniture suggestions, user input

[1660] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1661] Step 1:

[1662] The user enters the dimensions (length, width, height) and style (e.g., modern, classic) of the room into an input form on the device. The input data is formatted in JSON format.

[1663] Specific behavior: The user enters the following into a form on the browser: "Room length: 5 meters, width: 4 meters, height: 3 meters, style: modern." The device converts this data into JSON format ({ "length": 5, "width": 4, "height": 3, "style": "modern"}).

[1664] Input: User input of dimensions and styles

[1665] Output: Input information in JSON data format

[1666] Step 2:

[1667] The device sends the JSON data generated in step 1 to the server.

[1668] Specific behavior: The device sends JSON data to the server using an HTTP POST request.

[1669] Input: JSON data generated in step 1

[1670] Output: Send data to the server

[1671] Step 3:

[1672] The server receives and parses the JSON data.

[1673] What it does: The server parses the received JSON data and extracts the room's length, width, height, and style information.

[1674] Input: JSON data sent in step 2

[1675] Output: Parsed room information (length, width, height, style)

[1676] Step 4:

[1677] The server generates the optimal furniture layout based on the analyzed data.

[1678] How it works: The server uses an algorithm to calculate the placement of each piece of furniture and generate a layout, for example placing a sofa along the length of the room and a table in the center.

[1679] Input: Room information parsed in step 3

[1680] Output: Generated furniture layout information

[1681] Step 5:

[1682] The device captures the user's facial expressions and voice in real time and sends them to the emotion engine.

[1683] Specific operation: The device uses the camera and microphone to capture the user's facial expressions and voice, which are then analyzed by the emotion engine.

[1684] Input: Real-time captured facial expression and voice data

[1685] Output: Identified emotion information (e.g., joy, surprise)

[1686] Step 6:

[1687] The server adjusts the furniture layout and suggested furniture based on the analysis results from the emotion recognition means.

[1688] Specific behavior: The server adjusts the furniture arrangement and type based on the identified emotion (e.g., "joy"), for example, preferentially suggesting brightly colored furniture.

[1689] Input: Emotion information identified in step 5

[1690] Output: Adjusted furniture layout and suggested furniture information

[1691] Step 7:

[1692] The server uses the API of the online shopping platform to search for furniture information based on the adjusted layout information.

[1693] Specific operation: The server uses the API to obtain the furniture name, price, purchase link, etc. For example, search for "modern sofa" or "wooden table."

[1694] Input: Furniture layout information adjusted in step 6

[1695] Output: Retrieved furniture information (name, price, purchase link)

[1696] Step 8:

[1697] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal in JSON format.

[1698] Specific operation: The server integrates the layout information and furniture information, generates new JSON data, and sends it to the terminal.

[1699] Input: Furniture information obtained in step 7 and furniture layout information adjusted in step 6

[1700] Output: Consolidated JSON data

[1701] Step 9:

[1702] The device parses the received JSON data and displays it to the user in a visually easy-to-understand format.

[1703] Specific operation: The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links). The user can check the furniture layout and furniture information on the screen.

[1704] Input: JSON data sent in step 8

[1705] Output: Visually displayed furniture layout and furniture information

[1706] keyword

[1707] Generative AI model, prompt sentence

[1708] (Application example 2)

[1709] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1710] Conventional furniture layout generation systems simply propose optimal furniture layouts without considering the user's emotional state. This prevents flexible proposals based on the user's emotions and preferences, and fails to increase user satisfaction. Furthermore, there is a lack of systems that allow users to easily purchase the proposed furniture through online shopping. This makes the process of users finding and purchasing the furniture that best suits them cumbersome.

[1711] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for generating an optimal furniture layout based on the dimensions and style information of the user's room, means for searching for furniture information from an online shopping platform, means for displaying the acquired furniture information and furniture layout on the user terminal, means for capturing facial expressions and voice and identifying emotions, and means for adjusting the furniture layout and suggested furniture information based on the identified emotional information. This enables flexible furniture layout and suggestions based on the user's emotional state, providing a smooth purchasing process through online shopping.

[1712] "Input means" refers to a device or interface through which a user inputs room size and style information.

[1713] The "acquisition means" is a device or system having a function for acquiring and analyzing the room dimension and style information sent from the input means.

[1714] The "generator" is an algorithm or device that generates an optimal furniture layout based on the room dimensions and style information acquired by the acquirer.

[1715] The "search means" is a device or system having a function for searching furniture information from an online shopping platform based on the layout information generated by the generation means.

[1716] The "display means" refers to a device or software for displaying the acquired furniture information and furniture layout on a user terminal.

[1717] An "emotion recognition means" is a technology or device that captures a user's facial expressions and voice and identifies emotions from them.

[1718] The "adjustment means" is a device or system that has the function of correcting or optimizing the generated furniture layout or the proposed furniture information based on the emotion information identified by the emotion recognition means.

[1719] An "online shopping platform" is a website or application that allows users to search for, view, and purchase products over the Internet.

[1720] "Furniture layout" refers to the position information and layout diagram of furniture arranged based on the dimensions and style information of the room.

[1721] "Furniture information" refers to detailed information such as the name, price, size, and purchase link of the furniture obtained from the online shopping platform.

[1722] A "terminal" is an electronic device used by a user to enter data or display results, and includes smartphones, tablets, and personal computers.

[1723] The present invention is a system that generates an optimal furniture layout based on the dimensions and style information of a user's room, and suggests suitable furniture from an online shopping platform. It also has the ability to identify the user's emotional state and adjust the furniture layout and suggestions accordingly.

[1724] System configuration:

[1725] Input methods:

[1726] Users use devices such as smartphones, tablets, and computers to enter the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form.

[1727] Acquisition method:

[1728] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[1729] Generation means:

[1730] The server runs an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information, which includes calculating the placement of furniture.

[1731] Search by:

[1732] The server searches for furniture information from the online shopping platform based on the generated furniture layout information and obtains matching furniture information using an API.

[1733] Display means:

[1734] The server combines the acquired furniture information with the generated furniture layout information and sends it to the device as JSON format data. The device then analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[1735] Emotion recognition means:

[1736] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine, which identifies the user's emotions (e.g., joy, surprise, sadness, etc.).

[1737] Adjustment means:

[1738] The server adjusts the furniture layout to be generated and the type of furniture to be suggested based on the user's emotions identified by the emotion engine.

[1739] Hardware and software used:

[1740] Hardware: Smartphone, tablet, computer camera and microphone

[1741] Software: Emotion recognition engine (ai_emotion_recognition), furniture layout generation algorithm (furniture_layout_generator), online shopping search API (online_shopping_api)

[1742] Data processing and calculation details:

[1743] 1. The server receives and analyzes the room dimensions and style information sent from the terminal.

[1744] 2. The server runs an algorithm that generates the optimal furniture layout based on the analysis results.

[1745] 3. The server uses an API to obtain compatible furniture information from the online shopping platform based on the generated furniture layout information.

[1746] 4. The device captures the user's facial expression and voice data and uses an emotion recognition engine to identify emotions.

[1747] 5. The server adjusts the generated furniture layout and suggestions based on the analysis results of the emotion recognition engine.

[1748] Examples:

[1749] For example, if a user enters the following room information:

[1750] "My room measures 5 meters long, 4 meters wide, and 3 meters high. I want to fill it with modern-style furniture."

[1751] The system goes through the following steps:

[1752] 1. The user inputs the room dimensions and style.

[1753] 2. The terminal converts the input data into JSON format and sends it to the server.

[1754] 3. The server analyzes the received data and generates the optimal furniture layout.

[1755] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[1756] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[1757] 6. The device analyzes the received data and displays it to the user in a visually understandable format.

[1758] 7. The device analyzes the user's facial expressions and voice to recognize their emotions.

[1759] 8. The server adjusts the suggestions based on the perceived sentiment.

[1760] This allows users to find the best furniture arrangement and purchasing options based on their emotional state.

[1761] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1762] Step 1:

[1763] The user enters the dimensions (length, width, height) and style (modern, classic, etc.) of a room into an input form on the device. The input data is converted into JSON format. The input is information about the physical characteristics and design style of the room.

[1764] Step 2:

[1765] The device sends the user input data in JSON format to the server, which parses the data and extracts the room dimensions and style information. This step checks the consistency and completeness of the input data.

[1766] Step 3:

[1767] The server runs an algorithm to generate an optimal furniture layout based on the room dimensions and style information. The algorithm calculates the placement position of each piece of furniture and generates a furniture layout plan that matches the room dimensions. The output is layout information showing the placement positions of the furniture.

[1768] Step 4:

[1769] The server uses the API to search for furniture information from an online shopping platform based on the generated furniture layout information. The input is the generated layout information, and the output is the searched multiple furniture options (name, price, purchase link, etc.).

[1770] Step 5:

[1771] The server combines the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data. This process determines the furniture configuration to be proposed to the user.

[1772] Step 6:

[1773] The device receives and parses the JSON data sent from the server. After parsing, it displays a furniture layout diagram and furniture options (with names, prices, and purchase links) in a visually easy-to-understand format to the user. At this point, the user can review the proposed furniture.

[1774] Step 7:

[1775] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The input is the user's facial expressions and voice data, and the output is analyzed emotional information (e.g., joy, surprise, sadness, etc.).

[1776] Step 8:

[1777] The server adjusts the generated furniture layout and furniture suggestions based on the emotional information identified by the emotion engine. This adjustment determines the suggestions that are optimized for the user's emotional state. The final output is a furniture layout and furniture options that are adjusted based on the emotional information.

[1778] This clarifies the specific processing and operations of each step, making it possible to propose optimal furniture that takes into account the user's emotional state.

[1779] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1780] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1781] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1782] [Fourth embodiment]

[1783] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1784] 7, a 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.

[1785] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1786] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1787] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1788] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1789] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1790] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1791] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1792] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1793] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1794] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1795] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1796] The present invention provides a system that generates an optimal furniture layout based on the dimensions and style information of a user's room and suggests furniture that can be purchased at an affordable price from an online shopping platform. The system is mainly configured as follows.

[1797] System Configuration

[1798] 1. User input method

[1799] The user uses an input form provided on the terminal to input the dimensions (for example, length, width, height) and style (modern, classic, etc.) of the room.

[1800] 2. Acquisition method

[1801] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[1802] 3. Generation means

[1803] The server executes an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[1804] 4. Search Methods

[1805] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[1806] 5. Display means

[1807] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[1808] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[1809] Program processing overview

[1810] User Input

[1811] The user enters the room information (dimensions, style) into the terminal using the input form. The entered data is converted into JSON format and sent to the server.

[1812] Data reception and analysis

[1813] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[1814] Layout Generation

[1815] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (for example, placing the sofa at position X=1, Y=1).

[1816] Furniture Search

[1817] The server searches for furniture using the API of the online shopping platform based on the generated layout information, and obtains the name, price, and purchase link for each piece of furniture.

[1818] Consolidating and sending results

[1819] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[1820] Displaying the results

[1821] The device receives the data sent from the server, analyzes it, and then displays the results to the user in a visual format, providing the user with a furniture layout diagram and each furniture option (with name, price, and purchase link).

[1822] Specific examples

[1823] If a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[1824] 1. The user inputs the length, width, height and style of the room.

[1825] 2. The terminal converts the input data into JSON format and sends it to the server.

[1826] 3. The server analyzes the received data and generates the optimal furniture layout.

[1827] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[1828] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[1829] 6. The device analyzes the received data and displays the results visually to the user.

[1830] The system allows users to easily find the furniture layout that best suits their room and purchase that furniture at an affordable price.

[1831] The processing flow will be explained below.

[1832] Step 1:

[1833] The user inputs the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form on the terminal.

[1834] Step 2:

[1835] The terminal converts the user input data into JSON format.

[1836] example:

[1837] json

[1838] {

[1839] "length": 5,

[1840] "width": 4,

[1841] "height": 3,

[1842] "style": "modern"

[1843] }

[1844] Step 3:

[1845] The terminal sends the data converted into JSON format to the server via an HTTP request.

[1846] Step 4:

[1847] The server receives and analyzes the JSON data sent from the device.

[1848] Step 5:

[1849] The server runs an algorithm to generate the optimal furniture layout based on the received data, calculating the placement of each piece of furniture based on the room dimensions and style information.

[1850] example:

[1851] json

[1852] {

[1853] "sofa": {"x": 1, "y": 1},

[1854] "table": {"x": 2, "y": 2},

[1855] "bed": {"x": 3, "y": 3}

[1856] }

[1857] Step 6:

[1858] The server sends furniture search requests to the APIs of multiple online shopping platforms based on the generated layout information. It creates search queries that include the names and characteristics of the furniture.

[1859] example:

[1860] Example request:

[1861] json

[1862] {

[1863] "query": "modern sofa",

[1864] "max_price": 30000

[1865] }

[1866] Step 7:

[1867] The server receives and analyzes the API responses from each platform.

[1868] Step 8:

[1869] The server formats the acquired furniture information and integrates it with the generated furniture layout information.

[1870] example:

[1871] json

[1872] {

[1873] "layout": {

[1874] "sofa": {"x": 1, "y": 1},

[1875] "table": {"x": 2, "y": 2},

[1876] "bed": {"x": 3, "y": 3}

[1877] },

[1878] "furniture": [

[1879] {"name": "Modern sofa", "price": 20000, "url": "https: / / example.com / sofa"},

[1880] {"name": "Glass Table", "price": 15000, "url": "https: / / example.com / table"},

[1881] {"name": "Comfortable Bed", "price": 30000, "url": "https: / / example.com / bed"}

[1882] ]

[1883] }

[1884] Step 9:

[1885] The server sends the formatted data in JSON format to the terminal.

[1886] Step 10:

[1887] The terminal analyzes the received JSON data and displays it to the user in a visually easy-to-understand format.

[1888] Step 11:

[1889] The user checks the proposed furniture layout and purchase link on the terminal and purchases the furniture as necessary.

[1890] Example 1

[1891] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1892] Conventionally, it is very time-consuming and requires specialized knowledge for users to manually design the optimal furniture layout that matches the dimensions and style of the room and then search for the appropriate furniture. Therefore, there is a need for a system that can efficiently generate the optimal layout and allow users to easily select and purchase the appropriate furniture.

[1893] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1894] In this invention, the server includes a user input means, an acquisition means for acquiring room size and style information from the input means, a means for converting the acquired room size and style information into JSON format and transmitting the converted information to the server, a generation means for the server to generate an optimal furniture layout based on the acquired room size and style information, a search means for searching for furniture information from an API of an online shopping platform based on the layout information generated by the generation means, a acquisition means for acquiring the furniture information acquired by the search means, a means for integrating the acquired furniture information and the generated furniture layout and transmitting the combined data to a terminal in JSON format, and a display means for analyzing the data received by the terminal and displaying the combined data to the user in a visual format. This allows users to efficiently generate optimal furniture layouts and easily select and purchase appropriate furniture.

[1895] "User input means" is an interface provided on the terminal for the user to input room size and style information.

[1896] "Acquisition means" refers to the function that acquires room dimensions and style information from the user's input means and converts it into JSON format.

[1897] "JSON format" is a data structure in JavaScript Object Notation format, which is a method of expressing data in text format.

[1898] A "server" is a computer device that receives, analyzes, and processes data sent from an input means.

[1899] "Generator" refers to the functionality of the server that runs an algorithm to generate an optimal furniture layout based on room dimensions and style information.

[1900] The "search means" is a function for searching furniture information using the API of the online shopping platform based on the generated layout information.

[1901] An "online shopping platform" is a web service that provides product information and sells products via the Internet.

[1902] "API" stands for Application Programming Interface, and is an interface that allows software to provide and call functions to other software.

[1903] The "acquisition means" is a function that receives and processes furniture information acquired by the search means (used for a purpose different from the above-mentioned "acquisition means").

[1904] The "integration means" is a function that combines the generated furniture layout information and the acquired furniture information into a single data format (JSON format).

[1905] "Transmission means" refers to a function for transmitting the integrated data to the terminal.

[1906] The "analysis means" is a function that allows the terminal to process the JSON data received from the server and understand its structure.

[1907] "Display means" is a function of the terminal for visually presenting analyzed data to the user.

[1908] The present invention provides a system for generating an optimal furniture layout by a user inputting room dimensions and style information, and for suggesting affordable furniture from an online shopping platform based on the optimal furniture layout. The system includes the following means and processing steps:

[1909] System configuration

[1910] The system mainly consists of user input means, acquisition means, generation means, search means, integration means, transmission means, and display means. Specifically, the following hardware and software are used:

[1911] Hardware

[1912] User terminal: PC, tablet, smartphone, etc. Provides input and display means.

[1913] Server: A remotely located high-performance computer, cloud service, etc. that receives, analyzes, generates, searches, integrates, and transmits data.

[1914] software

[1915] Input Form: An HTML form that runs in a web browser, allowing users to enter room dimensions and style information.

[1916] JSON conversion library: A data format conversion library using JavaScript or other programming languages.

[1917] Server application: Implemented using Python's Flask framework, etc. Performs data analysis, layout generation, and API communication.

[1918] API: An API provided by an online shopping platform (e.g., Amazon) that acts as a search engine.

[1919] Presentation library: Visual presentation using HTML, CSS, and JavaScript.

[1920] Data processing and calculation

[1921] User Input

[1922] The user uses an input form on the terminal to input the dimensions of the room (e.g., 5 meters x 4 meters x 3 meters) and the style (e.g., modern), and the terminal acquires the input data.

[1923] Sending and Receiving Data

[1924] The device converts the acquired data into JSON format and sends it to the server. The server parses the received JSON data. For example, it receives data in the format {"length": 5, "width": 4, "height": 3, "style": "modern"}.

[1925] Generate layout

[1926] The server generates an optimal furniture layout based on the analyzed data. Specifically, a generation algorithm implemented in Python calculates the placement of each piece of furniture based on the room dimensions. For example, the sofa might be placed in the upper left corner of the room, and the table in the center.

[1927] Furniture Search

[1928] Based on the generated layout information, the server searches for furniture using the API of the online shopping platform, sending an HTTP request to the API endpoint to obtain the name, price, and purchase link of the appropriate furniture.

[1929] Consolidating and sending results

[1930] The server combines the acquired furniture information with the generated furniture layout information and sends it back to the device as JSON format data. For example, it generates data like this: {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}

[1931] Displaying the results

[1932] The device parses the JSON data received from the server and presents it visually to the user, for example, using HTML and JavaScript to display a furniture layout diagram and each furniture option (name, price, purchase link).

[1933] Specific examples

[1934] If a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[1935] 1. The user inputs the length, width, height, and style of the room.

[1936] 2. The device converts the input data into JSON format and sends it to the server. For example, it sends the following data: {"length": 5, "width": 4, "height": 3, "style": "modern"}.

[1937] 3. The server analyzes the received data and generates an optimal furniture layout, for example, placing the sofa at position X=1, Y=1.

[1938] 4. Based on the generated layout information, the server searches for furniture information from an online shopping platform through API, for example, searching for a modern-style sofa.

[1939] 5. The server combines the furniture information it has acquired with the generated layout information and sends it to the device as JSON data. For example, it generates the following data: {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}

[1940] 6. The device analyzes the received data and displays the results visually to the user, for example, using HTML and JavaScript to display a furniture layout diagram and a link to purchase.

[1941] Prompt Sentence Examples

[1942] "Based on the following information, design a program to generate a furniture layout diagram, search for suitable furniture from an online shopping platform based on this diagram, and provide its name, price, and purchase link."

[1943] Room dimensions: 5 meters long, 4 meters wide, 3 meters high

[1944] Style: Modern

[1945] Example output:

[1946] Layout diagram: Sofa placed at X=1, Y=1

[1947] Furniture information: Name: "Modern Sofa", Price: "199.99 USD", Purchase link: "http: / / example.com / sofa"

[1948] This invention allows users to easily understand the furniture layout that is suitable for their room and select and purchase that furniture at an affordable price.

[1949] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1950] Step 1:

[1951] The user uses the input form displayed on the device's web browser to input the dimensions (length, width, height) and style (modern, etc.) of the room. Specifically, the user enters numbers or text in each input field and presses the submit button. This acquires the input data.

[1952] Input: Room dimensions (length, width, height) and style information

[1953] Output: Input data (dimensions and style information)

[1954] Step 2:

[1955] The terminal converts the data entered by the user into JSON format. A JavaScript library (e.g., JSON.stringify()) is used to convert the data. After conversion, a JSON object such as {"length": 5, "width": 4, "height": 3, "style": "modern"} is generated.

[1956] Input: Data entered by the user

[1957] Output: JSON format data

[1958] Step 3:

[1959] The device sends the data converted to JSON format to the server as an HTTP POST request using an Ajax request or the fetch API.

[1960] Input: Data converted to JSON format

[1961] Output: Request sent to the server

[1962] Step 4:

[1963] The server parses the received JSON data. For example, using the Python Flask framework, the data is retrieved using the request.get_json() method. The parsed data is converted into an internal data structure (e.g., dictionary format).

[1964] Input: JSON data sent from the terminal

[1965] Output: Internal data structure (dictionary format)

[1966] Step 5:

[1967] The server then generates an optimal furniture layout based on the analyzed data, using a Python algorithm to calculate the position of each piece of furniture based on the room's dimensions and style information, such as placing a sofa in the upper left corner of the room and a table in the center.

[1968] Input: Room dimensions and style information

[1969] Output: Furniture layout information

[1970] Step 6:

[1971] The server searches for furniture using the API of an online shopping platform based on the generated furniture layout information, and sends an HTTP request to the API endpoint to obtain the name, price, and purchase link of each piece of furniture.

[1972] Input: Furniture layout information

[1973] Output: Furniture information (name, price, purchase link)

[1974] Step 7:

[1975] The server combines the generated layout information with the acquired furniture information and stores them in a single JSON format data, such as {"layout": [{"item": "sofa", "x": 1, "y": 1}], "furniture": [{"name": "Modern Sofa", "price": 199.99, "link": "http: / / example.com / sofa"}]}.

[1976] Input: Furniture layout information and acquired furniture information

[1977] Output: Consolidated JSON format data

[1978] Step 8:

[1979] The server sends the consolidated JSON format data to the terminal, which returns the data as an HTTP response.

[1980] Input: Consolidated JSON format data

[1981] Output: The response sent to the device

[1982] Step 9:

[1983] The device parses the received JSON data and converts it into an object using a JavaScript library (e.g., JSON.parse()). The parsed data is treated as an internal data structure.

[1984] Input: JSON data sent from the server

[1985] Output: Internal data structure (object format)

[1986] Step 10:

[1987] The device displays the visual results to the user based on the analyzed data. Using HTML and JavaScript, the layout diagram of the furniture and options for each piece of furniture (name, price, purchase link) are displayed on the screen. Specifically, the layout diagram is drawn using Canvas and SVG elements, and information about each piece of furniture is displayed as text elements.

[1988] Input: Internal data structure (object format)

[1989] Output: The visual result that is displayed to the user

[1990] (Application example 1)

[1991] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1992] Conventional furniture layout suggestion systems have the problem that even if users input the dimensions and style of a room, it is difficult to check in real time how the furniture will actually look. Also, even if furniture information is obtained from an online shopping platform, users cannot check the layout before purchasing, which can lead to problems such as the result being different from expectations after purchase.

[1993] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1994] In this invention, the server includes a user input means, an acquisition means, a generation means, a search means, an acquisition means, a display means, and a means for checking the furniture arrangement status in real time on a smart device, thereby enabling a user to generate an optimal furniture layout by inputting room dimensions and style information, and to decide on a purchase while checking furniture information suggested by the online shopping platform in real time.

[1995] "User input" is an interface through which a user inputs room size and style information.

[1996] The "acquisition means" is a means for transmitting the room size and style information input by the user to the server.

[1997] The "generator" is a means for executing an algorithm that generates an optimal furniture layout based on acquired room dimension and style information.

[1998] The "search means" is a means for searching furniture information from the online shopping platform based on the generated furniture layout information.

[1999] The "display means" is a means for visually presenting the acquired furniture information and the generated furniture layout on the user terminal.

[2000] "Means for checking the furniture arrangement status in real time on a smart device" refers to a means for visually checking the furniture arrangement status in a room in real time using a device such as a smartphone or smart glasses.

[2001] The present invention is a system that generates an optimal furniture layout based on room dimensions and style information and suggests furniture that can be purchased from an online shopping platform. The system includes user input means, acquisition means, generation means, search means, and display means, and further includes a means for checking the furniture arrangement status in real time using a smart device.

[2002] System Configuration

[2003] 1. User input method

[2004] The user uses an input form provided on the terminal to input the dimensions (e.g., length, width, height) and style (e.g., modern, classic) of the room.

[2005] 2. Acquisition method

[2006] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[2007] 3. Generation means

[2008] The server runs an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[2009] 4. Search Methods

[2010] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[2011] 5. Display means

[2012] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[2013] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[2014] 6. Real-time verification method

[2015] Users can use smart devices (e.g., smartphones, smart glasses) to check the furniture layout in real time in the actual room, allowing them to visually check the furniture layout and make adjustments as necessary.

[2016] Program processing overview

[2017] Data reception and analysis

[2018] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[2019] Layout Generation

[2020] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (e.g., placing the sofa at position X=1, Y=1).

[2021] Furniture Search

[2022] The server searches for furniture using the API of the online shopping platform based on the generated layout information, and obtains the name, price, and purchase link for each piece of furniture.

[2023] Consolidating and sending results

[2024] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[2025] Displaying the results

[2026] The device receives the data sent from the server, analyzes it, and then displays the results to the user in a visual format, providing the user with a furniture layout diagram and each furniture option (with name, price, and purchase link).

[2027] Real-time confirmation

[2028] The smart device displays the generated furniture layout in the actual room in real time, allowing the user to visually check the arrangement.

[2029] Specific examples

[2030] If the user inputs the room information as "length: 5m, width: 4m, height: 3m" and the style as "modern", the system will go through the following steps:

[2031] 1. The user inputs the dimensions and style of the room.

[2032] 2. The terminal converts the input data into JSON format and sends it to the server.

[2033] 3. The server analyzes the received data and generates the optimal furniture layout.

[2034] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[2035] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[2036] 6. The device analyzes the received data and displays the results visually to the user.

[2037] 7. The user can use their smart device to view the furniture arrangement in the room in real time.

[2038] Prompt Sentence Examples

[2039] "Generate the optimal furniture layout based on the room information entered by the user, 'Dimensions: 5m x 4m x 3m, Style: Modern', and retrieve and integrate furniture information (name, price, purchase link) available for purchase from online stores."

[2040] This system allows users to easily determine the furniture layout that best suits their room and visually check the layout before making an online purchase, thereby reducing the gap between expectations and reality after purchase and providing a more satisfying shopping experience.

[2041] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2042] Step 1:

[2043] The user enters the room dimensions (e.g., length, width, height) and style information (e.g., modern, classic) using an input form provided on the device. The input form can be accessed through a web browser or a mobile application.

[2044] Input: Room dimensions and style information

[2045] Output: A data object based on the user's input

[2046] Step 2:

[2047] The device converts the input room dimensions and style information into JSON format data and sends this data to the server. The conversion is performed using a front-end script (e.g., JavaScript).

[2048] Input: User-entered room dimensions and style information

[2049] Output: JSON format data

[2050] Specific operation: Converting data format and sending an HTTP request to the server

[2051] Step 3:

[2052] The server receives the JSON data sent from the device and parses it using a server-side script (e.g., Python, Flask).

[2053] Input: JSON data sent from the terminal

[2054] Output: Parsed room dimensions and style information

[2055] Specific operation: Parsing and extracting JSON data

[2056] Step 4:

[2057] The server runs an algorithm to generate an optimal furniture layout based on the analyzed room dimensions and style information. The algorithm takes the room dimensions as input and calculates the optimal placement of each piece of furniture.

[2058] Input: Parsed room dimensions and style information

[2059] Output: Optimal furniture layout information (e.g. furniture name and placement position)

[2060] Specific operation: Execution of layout generation algorithm

[2061] Step 5:

[2062] The server searches for furniture information using the API of the online shopping platform based on the generated furniture layout information, sending an API request to obtain the name, price, purchase link, etc. of the relevant furniture.

[2063] Input: Optimal furniture layout information

[2064] Output: Retrieved furniture information

[2065] Specific behavior: Generating API requests and parsing responses

[2066] Step 6:

[2067] The server integrates the generated furniture layout information with the acquired furniture information and sends it back to the terminal as JSON format data. The integration process is performed by a server-side script (e.g., Python).

[2068] Input: Optimal furniture layout information and retrieved furniture information

[2069] Output: Consolidated JSON data

[2070] Specific behavior: Data merging and format conversion

[2071] Step 7:

[2072] The device receives the aggregated data sent from the server and displays the results to the user in a visual format, including a furniture layout diagram of the room and each furniture option with its name, price, and a purchase link.

[2073] Input: Aggregated data sent from the server

[2074] Output: Visual display results

[2075] Specific behavior: Analyzing data and displaying it in the interface

[2076] Step 8:

[2077] Users can use smart devices (e.g., smartphones, smart glasses) to check the furniture arrangement in a room in real time. This function is realized using Augmented Reality (AR) technology.

[2078] Input: Room dimensions, style information, and generated furniture layout

[2079] Output: Real-time display of furniture layout

[2080] Specific operation: Displaying furniture in real space using AR technology

[2081] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2082] The present invention combines a system that generates an optimal furniture layout based on the dimensions and style information of a user's room and suggests furniture that can be purchased at an affordable price from an online shopping platform with an emotion engine that recognizes the user's emotions. Each component of the system and its operation will be described in detail below.

[2083] System Configuration

[2084] 1. User input method

[2085] The user uses an input form on the terminal to input the room dimensions (length, width, height) and style (modern, classic, etc.).

[2086] 2. Acquisition method

[2087] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[2088] 3. Generation means

[2089] The server executes an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[2090] 4. Search Methods

[2091] The server searches for furniture on an online shopping platform (e.g., a shopping site) based on the generated furniture layout information and obtains matching furniture information using an API.

[2092] 5. Display means

[2093] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[2094] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[2095] 6. Emotion Engine

[2096] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[2097] The server adjusts the furniture layout to be generated and the type of furniture to be suggested based on the user's emotions identified by the emotion engine.

[2098] Program processing overview

[2099] User Input

[2100] The user enters the room information (dimensions, style) into the terminal using the input form. The entered data is converted into JSON format and sent to the server.

[2101] Data reception and analysis

[2102] The terminal sends the JSON data entered by the user to the server, which receives and analyzes it.

[2103] Layout Generation

[2104] The server generates an optimal furniture layout based on the received data, calculating the placement position of each piece of furniture (for example, placing the sofa at position X=1, Y=1).

[2105] Emotion Recognition and Analysis

[2106] The device analyzes the user's facial expressions and voice using an emotion engine to identify the user's emotions.

[2107] Furniture Search

[2108] The server searches for furniture using the API of the online shopping platform based on the generated layout information, obtains the name, price, and purchase link for each piece of furniture, and adjusts the suggestions based on the user's sentiment.

[2109] Consolidating and sending results

[2110] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal as JSON format data.

[2111] Displaying the results

[2112] The device receives the JSON data sent from the server, analyzes it, and displays it to the user in a visually easy-to-understand format, providing the user with a furniture layout diagram and options for each piece of furniture (with name, price, and purchase link).

[2113] Specific examples

[2114] For example, if a user inputs information about a 5m x 4m x 3m room that they want to fill with modern style furniture, the system will go through the following steps:

[2115] 1. The user inputs the length, width, height and style of the room.

[2116] 2. The terminal converts the input data into JSON format and sends it to the server.

[2117] 3. The server analyzes the received data and generates the optimal furniture layout.

[2118] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[2119] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[2120] 6. The terminal analyzes the received data and displays it to the user in a visually easy-to-understand format.

[2121] 7. The device analyzes the user's facial expressions and voice to recognize their emotions.

[2122] 8. The server adjusts the suggestions based on the perceived sentiment.

[2123] 9. The user checks the proposed furniture layout and purchase link on the device and purchases the furniture if necessary.

[2124] The system allows users to find optimal furniture placement and purchasing options based on their emotional state.

[2125] The processing flow will be explained below.

[2126] Step 1:

[2127] The user inputs the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form on the terminal.

[2128] Step 2:

[2129] The terminal converts the user input data into JSON format.

[2130] example:

[2131] json

[2132] {

[2133] "length": 5,

[2134] "width": 4,

[2135] "height": 3,

[2136] "style": "modern"

[2137] }

[2138] Step 3:

[2139] The terminal sends the data converted into JSON format to the server via an HTTP request.

[2140] Step 4:

[2141] The server receives and analyzes the JSON data sent from the device.

[2142] Step 5:

[2143] The server runs an algorithm to generate the optimal furniture layout based on the received data, calculating the placement of each piece of furniture based on the room dimensions and style information.

[2144] example:

[2145] json

[2146] {

[2147] "sofa": {"x": 1, "y": 1},

[2148] "table": {"x": 2, "y": 2},

[2149] "bed": {"x": 3, "y": 3}

[2150] }

[2151] Step 6:

[2152] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[2153] example:

[2154] Emotion engine result: "happy"

[2155] Step 7:

[2156] The server receives emotion data from the emotion engine and adjusts the furniture layout to suit the user's needs. For example, if the user feels sad, the server will suggest brightly colored furniture.

[2157] Step 8:

[2158] The server sends furniture search requests to the APIs of multiple online shopping platforms based on the generated layout information. It creates search queries that include the names and characteristics of the furniture.

[2159] example:

[2160] Example request:

[2161] json

[2162] {

[2163] "query": "modern sofa",

[2164] "max_price": 30000

[2165] }

[2166] Step 9:

[2167] The server receives and analyzes the API responses from each platform.

[2168] Step 10:

[2169] The server formats the acquired furniture information and integrates it with the generated furniture layout information.

[2170] example:

[2171] json

[2172] {

[2173] "layout": {

[2174] "sofa": {"x": 1, "y": 1},

[2175] "table": {"x": 2, "y": 2},

[2176] "bed": {"x": 3, "y": 3}

[2177] },

[2178] "furniture": [

[2179] {"name": "Modern sofa", "price": 20000, "url": "https: / / example.com / sofa"},

[2180] {"name": "Glass Table", "price": 15000, "url": "https: / / example.com / table"},

[2181] {"name": "Comfortable Bed", "price": 30000, "url": "https: / / example.com / bed"}

[2182] ]

[2183] }

[2184] Step 11:

[2185] The server sends the formatted data in JSON format to the terminal.

[2186] Step 12:

[2187] The device parses the received JSON data and displays it to the user in a visually easy-to-understand format, providing the user with a furniture layout diagram and options for each piece of furniture (with name, price, and purchase link).

[2188] Step 13:

[2189] The user checks the proposed furniture layout and purchase link on the terminal and purchases the furniture as necessary.

[2190] Example 2

[2191] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2192] Conventional furniture layout suggestion systems simply provide optimal layouts based on the dimensions and style of a room, but lack the ability to adjust the suggestions based on the user's emotional state. As a result, users often feel dissatisfied with the proposed furniture layout. To solve this problem, a system is needed that can suggest furniture and layouts that reflect the user's emotional state.

[2193] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user input means, an acquisition means for acquiring room dimension and style information from the input means, a generation means for generating an optimal furniture layout based on the room dimension and style information acquired by the acquisition means, a search means for searching for furniture information from an online shopping platform based on the layout information generated by the generation means, an acquisition means for acquiring the furniture information acquired by the search means, a display means for displaying the furniture information and furniture layout acquired by the acquisition means on the user terminal, an emotion recognition means for the terminal to recognize the user's emotion in real time, and an adjustment means for adjusting the generated furniture layout or the proposed furniture based on the emotion recognized by the emotion recognition means. This makes it possible to propose an optimal furniture layout and furniture that reflects the user's emotional state.

[2194] A "user input means" is a device that provides an interface for a user to input room dimensions and style information.

[2195] The "acquisition means" is a method or device for collecting data obtained from the user's input means and proceeding to the next step.

[2196] The "generation means" refers to an algorithm or program that calculates and generates an optimal furniture layout based on the data obtained by the acquisition means.

[2197] The "search means" refers to a method or device for searching for furniture information on the online shopping platform based on the layout information generated by the generation means.

[2198] The "display means" is a method or device for visually displaying the furniture information collected by the acquisition means and the furniture layout information generated on the user terminal.

[2199] An "emotion recognition means" is a method or equipment for capturing a user's facial expressions and voice in real time and analyzing them to identify the user's emotions.

[2200] The "adjustment means" is a method or apparatus that adjusts the generated furniture layout or suggested furniture based on the user's emotions identified by the emotion recognition means.

[2201] The present invention combines a system that generates an optimal furniture layout based on the user's room dimensions and style information and suggests furniture that can be purchased at an affordable price from an online shopping platform with an emotion engine that recognizes the user's emotions.

[2202] System Configuration

[2203] 1. User input method

[2204] The user uses an input form on the terminal to input the room dimensions (length, width, height) and style (e.g., modern, classic).

[2205] 2. Acquisition method

[2206] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[2207] 3. Generation means

[2208] The server executes an algorithm for generating an optimal furniture layout based on the room dimensions and style information acquired by the acquisition means. The algorithm calculates the placement of furniture according to the room dimensions and determines the placement position of each piece of furniture.

[2209] 4. Search Methods

[2210] The server searches for furniture on the online shopping platform based on the generated furniture layout information and obtains matching furniture information using an API.

[2211] 5. Display means

[2212] The server integrates the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data.

[2213] The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[2214] 6. Emotion recognition means

[2215] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The analysis results identify the user's emotions (e.g., joy, surprise, sadness, etc.).

[2216] 7. Adjustment means

[2217] The server adjusts the furniture layout to be generated and the type of furniture to be proposed based on the user's emotion identified by the emotion recognition means.

[2218] System Operation Overview

[2219] User Input

[2220] The user inputs the dimensions and style of the room into a form on the browser. For example, the user inputs "room length: 5 meters, width: 4 meters, height: 3 meters, style: modern."

[2221] Data reception and analysis

[2222] The terminal converts the data entered by the user into JSON format and sends it to the server, which receives and analyzes the data.

[2223] Layout Generation

[2224] The server generates the optimal furniture layout based on the analyzed data. For example, the server calculates a specific layout such as "placing the sofa longitudinally and placing the table in the center."

[2225] Emotion Recognition and Analysis

[2226] The device uses a camera and microphone to capture the user's facial expressions and voice in real time, and analyzes them with an emotion engine. As a result, emotions such as "joy" are identified.

[2227] Furniture Search

[2228] Based on the optimal furniture layout, the server retrieves matching furniture information from online shopping platforms, such as a modern sofa or a wooden table, via API, and obtains the name, price, and purchase link.

[2229] Consolidating and sending results

[2230] The server combines the generated layout information and the acquired furniture information and sends it to the device as new JSON data. The device then analyzes the received data and visually displays a furniture layout diagram and furniture options.

[2231] Specific examples

[2232] For example, if a user enters the dimensions of a room as "5m x 4m x 3m" and the style as "Modern," the system will perform the following steps:

[2233] 1. The user inputs the dimensions and style of the room.

[2234] 2. The terminal converts the input data into JSON format and sends it to the server.

[2235] 3. The server receives and analyzes the data.

[2236] 4. The server generates the optimal furniture layout.

[2237] 5. The device recognizes the user's emotions and sends the analysis results to the server.

[2238] 6. Based on the generated layout information, the server searches for furniture information from the online shopping platform via API.

[2239] 7. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal.

[2240] 8. The device analyzes the received data and displays it to the user in a visually understandable format.

[2241] Examples of prompt statements

[2242] Examples of prompts to be input to a generative AI model include:

[2243] "Suggest the best furniture layout based on the room dimensions and style, and adjust it according to the user's emotions. Room information is: Length: 5 meters, Width: 4 meters, Height: 3 meters, Style: Modern. User's emotions: Joy."

[2244] keyword

[2245] Generative AI model, prompt sentence, furniture layout, emotion engine, online shopping platform, room dimensions, room style, furniture suggestions, user input

[2246] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2247] Step 1:

[2248] The user enters the dimensions (length, width, height) and style (e.g., modern, classic) of the room into an input form on the device. The input data is formatted in JSON format.

[2249] Specific behavior: The user enters the following into a form on the browser: "Room length: 5 meters, width: 4 meters, height: 3 meters, style: modern." The device converts this data into JSON format ({ "length": 5, "width": 4, "height": 3, "style": "modern"}).

[2250] Input: User input of dimensions and styles

[2251] Output: Input information in JSON data format

[2252] Step 2:

[2253] The device sends the JSON data generated in step 1 to the server.

[2254] Specific behavior: The device sends JSON data to the server using an HTTP POST request.

[2255] Input: JSON data generated in step 1

[2256] Output: Send data to the server

[2257] Step 3:

[2258] The server receives and parses the JSON data.

[2259] What it does: The server parses the received JSON data and extracts the room's length, width, height, and style information.

[2260] Input: JSON data sent in step 2

[2261] Output: Parsed room information (length, width, height, style)

[2262] Step 4:

[2263] The server generates the optimal furniture layout based on the analyzed data.

[2264] How it works: The server uses an algorithm to calculate the placement of each piece of furniture and generate a layout, for example placing a sofa along the length of the room and a table in the center.

[2265] Input: Room information parsed in step 3

[2266] Output: Generated furniture layout information

[2267] Step 5:

[2268] The device captures the user's facial expressions and voice in real time and sends them to the emotion engine.

[2269] Specific operation: The device uses the camera and microphone to capture the user's facial expressions and voice, which are then analyzed by the emotion engine.

[2270] Input: Real-time captured facial expression and voice data

[2271] Output: Identified emotion information (e.g., joy, surprise)

[2272] Step 6:

[2273] The server adjusts the furniture layout and suggested furniture based on the analysis results from the emotion recognition means.

[2274] Specific behavior: The server adjusts the furniture arrangement and type based on the identified emotion (e.g., "joy"), for example, preferentially suggesting brightly colored furniture.

[2275] Input: Emotion information identified in step 5

[2276] Output: Adjusted furniture layout and suggested furniture information

[2277] Step 7:

[2278] The server uses the API of the online shopping platform to search for furniture information based on the adjusted layout information.

[2279] Specific operation: The server uses the API to obtain the furniture name, price, purchase link, etc. For example, search for "modern sofa" or "wooden table."

[2280] Input: Furniture layout information adjusted in step 6

[2281] Output: Retrieved furniture information (name, price, purchase link)

[2282] Step 8:

[2283] The server integrates the generated layout information and the acquired furniture information and sends it to the terminal in JSON format.

[2284] Specific operation: The server integrates the layout information and furniture information, generates new JSON data, and sends it to the terminal.

[2285] Input: Furniture information obtained in step 7 and furniture layout information adjusted in step 6

[2286] Output: Consolidated JSON data

[2287] Step 9:

[2288] The device parses the received JSON data and displays it to the user in a visually easy-to-understand format.

[2289] Specific operation: The device analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links). The user can check the furniture layout and furniture information on the screen.

[2290] Input: JSON data sent in step 8

[2291] Output: Visually displayed furniture layout and furniture information

[2292] keyword

[2293] Generative AI model, prompt sentence

[2294] (Application example 2)

[2295] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2296] Conventional furniture layout generation systems simply propose optimal furniture layouts without considering the user's emotional state. This prevents flexible proposals based on the user's emotions and preferences, and fails to increase user satisfaction. Furthermore, there is a lack of systems that allow users to easily purchase the proposed furniture through online shopping. This makes the process of users finding and purchasing the furniture that best suits them cumbersome.

[2297] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for generating an optimal furniture layout based on the dimensions and style information of the user's room, means for searching for furniture information from an online shopping platform, means for displaying the acquired furniture information and furniture layout on the user terminal, means for capturing facial expressions and voice and identifying emotions, and means for adjusting the furniture layout and suggested furniture information based on the identified emotional information. This enables flexible furniture layout and suggestions based on the user's emotional state, providing a smooth purchasing process through online shopping.

[2298] "Input means" refers to a device or interface through which a user inputs room size and style information.

[2299] The "acquisition means" is a device or system having a function for acquiring and analyzing the room dimension and style information sent from the input means.

[2300] The "generator" is an algorithm or device that generates an optimal furniture layout based on the room dimensions and style information acquired by the acquirer.

[2301] The "search means" is a device or system having a function for searching furniture information from an online shopping platform based on the layout information generated by the generation means.

[2302] The "display means" refers to a device or software for displaying the acquired furniture information and furniture layout on a user terminal.

[2303] An "emotion recognition means" is a technology or device that captures a user's facial expressions and voice and identifies emotions from them.

[2304] The "adjustment means" is a device or system that has the function of correcting or optimizing the generated furniture layout or the proposed furniture information based on the emotion information identified by the emotion recognition means.

[2305] An "online shopping platform" is a website or application that allows users to search for, view, and purchase products over the Internet.

[2306] "Furniture layout" refers to the position information and layout diagram of furniture arranged based on the dimensions and style information of the room.

[2307] "Furniture information" refers to detailed information such as the name, price, size, and purchase link of the furniture obtained from the online shopping platform.

[2308] A "terminal" is an electronic device used by a user to enter data or display results, and includes smartphones, tablets, and personal computers.

[2309] The present invention is a system that generates an optimal furniture layout based on the dimensions and style information of a user's room, and suggests suitable furniture from an online shopping platform. It also has the ability to identify the user's emotional state and adjust the furniture layout and suggestions accordingly.

[2310] System configuration:

[2311] Input methods:

[2312] Users use devices such as smartphones, tablets, and computers to enter the room dimensions (length, width, height) and style (modern, classic, etc.) into an input form.

[2313] Acquisition method:

[2314] The terminal converts the data entered by the user into JSON format and sends this data to the server.

[2315] Generation means:

[2316] The server runs an algorithm to generate an optimal furniture layout based on the acquired room dimensions and style information, which includes calculating the placement of furniture.

[2317] Search by:

[2318] The server searches for furniture information from the online shopping platform based on the generated furniture layout information and obtains matching furniture information using an API.

[2319] Display means:

[2320] The server combines the acquired furniture information with the generated furniture layout information and sends it to the device as JSON format data. The device then analyzes the received data and displays a furniture layout diagram and furniture options (with names, prices, and purchase links) to the user.

[2321] Emotion recognition means:

[2322] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine, which identifies the user's emotions (e.g., joy, surprise, sadness, etc.).

[2323] Adjustment means:

[2324] The server adjusts the furniture layout to be generated and the type of furniture to be suggested based on the user's emotions identified by the emotion engine.

[2325] Hardware and software used:

[2326] Hardware: Smartphone, tablet, computer camera and microphone

[2327] Software: Emotion recognition engine (ai_emotion_recognition), furniture layout generation algorithm (furniture_layout_generator), online shopping search API (online_shopping_api)

[2328] Data processing and calculation details:

[2329] 1. The server receives and analyzes the room dimensions and style information sent from the terminal.

[2330] 2. The server runs an algorithm that generates the optimal furniture layout based on the analysis results.

[2331] 3. The server uses an API to obtain compatible furniture information from the online shopping platform based on the generated furniture layout information.

[2332] 4. The device captures the user's facial expression and voice data and uses an emotion recognition engine to identify emotions.

[2333] 5. The server adjusts the generated furniture layout and suggestions based on the analysis results of the emotion recognition engine.

[2334] Examples:

[2335] For example, if a user enters the following room information:

[2336] "My room measures 5 meters long, 4 meters wide, and 3 meters high. I want to fill it with modern-style furniture."

[2337] The system goes through the following steps:

[2338] 1. The user inputs the room dimensions and style.

[2339] 2. The terminal converts the input data into JSON format and sends it to the server.

[2340] 3. The server analyzes the received data and generates the optimal furniture layout.

[2341] 4. The server searches for furniture information from the online shopping platform through API based on the generated layout information.

[2342] 5. The server integrates the acquired furniture information with the generated layout information and sends it to the terminal as JSON format data.

[2343] 6. The device analyzes the received data and displays it to the user in a visually understandable format.

[2344] 7. The device analyzes the user's facial expressions and voice to recognize their emotions.

[2345] 8. The server adjusts the suggestions based on the perceived sentiment.

[2346] This allows users to find the best furniture arrangement and purchasing options based on their emotional state.

[2347] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2348] Step 1:

[2349] The user enters the dimensions (length, width, height) and style (modern, classic, etc.) of a room into an input form on the device. The input data is converted into JSON format. The input is information about the physical characteristics and design style of the room.

[2350] Step 2:

[2351] The device sends the user input data in JSON format to the server, which parses the data and extracts the room dimensions and style information. This step checks the consistency and completeness of the input data.

[2352] Step 3:

[2353] The server runs an algorithm to generate an optimal furniture layout based on the room dimensions and style information. The algorithm calculates the placement position of each piece of furniture and generates a furniture layout plan that matches the room dimensions. The output is layout information showing the placement positions of the furniture.

[2354] Step 4:

[2355] The server uses the API to search for furniture information from an online shopping platform based on the generated furniture layout information. The input is the generated layout information, and the output is the searched multiple furniture options (name, price, purchase link, etc.).

[2356] Step 5:

[2357] The server combines the acquired furniture information with the generated furniture layout information and sends it to the terminal as JSON format data. This process determines the furniture configuration to be proposed to the user.

[2358] Step 6:

[2359] The device receives and parses the JSON data sent from the server. After parsing, it displays a furniture layout diagram and furniture options (with names, prices, and purchase links) in a visually easy-to-understand format to the user. At this point, the user can review the proposed furniture.

[2360] Step 7:

[2361] The device captures the user's facial expressions and voice in real time and analyzes them with an emotion engine. The input is the user's facial expressions and voice data, and the output is analyzed emotional information (e.g., joy, surprise, sadness, etc.).

[2362] Step 8:

[2363] The server adjusts the generated furniture layout and furniture suggestions based on the emotional information identified by the emotion engine. This adjustment determines the suggestions that are optimized for the user's emotional state. The final output is a furniture layout and furniture options that are adjusted based on the emotional information.

[2364] This clarifies the specific processing and operations of each step, making it possible to propose optimal furniture that takes into account the user's emotional state.

[2365] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2366] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2367] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2368] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2369] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2370] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2371] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2372] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2373] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2374] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2375] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2376] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2377] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2378] 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.

[2379] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2380] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2381] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[2382] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2383] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2384] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2385] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2386] The following is further disclosed regarding the above embodiment.

[2387] (Claim 1)

[2388] A user input means;

[2389] an acquisition means for acquiring room size and style information from the input means;

[2390] a generating means for generating an optimal furniture layout based on the room size and style information acquired by the acquiring means;

[2391] a search means for searching for furniture information from an online shopping platform based on the layout information generated by the generation means;

[2392] an acquisition means for acquiring the furniture information ac...

Claims

1. A user input means; an acquisition means for acquiring room size and style information from the input means; a generating means for generating an optimal furniture layout based on the room size and style information acquired by the acquiring means; a search means for searching for furniture information from an online shopping platform based on the layout information generated by the generation means; an acquisition means for acquiring the furniture information acquired by the search means; a display means for displaying the furniture information and furniture layout acquired by the acquisition means on a user terminal; A system including:

2. 2. The system of claim 1, wherein said generating means comprises means for calculating a placement position for each piece of furniture based on room size and style information.

3. 2. The system of claim 1, wherein the searching means comprises means for searching furniture information from a plurality of online shopping platforms.

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