System

Abstract

To provide a system.SOLUTION: A system includes means for presenting a plurality of room layout simulations by selecting lot size and orientation, required facilities, design conditions, and tolerance of the design conditions, means for pre-inserting conditions in accordance with building laws, means for recognizing user's feelings, means for analyzing a feedback from the user, and means for adjusting the room layout simulations on the basis of at least either one of the recognized user feelings or the analyzed feedback.SELECTED DRAWING: Figure 1

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] In the traditional design process, architects typically manually draft plans and present three-dimensional floor plans to clients. However, this process takes time and effort, and it is difficult to present a floor plan that perfectly matches the client's needs. Furthermore, building regulations must also be taken into consideration, placing a significant burden on architects. [Means for solving the problem]

[0005] This invention provides a means for designers to use in drafting plans to show customers three-dimensional floor plan proposals, a means for presenting multiple floor plan simulations by selecting the land size and orientation, necessary facilities, and other conditions and their tolerance levels, and a means for pre-entering conditions in accordance with building regulations. Furthermore, it provides a means for selecting only from "reference knowledge" provided by manufacturers of wall and flooring materials, and then using image generation AI to generate not only the floor plan but also fixtures and interiors that match the image. This reduces the burden on designers and enables them to efficiently present floor plan proposals that more precisely meet customer requests. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The system of the present invention is used by architects to create draft plans. Specifically, the architect inputs the size and orientation of the land, the necessary facilities, and other conditions and tolerances for those conditions into the system. Based on this information, the system automatically generates multiple floor plan simulations and presents them to the architect. This allows the architect to efficiently show the client three-dimensional floor plan proposals.

[0029] "Example 2"

[0030] Furthermore, the system of this invention has the ability to select only from "reference knowledge" prepared by manufacturers of wall and flooring materials. Designers can use this function to select not only the floor plan but also fixtures and interiors that fit their image. The selected fixtures and interiors are generated by image generation AI and presented to the designer. This allows the designer to provide a floor plan proposal that more precisely meets the customer's requests.

[0031] "Example 3"

[0032] The system of the present invention also has the ability to pre-load conditions that comply with building laws. Specifically, the system stores legal information such as building laws and local government ordinances in a database, and takes this legal information into account when generating floor plan simulations. This makes it possible to generate floor plan proposals that do not violate laws.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The architect inputs the size and orientation of the land, the necessary facilities, and other conditions and tolerances for the conditions into the system.

[0036] Step 2: Based on this information, the system automatically generates multiple floor plan simulations.

[0037] Step 3: The generated floor plan simulation is presented to the architect, who then uses it to present a three-dimensional floor plan proposal to the client.

[0038] "Example 2"

[0039] Step 1: The designer uses the system's "reference knowledge" function to select wall and floor materials.

[0040] Step 2: The selected features and interior are generated using image generation AI.

[0041] Step 3: The generated images of fixtures and interiors are presented to the architect, who then uses them to present a floor plan to the client.

[0042] "Example 3"

[0043] Step 1: The system maintains legal information such as building codes and local government ordinances in a database.

[0044] Step 2: The system takes this legal information into account when generating the simulated floor plan.

[0045] Step 3: This makes it possible to generate floor plan proposals that do not violate any laws.

[0046] Example 1

[0047] Next, a description will be given of Example 1 of Form 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."

[0048] Previous systems used by architects to draft plans had limited means of showing floor plan proposals in three dimensions, making it difficult to efficiently propose them to clients. Furthermore, even if the land size, orientation, necessary facilities, and other conditions and their tolerances were input, the system lacked the functionality to automatically generate multiple floor plan simulations. Furthermore, there were insufficient means to consider conditions in accordance with building laws in advance, placing a heavy burden on architects.

[0049] 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. In this invention, the server includes a means for receiving input data and performing preprocessing, a means for inputting a prompt sentence to the generation AI model and generating a floor plan simulation, and a means for visualizing the generated floor plan simulation. This allows the architect to efficiently generate multiple floor plan simulations and propose them to the customer in three dimensions. In addition, by taking into account the conditions in accordance with building laws in advance, the burden on the architect can be reduced.

[0050] An "architect" is an engineer who specializes in designing buildings.

[0051] "Drafting a plan" is the initial stage of creating a basic design for a building.

[0052] The "customer" is the client who requests the architect to design a building.

[0053] A "three-dimensional floor plan" is a blueprint that represents the floor plan of a building in three dimensions.

[0054] "Land size" refers to the area of ​​land available for building a structure.

[0055] "Land orientation" refers to the direction of the land on which a building is to be constructed.

[0056] "Necessary facilities" are facilities and equipment that must be installed in a building.

[0057] "Other conditions" are additional requirements or constraints that must be taken into account in the design of a building.

[0058] "Condition tolerance" refers to the degree to which conditions are applied flexibly in the design.

[0059] "Floor plan simulation" is the process of virtually calculating and verifying the floor plan of a building.

[0060] "Building laws" are legal regulations and standards governing the design and construction of buildings.

[0061] "Input data" is information provided by a user to a system.

[0062] "Preprocessing" is the process of analyzing input data and converting it into a format suitable for subsequent processing.

[0063] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate data.

[0064] A "prompt sentence" is an instruction sentence input to a generative AI model.

[0065] "Visualization" is the process of representing data or information visually.

[0066] "User" refers to the designers and other users of this system.

[0067] This invention is a system that allows architects to create draft plans and show three-dimensional floor plan proposals to clients. The system automatically generates multiple floor plan simulations and presents them to architects by inputting the land size and orientation, necessary facilities, and other conditions and tolerances for those conditions.

[0068] The user (architect) first uses a device (PC or tablet) to input the land size, orientation, required facilities, other conditions, and their tolerance levels. For example, the user might input "Land size: 200 square meters," "Land orientation: south-facing," "Required facilities: 3LDK, 2 parking spaces, garden," "Other conditions: barrier-free," and "Condition tolerance level: high."

[0069] The terminal sends the data entered by the user to the server. Specifically, the terminal converts the input data into JSON format and sends it to the server using an HTTP request. The server receives the data sent from the terminal and performs preprocessing. Preprocessing involves formatting the data and removing unnecessary information.

[0070] The server generates a prompt based on the preprocessed data and inputs it into a generative AI model (for example, a general-purpose generative AI model). An example of a prompt might be, "Please propose a floor plan for a 200-square-meter plot of land facing south, with 3 bedrooms, a living room, kitchen, kitchen, and kitchen, two parking spaces, and a garden. The conditions are highly tolerant." The generative AI model generates multiple floor plan simulations based on this prompt.

[0071] The server inputs the floor plan simulation obtained from the generative AI model into 3D modeling software (e.g., general-purpose 3D modeling software) and visualizes it. This displays the proposed floor plan in three dimensions. The visualized data is generated as an image file or 3D model file and sent to the terminal as an HTTP response.

[0072] The device displays the visualized data received from the server to the user, who can then check multiple floor plan proposals on the device screen and efficiently propose them to the customer.

[0073] This system allows designers to efficiently generate multiple floor plan simulations and propose them to customers in three dimensions. It also reduces the burden on designers by taking into account building regulations in advance.

[0074] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0075] Step 1:

[0076] The user inputs the input data into the terminal. The user inputs the land size, orientation, required facilities, other conditions, and their tolerance levels into the terminal. For example, the user might input "Land size: 200 square meters," "Land orientation: south-facing," "Required facilities: 3LDK, 2 parking spaces, garden," "Other conditions: barrier-free," and "Condition tolerance level: high." The input data is collected through an input form on the terminal.

[0077] Step 2:

[0078] The terminal sends the input data to the server. The terminal converts the data entered by the user into JSON format and sends it to the server using an HTTP request. The input data is sent to the server as a JSON object containing the land size, orientation, required facilities, other conditions, and their tolerances.

[0079] Step 3:

[0080] The server receives the data and performs preprocessing. The server receives the JSON data sent from the device and formats the data and removes unnecessary information. For example, it checks the format of the input data and whether any information is missing. The preprocessed data is converted into a format suitable for the generative AI model.

[0081] Step 4:

[0082] The server inputs a prompt statement into the generative AI model and generates a floor plan simulation. The server generates a prompt statement based on the preprocessed data and inputs it into the generative AI model. An example of a prompt statement might be, "Please propose a floor plan for a 200 square meter plot of land facing south, with 3 bedrooms, living room, kitchen, kitchenette, parking for two cars, and a garden, and that is barrier-free. The conditions are highly tolerant." The generative AI model generates multiple floor plan simulations based on this prompt statement. The generated floor plan simulations are returned to the server in text or data format.

[0083] Step 5:

[0084] The server visualizes the generated floor plan simulation using 3D modeling software. The server inputs the floor plan simulation obtained from the generative AI model into 3D modeling software and visualizes it. For example, general-purpose 3D modeling software is used to display the proposed floor plan in three dimensions. The visualized data is generated as an image file or a 3D model file.

[0085] Step 6:

[0086] The server sends the visualized data to the terminal. The server sends the visualized floor plan simulation data to the terminal as an HTTP response. The visualization data is sent to the terminal as an image file or a 3D model file.

[0087] Step 7:

[0088] The device displays a floor plan simulation to the user. The device then displays the visualization data received from the server to the user. The user can check multiple floor plan proposals on the device screen and make efficient proposals to the customer. For example, a 3D model can be displayed on the device display, allowing the user to freely rotate and zoom.

[0089] (Application example 1)

[0090] Next, a description will be given of Application Example 1 of Embodiment 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."

[0091] Conventional floor plan simulation systems used by designers have difficulty efficiently presenting three-dimensional floor plan proposals, even when users input conditions such as the size and orientation of the land and the necessary equipment. Furthermore, there was a lack of systems that could automatically generate optimal furniture layout plans and allow users to check them in a 3D view when simulating the layout and furniture arrangement of their home. This made it difficult for users to efficiently arrange and purchase furniture.

[0092] 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.

[0093] In this invention, the server includes: a means for an architect to draft a plan and show the customer a three-dimensional floor plan; a means for presenting multiple floor plan simulations by selecting the land size and orientation, necessary facilities, and other conditions and their tolerance; a means for inputting conditions in accordance with building regulations in advance; a means for a generative AI model to generate multiple furniture arrangement plans based on the floor plan information entered by the user; a means for rendering and displaying the generated plans as 3D models; and a means for saving the plans selected by the user and generating a shopping list. This enables users to efficiently simulate the floor plan and furniture arrangement of their home, check the optimal furniture arrangement plan in a 3D view, and generate a shopping list.

[0094] An "architect" is an engineer who specializes in designing buildings and interiors.

[0095] A "draft plan" is a document or drawing created by an architect at an early stage that shows the basic concept and ideas of the design.

[0096] A "three-dimensional floor plan" is a blueprint or model that represents the interior space of a building in three dimensions.

[0097] "Land size" refers to the area of ​​the site on which the building is constructed.

[0098] "Orientation" is information that indicates the direction in which the building faces.

[0099] "Necessary facilities" refers to the basic facilities and equipment that should be installed in a building.

[0100] "Condition tolerance" refers to the range and flexibility of conditions that are acceptable in the design.

[0101] "Floor plan simulation" is a process of virtually testing the layout of the interior space of a building based on input conditions.

[0102] "Building laws" refer to legal regulations and standards governing the design and construction of buildings.

[0103] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate data based on specific conditions.

[0104] A "furniture arrangement plan" is a design proposal that shows how furniture should be arranged in the interior space of a building.

[0105] A "3D model" is digital data that represents an object or space in three-dimensional space.

[0106] "Rendering" is the process of generating images to visually represent a 3D model.

[0107] A "shopping list" is a document or data that lists the furniture and equipment selected by a user.

[0108] The system for implementing this invention is used by architects to draft plans and show three-dimensional floor plan proposals to clients. The system automatically generates and presents multiple floor plan simulations by inputting the land size and orientation, necessary facilities, and other conditions and tolerances for those conditions. Furthermore, based on the floor plan information entered by the user, a generative AI model generates multiple furniture layout plans, which are then rendered and displayed as 3D models.

[0109] Hardware and software used

[0110] 1. Hardware:

[0111] Smartphone (iOS or ANDROID (registered trademark))

[0112] GPU for 3D rendering

[0113] 2. Software:

[0114] Development environment: Unity (3D rendering), TENSORFLOW (registered trademark) (generative AI model)

[0115] Database: Firebase (registered trademark) (storage of user data)

[0116] API: Google (registered trademark) Maps API (acquisition of location information)

[0117] Data processing and calculation

[0118] 1. User Input:

[0119] Using a smartphone application, users input the land size, orientation, required amenities, and other conditions and tolerances for those conditions.

[0120] 2. Generative AI Model:

[0121] The server uses a generative AI model to generate multiple furniture layout plans based on the floor plan information entered by the user.

[0122] The generative AI model is built using TensorFlow and generates optimal furniture placement plans based on user input.

[0123] 3. 3D rendering:

[0124] The server renders the generated furniture layout plan as a 3D model and displays it on a smartphone.

[0125] Unity is used for 3D rendering to generate visually realistic models.

[0126] 4. Data storage and shopping list generation:

[0127] The plan selected by the user is stored in Firebase for future reference.

[0128] It also generates a shopping list based on the selected plan and provides it to the user.

[0129] Specific examples

[0130] 1. User Input:

[0131] Land size: 100 square meters

[0132] Orientation: South

[0133] Required facilities: kitchen, living room, bathroom, bedroom

[0134] 2. Prompt for the generative AI model:

[0135] The land area is 100 square meters, facing south. The required facilities are a kitchen, living room, bathroom, and bedroom. Please generate the optimal furniture layout plan based on these conditions.

[0136] 3. Example output:

[0137] Plan 1: Open floor plan with integrated kitchen and living room

[0138] Plan 2: A plan that prioritizes privacy with a separate living room and bedroom

[0139] In this way, the system provides a generative AI model that automatically generates multiple furniture layout plans based on information entered by the user and allows users to check them in a 3D view. This allows users to efficiently simulate their home layout and furniture placement, check the optimal furniture layout plan in 3D view, and generate a shopping list.

[0140] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0141] Step 1:

[0142] The user launches the smartphone application and inputs the land size, orientation, required facilities, and other conditions and tolerances for those conditions. The input data is sent from the smartphone device to the server. The input data includes the land size (e.g., 100 square meters), orientation (e.g., facing south), and required facilities (e.g., kitchen, living room, bathroom, bedroom).

[0143] Step 2:

[0144] The server generates a prompt for the generative AI model based on the received input data. The generated prompt reflects the conditions entered by the user. For example, a prompt might be generated that reads, "The land is 100 square meters in size and faces south. The required facilities are a kitchen, living room, bathroom, and bedroom. Based on these conditions, please generate the optimal furniture layout plan."

[0145] Step 3:

[0146] The server inputs the generated prompt sentences into a generative AI model to generate multiple furniture layout plans. The generative AI model is built using TensorFlow and generates the optimal furniture layout plan based on the input prompt sentences. The output is multiple furniture layout plans.

[0147] Step 4:

[0148] The server renders the generated furniture layout plan as a 3D model using Unity, generating a visually realistic 3D model. The output is a 3D model.

[0149] Step 5:

[0150] The server then sends the rendered 3D model to the smartphone device and displays it to the user, who can then view the generated furniture layout plans in 3D through the smartphone application.

[0151] Step 6:

[0152] The user selects the most suitable plan from the displayed furniture layout plans, and the selected plan is sent from the smartphone device to the server.

[0153] Step 7:

[0154] The server saves the selected plan in Firebase for future reference, and generates a shopping list based on the selected plan and provides it to the user. The shopping list includes a list of furniture and equipment included in the selected plan.

[0155] Through the above processing steps, users can efficiently simulate the layout and furniture arrangement of their home, check the optimal furniture arrangement plan in a 3D view, and generate a shopping list.

[0156] Example 2

[0157] Next, a description will be given of Example 2 of Form 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."

[0158] With conventional design support systems, it was difficult for designers to concretely express detailed images of floor plans and interiors, and it was also difficult to precisely respond to customer requests. Furthermore, there were limited options for wall and floor materials, restricting design freedom. This often prevented designers from making satisfactory proposals to customers, making the design process inefficient.

[0159] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0160] In this invention, the server includes means for the designer to select wall and floor materials from reference knowledge, means for the designer to input images of the floor plan and interior, means for the server to collect data on the selected fixtures and interior, means for the server to generate images using image generation AI, means for the server to present the generated images to the designer, and means for the designer to check the generated images and make corrections as necessary. This enables the designer to quickly and accurately generate and propose detailed images of the floor plan and interior based on the customer's requests.

[0161] An "architect" is an engineer who specializes in designing buildings and designs floor plans and interiors.

[0162] A "draft plan" is an early stage plan that shows the basic design and layout of a building.

[0163] A "three-dimensional floor plan" is a blueprint or model that represents the floor plan of a building in three dimensions.

[0164] "Land size and orientation" refers to the area and orientation of the land on which the building will be constructed.

[0165] "Essential facilities" refers to the basic facilities and equipment that should be installed in a building.

[0166] "Condition tolerance" refers to the range and flexibility of conditions that are acceptable in the design.

[0167] "Floor plan simulation" is the process of virtually trying out a designed floor plan and visually confirming the results.

[0168] "Building laws" refer to legal regulations and standards governing the design and construction of buildings.

[0169] "Reference knowledge" refers to standard information and data provided by manufacturers of wall and flooring materials, etc.

[0170] "Image generation AI" refers to artificial intelligence technology that generates images based on input text or data.

[0171] "Fixtures" refers to decorations and structures installed inside and outside a building.

[0172] "Interior" refers to the design and decoration of the interior space of a building.

[0173] "Collecting data" refers to the process of gathering and organizing the necessary information or data.

[0174] "Generating an image" refers to creating a visual picture or model based on input information.

[0175] "Modifying" refers to making changes or adjustments to the generated image or design.

[0176] This invention is a system used by architects when designing the layout and interior of buildings, and allows them to select from "reference knowledge" provided by manufacturers of wall and flooring materials, among other things, and generate specific images using image generation AI. The system is operated by the user (architect) using a dedicated terminal, and the server collects data and generates images.

[0177] Hardware and software used

[0178] Device: A device such as a computer or tablet used by an architect.

[0179] Server: A server for collecting data, processing, and generating images.

[0180] Image generation AI: Image generation models such as DALL-E.

[0181] Data processing and calculation

[0182] 1. A user logs into the system

[0183] The user accesses the system using a terminal and enters their user ID and password on the login screen. The server performs authentication, and if authentication is successful, the main screen is displayed.

[0184] 2. The user selects wall and floor materials from reference knowledge.

[0185] The user browses through a list of wall and flooring materials offered by manufacturers on the system interface and selects the desired material, which is then sent to the server and temporarily stored.

[0186] 3. The user inputs the floor plan and interior image

[0187] The user inputs a specific image of the floor plan and interior into the text box. For example, they can input a request such as "I want wood-grain flooring in the living room and white walls."

[0188] 4. The server collects data on the selected features and interior.

[0189] The server collects data on the selected wall and floor materials from the database, including images of the materials, texture information, and manufacturer information.

[0190] 5. The server generates the image using image generation AI

[0191] The server sends a prompt to the image generation AI based on the collected data and the image entered by the user. The prompt specifically describes the user's request. The image generation AI analyzes the prompt and generates a corresponding image.

[0192] 6. The server presents the generated image to the user

[0193] The server receives the images generated by the image generation AI and sends them to the user's device, where the user can view the generated images on the system interface.

[0194] 7. The user checks the generated image and makes corrections if necessary.

[0195] The user can review the generated image and make any necessary modifications or regenerate it, for example, changing the wall color or adjusting the furniture placement. Once modifications are complete, the user saves the final design and is ready to present it to the client.

[0196] Specific examples

[0197] For example, if an architect inputs a request such as "Use wood-grain flooring and white walls in the living room," the system will process it as follows:

[0198] 1. The designer logs into the system.

[0199] 2. The architect selects wood-grain flooring and white wall coverings from reference knowledge.

[0200] 3. The architect inputs an image of "wood-grain flooring in the living room and white walls."

[0201] 4. The server retrieves images and texture information for "white wall material" and "wood-grain floor material" from the database.

[0202] 5. The server sends the prompt "Use wood-grain flooring and white walls in the living room" to the image generation AI and receives the generated image.

[0203] 6. The server sends the generated image to the designer's terminal, and the designer checks the image on the interface.

[0204] 7. The architect types "change the wall color to blue" and sends the prompt to the image generation AI again. A new image is generated and presented to the architect.

[0205] Prompt Sentence Examples

[0206] "The living room will have wood-grain flooring and white walls. The furniture will be modern, with a gray sofa and a glass table."

[0207] By inputting this prompt into the image generation AI, an image of the living room the designer envisions is generated.

[0208] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0209] Step 1:

[0210] A user logs in to the system.

[0211] Input: User ID and password.

[0212] Data processing: The server checks the entered user ID and password against the database and performs authentication.

[0213] Output: If authentication is successful, display the main screen.

[0214] Specific operation: The user enters the user ID and password on the login screen of the terminal and clicks the "Login" button. The server accesses the database and verifies the authentication information. If authentication is successful, the main screen is displayed on the terminal.

[0215] Step 2:

[0216] The user selects wall and floor materials from reference knowledge.

[0217] Input: A list of wall and flooring materials.

[0218] Data processing: The server temporarily stores information about the selected wall and floor materials.

[0219] Output: Information about the selected wall and floor coverings.

[0220] Specific operation: The user selects wall and floor materials using drop-down menus and search functions on the system interface. The selected materials are sent to the server and temporarily stored.

[0221] Step 3:

[0222] The user inputs the floor plan and interior image.

[0223] Input: A concrete image (text) of the floor plan and interior.

[0224] Data processing: The server analyzes the input image and generates a prompt.

[0225] Output: The generated prompt statement.

[0226] Specific behavior: The user enters "I want wood-effect flooring and white walls in the living room" into the text box and clicks the "Submit" button. The server parses the entered text and generates a prompt.

[0227] Step 4:

[0228] The server collects data on the selected fixtures and interiors.

[0229] Input: Information about the selected wall and floor covering.

[0230] Data processing: The server retrieves images, texture information, and manufacturer information of the selected material from the database.

[0231] Output: Collected data.

[0232] Specific operation: The server accesses the database and obtains images, texture information, and manufacturer information of the selected wall or floor material.

[0233] Step 5:

[0234] The server generates the image using image generation AI.

[0235] Input: Prompt statement and collected data.

[0236] Data processing: The server sends a prompt to the image generation AI, which then generates a corresponding image.

[0237] Output: The generated image.

[0238] Specific operation: The server sends the prompt "Use wood-grain flooring and white walls in the living room" to the image generation AI, which analyzes the prompt and generates the corresponding image.

[0239] Step 6:

[0240] The server presents the generated image to the user.

[0241] Input: The generated image.

[0242] Data processing: The server sends the generated image to the user's device.

[0243] Output: The image displayed on the user's device.

[0244] Specific operation: The server sends the generated image to the user's terminal, and the user checks the image on the interface.

[0245] Step 7:

[0246] The user checks the generated image and makes corrections as necessary.

[0247] Input: User correction instructions.

[0248] Data processing: The server receives the correction instructions and sends the prompt text to the image generation AI again.

[0249] Output: The rectified image.

[0250] Specific operation: The user checks the generated image, inputs "change the wall color to blue," and sends the prompt to the image generation AI again. A new image is generated and presented to the user.

[0251] (Application example 2)

[0252] Next, a description will be given of Application Example 2 of Form 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."

[0253] With conventional design systems, when proposing floor plans and interiors, designers had to manually select materials and furniture and create images, which was time-consuming and labor-intensive. Even in the interior design of brick-and-mortar stores, it was difficult for store owners to have a concrete image, making it difficult to confirm and modify the design. This made it difficult to precisely meet customer requests, potentially reducing satisfaction.

[0254] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0255] In this invention, the server includes: a means for an architect to draft a plan and show a three-dimensional floor plan to a customer; a means for presenting multiple floor plan simulations by selecting the size and orientation of the lot, necessary equipment, and other conditions and their tolerance; a means for inputting conditions in accordance with building regulations in advance; a means for selecting only from "reference knowledge" provided by manufacturers of wall and floor materials, etc., and then using image generation AI to generate not only the floor plan but also fixtures and interior fittings that match the image; a means for supporting the interior design of a physical store by allowing a store owner to select wall materials, flooring materials, furniture, etc. and simulate the store layout and design; a means for using image generation AI to generate a realistic image of the store interior based on the selected materials and furniture and present it to the store owner; and a means for the store owner to review and modify the generated image. This enables architects and store owners to efficiently create floor plans and interior designs that precisely meet customer requests.

[0256] An "architect" is an engineer who specializes in designing buildings and interiors.

[0257] A "draft plan" is a basic design concept or plan created by an architect in the early stages.

[0258] A "three-dimensional floor plan" is a blueprint or model that represents the internal structure of a building in three dimensions.

[0259] The land area refers to the area of ​​the site on which a building is constructed.

[0260] "Orientation" refers to information that indicates the direction in which a building faces.

[0261] "Essential facilities" refers to the basic infrastructure and equipment that must be installed in a building.

[0262] "Condition tolerance" refers to the range and flexibility of conditions that are allowed in a design.

[0263] "Floor plan simulation" is a process in which an architect virtually tests out design proposals to find the optimal floor plan.

[0264] "Building laws" refer to legal regulations and standards regarding the design and construction of buildings.

[0265] "Reference knowledge" refers to information and data on wall and floor materials provided by manufacturers.

[0266] "Image generation AI" is a technology that uses artificial intelligence to generate images from text or data.

[0267] A "brick and mortar store" is a commercial establishment or store that exists in a physical location.

[0268] "Store owner" refers to the owner or manager of a physical store.

[0269] "Materials" refers to materials and parts used in architecture and interior design.

[0270] "Furniture" refers to interior items placed inside a building.

[0271] "Layout" refers to the design of the layout and structure within a building or store.

[0272] "Simulation" is a process of virtually recreating a real-world situation and conducting trial and error.

[0273] "Realistic store interior image" refers to a visual representation that faithfully reproduces the interior of an actual store.

[0274] "Verification and correction" refers to the process of reviewing the generated designs and images and making changes as necessary.

[0275] The system for implementing this invention aims to enable designers and store owners to efficiently create floor plans and interior designs that precisely meet customer needs. This system is realized using the following hardware and software.

[0276] Hardware

[0277] Server: Processes data and runs image-generating AI models.

[0278] Devices: Devices such as smartphones and tablets used by designers and store owners.

[0279] Network: An internet connection to connect the server and your device.

[0280] software

[0281] Image generation AI model: Uses OpenAI (registered trademark) API to generate images based on prompt text.

[0282] Database: Stores "reference knowledge" such as wall and floor materials.

[0283] User interface: An application that allows designers and store owners to select materials and layouts and check simulation results.

[0284] Data processing and calculation

[0285] 1. Selection of materials and conditions: The user (architect or store owner) selects conditions such as wall materials, flooring materials, furniture, and layout.

[0286] 2. Generate prompt sentence: Generate prompt sentence based on selected conditions.

[0287] 3. Image generation: The generated prompt sentences are input into an image generation AI model to generate a realistic image of the store interior.

[0288] 4. Image presentation: The generated image is presented to the user for review and correction.

[0289] Specific examples

[0290] For example, when simulating the interior design of a cafe, the user selects the following conditions:

[0291] Wall material: White brick

[0292] Flooring: Wooden flooring

[0293] Layout: Cafe style layout

[0294] The prompt generated based on this condition is as follows:

[0295] Walls: White brick, Floors: Wooden flooring, Layout: Cafe-style layout

[0296] By inputting this prompt into an image-generating AI model, a realistic image of the cafe's interior design is generated, which is then presented to the user, who can review it and make any necessary adjustments.

[0297] In this way, designers and store owners can efficiently create designs and respond precisely to customer requests.

[0298] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0299] Step 1:

[0300] The user uses a terminal to select conditions such as wall materials, floor materials, furniture, and layout.

[0301] Input: User-selected conditions (wall materials, floor materials, furniture, layout)

[0302] Output: Data for selected conditions

[0303] How it works: Through the application interface, users tap or click to select options such as wall and flooring materials, furniture, and layout. The selected conditions are saved on the device.

[0304] Step 2:

[0305] The terminal generates a prompt based on the selected conditions.

[0306] Input: Data for selected conditions

[0307] Output: Generated prompt statement

[0308] Specific operation: The terminal converts the selected conditions into text and generates a prompt sentence. For example, a prompt sentence of the form "Wall material: white brick, Floor material: wooden flooring, Layout: cafe-style layout" is generated.

[0309] Step 3:

[0310] The terminal sends the generated prompt to the server.

[0311] Input: Generated prompt text

[0312] Output: The prompt sent to the server

[0313] Specific operation: The terminal sends the generated prompt text as an HTTP request to the server, which receives the request.

[0314] Step 4:

[0315] The server receives the prompt text and inputs it into the image generation AI model.

[0316] Input: The prompt sent to the server

[0317] Output: Input data to the image generation AI model

[0318] Specific operation: The server analyzes the received prompt text and converts it into a format suitable for the image generation AI model. The converted data is then input into the image generation AI model.

[0319] Step 5:

[0320] The server uses an image generation AI model to generate an image based on the prompt text.

[0321] Input: Input data to the image generation AI model

[0322] Output: The generated image

[0323] How it works: The image generation AI model generates a realistic image of the store interior based on the input prompt. The generated image is stored on the server.

[0324] Step 6:

[0325] The server transmits the generated image to the terminal.

[0326] Input: Generated image

[0327] Output: Image sent to the device

[0328] Specific operation: The server sends the generated image to the terminal as an HTTP response. The terminal receives this response.

[0329] Step 7:

[0330] The terminal presents the received image to the user.

[0331] Input: Image sent to the device

[0332] Output: The image presented to the user

[0333] Specific operation: The device displays the received image in the application interface, allowing the user to review the image and make any necessary corrections.

[0334] Example 3

[0335] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0336] Conventional floor plan simulation systems have the problem that it is difficult for designers to generate floor plan proposals that comply with building laws and local government ordinances when drafting plans. Furthermore, there is a lack of a way to check whether the floor plan proposal entered by the user violates the law, which can result in the creation of a floor plan that violates the law. Furthermore, there is a lack of a way to quickly return the verification results to the user, which makes it difficult to achieve an efficient design process.

[0337] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0338] In this invention, the server includes a means for an architect to use in drafting plans and for showing three-dimensional floor plan proposals to a customer, a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels, a means for inputting conditions in accordance with building laws in advance, a means for comparing the floor plan proposal entered by the user with legal information, and a means for returning the comparison results to the user. This makes it possible to efficiently generate floor plan proposals that comply with laws and quickly return the comparison results to the user.

[0339] An "architect" is an engineer who specializes in designing buildings, and is responsible for drafting architectural plans and designing floor plans.

[0340] A "draft plan" is an early proposal for the basic design and floor plan of a building, and is created as a preliminary step to detailed design.

[0341] "Customer" refers to an individual or corporation that requests the design and construction of a building, and is the party that receives proposals for floor plans and architectural plans from the architect.

[0342] A "three-dimensional floor plan" is a blueprint or model that represents the floor plan of a building in three dimensions, making it easier to visually understand the internal structure of the building.

[0343] "Land size" refers to the area of ​​the site on which a building will be constructed, and is an important factor in architectural planning.

[0344] "Orientation" refers to the direction or orientation of the site on which a building is constructed, and is a factor that affects the layout and design of a building.

[0345] "Necessary facilities" refers to the basic facilities and equipment that must be installed in a building, including, for example, electrical equipment and water supply and drainage facilities.

[0346] "Condition tolerance" refers to the range and restrictions of conditions that are permissible in architectural plans, including, for example, building height and building coverage ratio.

[0347] "Floor plan simulation" is the process of virtually designing the floor plan of a building and generating multiple floor plan proposals based on various conditions.

[0348] "Building laws" refers to legal regulations regarding the design and construction of buildings, including, for example, the Building Standards Act and local government ordinances.

[0349] "Legal information" refers to specific data and regulations related to building laws, which are stored in a database.

[0350] "Verification" is the process of comparing the floor plan entered by the user with legal information to determine whether there are any matches or mismatches.

[0351] "Matching result" refers to the information obtained as a result of the matching process, including, for example, a determination of whether or not a law has been violated.

[0352] MODE FOR CARRYING OUT THE INVENTION

[0353] The present invention provides a system for efficiently generating floor plan proposals that comply with building regulations and quickly returning collation results to the user. Specific embodiments of this system will be described below.

[0354] Generate a program for the system

[0355] The server generates a program that stores legal information, such as building laws and local ordinances, in a database. This program takes legal information into account when users simulate floor plans. The hardware used includes a standard server computer, and the software uses the MySQL® database management system and the Python programming language.

[0356] Explaining the program's processing in natural language

[0357] The server uses the legal information stored in the database to verify the floor plan entered by the user. Specifically, it performs the following data processing and calculations:

[0358] 1. A user inputs a floor plan proposal. For example, the user inputs the building height as "10 meters" and the lot area as "200 square meters" into a web application form.

[0359] 2. The server receives the JSON data {"height": 10, "area": ​​200} sent by the user.

[0360] 3. The server queries the MySQL database to get the building code information for the area. For example, the query might return {"max_height": 8, "max_area": ​​250}.

[0361] 4. The server compares the acquired legal information with the proposed floor plan entered by the user. For example, it verifies that the building height entered by the user (10 meters) exceeds the legal maximum height of 8 meters. It also verifies that the site area (200 square meters) is within the maximum area (250 square meters).

[0362] 5. The server returns the result of the check to the user. If the law is violated, an error message containing the specific details of the violation is returned. If the law is not violated, the server notifies the user that the proposed floor plan complies with the law.

[0363] Add examples to your description

[0364] As a concrete example, consider the case where a user sets the height of a building to 10 meters. The server references the information stored in the database under the Building Standards Act and verifies that the building height limit for that area is 8 meters. In this case, the server returns an error message to the user stating, "The building height exceeds the legal limit. Please set the height to 8 meters or less."

[0365] Example prompts to input to a generative AI model:

[0366] "If you set the building height at 10 metres, check whether it violates the Building Standards Act."

[0367] In this way, the system can generate legally compliant floor plan proposals. The flow of the specification process in the third embodiment will be described with reference to FIG.

[0368] Program processing flow

[0369] Step 1:

[0370] The user inputs a floor plan.

[0371] Specifically, a user enters information such as the building's height and lot area into a web application form. For example, the user enters the building's height as "10 meters" and the lot area as "200 square meters."

[0372] Input: Building height "10 meters", site area "200 square meters"

[0373] Output: Floor plan data entered by the user

[0374] Step 2:

[0375] The server receives the input floor plan.

[0376] Specifically, the server receives the JSON data {"height": 10, "area": ​​200} sent by the user.

[0377] Input: Floor plan data entered by the user

[0378] Output: Floor plan data received by the server

[0379] Step 3:

[0380] The server retrieves the legal information from the database.

[0381] Specifically, the server queries the MySQL database to get the building code information for the area, for example, {"max_height": 8, "max_area": ​​250} .

[0382] Input: Floor plan data received by the server

[0383] Output: Legal information retrieved from the database

[0384] Step 4:

[0385] The server compares the floor plan with legal information.

[0386] Specifically, the server compares the acquired legal information with the proposed floor plan entered by the user. For example, it verifies that the building height entered by the user (10 meters) exceeds the legal maximum height of 8 meters. It also verifies that the site area (200 square meters) is within the maximum area of ​​250 square meters.

[0387] Input: Legal information retrieved from the database, floor plan data entered by the user

[0388] Output: Matching result (whether it violates the law or not)

[0389] Step 5:

[0390] The server returns the match result to the user.

[0391] Specifically, the server returns the results of the comparison to the user. If the law is violated, an error message is returned containing the specific details of the violation. For example, a message such as "The building height exceeds the legal limit. Please set the height to 8 meters or less" is returned. If the violation is not present, the user is notified that the proposed floor plan complies with the law.

[0392] Input: Matching result

[0393] Output: A message of the match result returned to the user

[0394] (Application example 3)

[0395] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0396] With conventional architectural design systems, it was difficult for designers to generate floor plan proposals that took legal and safety standards into account when creating draft plans. Furthermore, when it came to layout design to optimize the placement of machinery and equipment within a factory, there was a lack of a way to automatically generate optimal layout proposals that took legal and safety standards into account. This made it difficult to achieve an efficient and safe factory layout.

[0397] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0398] In this invention, the server includes a means for an architect to use in drafting plans and for showing three-dimensional floor plan proposals to a customer, a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary equipment, and other conditions and their tolerance levels, a means for inputting conditions in accordance with building regulations in advance, a means for designing a layout to optimize the placement of machinery and equipment within a factory, and a means for generating layout proposals that take laws and safety standards into consideration. This makes it possible to automatically generate floor plan proposals and factory layout proposals that take laws and safety standards into consideration.

[0399] An "architect" is an engineer who specializes in architectural and interior design.

[0400] A "draft plan" is the basic design concept or plan created by an architect in the early stages.

[0401] A "three-dimensional floor plan" is a blueprint that represents the internal structure of a building in three dimensions.

[0402] "Land size" refers to the area of ​​land available for constructing a building.

[0403] "Orientation" refers to the direction or orientation in which a building or facility is located.

[0404] "Necessary facilities" is a general term for machines and equipment required within a building or factory.

[0405] "Condition tolerance" refers to the range and limits that are permissible in design and layout.

[0406] A "floor plan simulation" is a simulation for virtually arranging and evaluating the internal structure of a building.

[0407] "Building law" refers to legal regulations and standards governing the design and construction of buildings.

[0408] "Layout of machinery and equipment within a factory" refers to planning the optimal layout of the machinery and equipment used within a factory.

[0409] "Layout design" is the planning of the physical arrangement and structure within a specific space.

[0410] "Legal and safety standards" refers to legal regulations and safety standards that must be observed in design and layout.

[0411] A "layout proposal" is a proposal for the physical arrangement or structure within a particular space.

[0412] A system for carrying out this invention includes means for an architect to use in drafting plans and showing a three-dimensional floor plan to a client, means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and tolerances for those conditions, means for inputting conditions in accordance with building laws in advance, means for designing a layout to optimize the placement of machinery and facilities within a factory, and means for generating a layout plan that takes into account laws and safety standards.

[0413] Program processing explanation

[0414] The server uses a Python program to utilize generative AI models and legal databases. The server receives factory specifications and local legal requirements as input and generates a layout based on them. Specifically, it performs the following processes:

[0415] 1. Data entry: The server receives the factory specifications (e.g., type of machinery, space size) and local legal requirements.

[0416] 2. Data processing: The server retrieves the relevant laws and safety standards from the legal database and integrates them with the factory specifications.

[0417] 3. Layout generation: The server uses a generative AI model to generate an optimal layout plan that takes into account legal and safety standards.

[0418] 4. Result output: The server presents the generated layout proposal to the user.

[0419] Specific examples

[0420] For example, when used in a factory in Tokyo, the following prompt sentences are input into the generative AI model:

[0421] Factory specifications: There are machine 1, machine 2 and machine 3, the space is 1000 square meters.

[0422] Region: Tokyo

[0423] Example prompt sentence:

[0424] Factory specifications: Machine 1, Machine 2, Machine 3, space 1000 square meters, location Tokyo. Generate the optimal layout taking into account laws and safety standards.

[0425] In this way, the server can automatically generate floor plan and factory layout proposals that take into account laws and safety standards.

[0426] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0427] Step 1:

[0428] The server receives factory specifications (e.g., machine type, space size) and local legal requirements as input from the user. Specifically, the user enters the factory specifications and local information into an input form on their terminal and sends it to the server. The input data includes the machine type, installation space size, and local area name.

[0429] Step 2:

[0430] The server retrieves the relevant laws and safety standards from the legal database based on the received regional information. Specifically, the server sends the regional information as a query to the legal database and retrieves data on the relevant laws and safety standards. The input is regional information, and the output is data on the relevant laws and safety standards.

[0431] Step 3:

[0432] The server integrates the factory specifications with the acquired legal and safety standard data. Specifically, it merges the factory specification data with the legal data to create integrated data to input into the generative AI model. The input is the factory specification data and legal data, and the output is the integrated data.

[0433] Step 4:

[0434] The server uses a generative AI model to generate an optimal layout plan based on the integrated data. Specifically, the integrated data is input into the generative AI model, which then generates an optimal layout plan that takes into account laws and safety standards. The input is the integrated data, and the output is the optimal layout plan.

[0435] Step 5:

[0436] The server presents the generated layout plan to the user. Specifically, the server sends the generated layout plan to the user's device so that the user can visually check it. The input is the optimal layout plan, and the output is the layout plan presented to the user.

[0437] In this way, the server can automatically generate floor plan and factory layout proposals that take into account laws and safety standards and provide them to users.

[0438] 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.

[0439] "Example 1"

[0440] The system described in claim 4 includes an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their facial expressions, tone of voice, choice of words, etc. For example, if the user says, "This room is dark," the emotion engine will sense dissatisfaction from the user's tone of voice, and the system will suggest a brighter floor plan.

[0441] "Example 2"

[0442] The system described in claim 5 includes an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their reactions and adjusts the selection of wall and floor materials and the image generation of fixtures and interiors based on the analysis. For example, if the user comments, "I'd like a more subdued feel" in response to a proposed floor plan, the emotion engine analyzes the user's desired "subdued feel," and the system selects wall and floor materials with more subdued colors and materials, and adjusts the image generation of fixtures and interiors accordingly.

[0443] "Example 3"

[0444] The system described in claim 6 includes an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their reactions and automatically generates an optimal floor plan based on the analysis. For example, if the user comments, "I want a more open feeling" in response to a proposed floor plan, the emotion engine analyzes the "open feeling" desired by the user, and the system automatically generates a more open floor plan.

[0445] The processing flow of each embodiment will be described below.

[0446] "Example 1"

[0447] Step 1: The user starts the system and inputs the necessary information (land size, orientation, required facilities, etc.).

[0448] Step 2: The system generates multiple floor plan options based on the input information and presents them to the user.

[0449] Step 3: The user provides feedback on the floor plan. This feedback can include not only words, but also facial expressions and tone of voice.

[0450] Step 4: The emotion engine analyzes emotions from user feedback.

[0451] Step 5: The system adjusts the floor plan proposal based on the analysis results of the emotion engine and presents it to the user again.

[0452] "Example 2"

[0453] Step 1: The user starts the system and inputs the necessary information (land size, orientation, required facilities, etc.).

[0454] Step 2: The system generates multiple floor plan options based on the input information and presents them to the user.

[0455] Step 3: The user provides feedback on the floor plan. This feedback can include not only words, but also facial expressions and tone of voice.

[0456] Step 4: The emotion engine analyzes emotions from user feedback.

[0457] Step 5: Based on the analysis results of the emotion engine, the system adjusts the selection of wall and floor materials and the image generation of fixtures and interiors, and presents them again to the user.

[0458] "Example 3"

[0459] Step 1: The user starts the system and inputs the necessary information (land size, orientation, required facilities, etc.).

[0460] Step 2: The system generates multiple floor plan options based on the input information and presents them to the user.

[0461] Step 3: The user provides feedback on the floor plan. This feedback can include not only words, but also facial expressions and tone of voice.

[0462] Step 4: The emotion engine analyzes emotions from user feedback.

[0463] Step 5: The system automatically generates an optimal floor plan based on the analysis results of the emotion engine and presents it to the user again.

[0464] Example 1

[0465] Next, a description will be given of Example 1 of Form 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."

[0466] With conventional design support systems, when a designer drafts a plan, they have to manually create a floor plan while taking into account conditions such as the size and orientation of the land and the necessary facilities, which is time-consuming and labor-intensive. It is also difficult to reflect the user's feelings and feedback in real time, making it impossible to quickly provide optimal floor plan proposals. Furthermore, the design process is complicated because it is necessary to manually check conditions that comply with building laws.

[0467] The specification process by the specification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means used by an architect to create a draft plan and to show a three-dimensional floor plan to a customer, a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels, a means for inputting conditions in accordance with building laws in advance, a means for analyzing the user's emotions and adjusting the floor plan based on those emotions, and a means for generating floor plan proposals using a generative AI model. This enables the architect to efficiently generate optimal floor plan proposals and make flexible proposals that respond to the user's emotions.

[0468] An "architect" is an engineer who specializes in architectural and interior design.

[0469] "Drafting the plan" refers to the design proposal that the architect creates at an early stage.

[0470] A "3D floor plan" refers to a diagram of the interior layout of a building presented in 2D or 3D visual format.

[0471] "Land size" refers to the area of ​​the proposed construction site.

[0472] "Orientation" refers to the direction in which the proposed construction site or building faces.

[0473] "Necessary facilities" refers to the basic equipment and facilities that should be installed within the building.

[0474] "Other conditions" refers to additional requirements or constraints that must be considered in the design.

[0475] "Condition tolerance" refers to the flexibility and tolerance for design conditions.

[0476] "Floor plan simulation" refers to a virtual model of the interior layout of a building that is automatically generated based on input conditions.

[0477] "Building laws" refers to legal regulations and standards governing the design and construction of buildings.

[0478] "Analyzing emotions" refers to reading a user's emotions from their facial expressions, tone of voice, choice of words, etc.

[0479] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to generate new information or suggestions from data.

[0480] A "prompt" refers to an instruction or question that is input into a generative AI model.

[0481] The present invention is a system used by architects to draft plans, and includes a function to analyze the user's emotions and adjust the floor plan proposal based on those emotions. Specific embodiments of this system are described below.

[0482] Hardware and software used

[0483] Hardware: High-performance server (e.g., high-performance server equipment)

[0484] Software: Generative AI models (e.g., advanced generative AI algorithms), emotion engines (e.g., emotion analysis software)

[0485] Details of data processing and calculation

[0486] 1. Data Entry:

[0487] The user (designer) inputs the land size, orientation, necessary facilities, other conditions and their tolerances through the system interface.

[0488] Specifically, you enter information such as "Land size: 200 square meters," "Orientation: South-facing," "Required facilities: Kitchen, living room, two bedrooms, bathroom," "Other conditions: Barrier-free, lots of natural light," and "Condition tolerance: High" into the input form.

[0489] 2. Data transmission:

[0490] The terminal transmits the data entered by the user to the server in real time.

[0491] Specifically, when you press the submit button on the input form, the data is sent to the server in JSON format.

[0492] 3. Generate floor plan simulation:

[0493] Based on the received data, the server uses a generative AI model to generate multiple floor plan simulations.

[0494] Specifically, the server inputs prompt text into the generative AI model, using prompt text such as, "The land is 200 square meters and faces south. The required facilities are a kitchen, living room, two bedrooms, and a bathroom. It must be barrier-free and have plenty of natural light. The conditions are highly tolerant. Please generate a floor plan based on this."

[0495] 4. Floor plan presentation:

[0496] The server transmits the generated floor plan proposals to the terminal.

[0497] Specifically, the generated floor plan is sent to the device as an image or 3D model so that the user can check it.

[0498] 5. Emotion analysis:

[0499] As the user reviews the proposed floor plan, the device uses an emotion engine to analyze the user's facial expressions, tone of voice, and choice of words.

[0500] Specifically, if a user says, "This room is dark," the emotion engine will sense dissatisfaction from the tone of voice and facial expression.

[0501] 6. Adjusting the floor plan:

[0502] The server receives feedback from the emotion engine and again uses the generative AI model to generate new floor plan suggestions based on the user's emotions.

[0503] Specifically, a prompt such as "The user feels that the room is dark, so please generate a brighter floor plan" is used.

[0504] 7. Presenting a new floor plan:

[0505] The server sends the new floor plan to the terminal and presents it to the user.

[0506] Specifically, the new floor plan is sent to the device again as an image or 3D model.

[0507] Specific examples

[0508] Example input:

[0509] Land size: 200 square meters

[0510] Orientation: South

[0511] Required facilities: kitchen, living room, two bedrooms, bathroom

[0512] Other requirements: Barrier-free access, plenty of natural light

[0513] Condition tolerance: High

[0514] Example prompt sentence:

[0515] The land area is 200 square meters and faces south. The required facilities are a kitchen, living room, two bedrooms, and a bathroom. It must be barrier-free and have plenty of natural light. The conditions are highly tolerant. Please generate a floor plan based on this.

[0516] This system allows designers to efficiently generate optimal floor plan proposals and make flexible suggestions that reflect the user's emotions.

[0517] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0518] Step 1:

[0519] The user inputs the data. The user (architect) enters the land size, orientation, required facilities, other conditions, and their tolerance levels through the system interface. Specifically, the user enters information such as "Land size: 200 square meters," "Orientation: South-facing," "Required facilities: Kitchen, living room, two bedrooms, bathroom," "Other conditions: Barrier-free access, lots of natural light," and "Condition tolerance: High" into the input form. The input data is sent to the system.

[0520] Step 2:

[0521] The terminal sends data to the server. The terminal sends the data entered by the user to the server in real time. Specifically, when the submit button on the input form is pressed, the data is sent to the server in JSON format. The input data reaches the server and proceeds to the next processing step.

[0522] Step 3:

[0523] The server generates a floor plan simulation. Based on the received data, the server uses a generative AI model to generate multiple floor plan simulations. Specifically, the server inputs a prompt statement into the generative AI model, such as, "The land is 200 square meters in size and faces south. The required facilities are a kitchen, living room, two bedrooms, and a bathroom. It must be barrier-free and have plenty of natural light. The conditions are highly tolerant. Please generate a floor plan proposal based on this." The generated floor plan proposals are saved on the server.

[0524] Step 4:

[0525] The server sends the generated floor plan to the terminal. The server then sends the multiple floor plan plans it has generated to the terminal. Specifically, the generated floor plan plans are sent to the terminal as images or 3D models so that the user can check them. The sent floor plan plans are displayed on the terminal.

[0526] Step 5:

[0527] The user reviews the floor plan. The user reviews the floor plan presented on the device. Specifically, the user rotates the floor plan on the device screen and zooms in and out to view the details. The user's feedback advances to the next processing step.

[0528] Step 6:

[0529] The device analyzes the user's emotions. Using an emotion engine, the device analyzes the user's facial expressions, tone of voice, and choice of words. For example, if the user says, "This room is dark," the emotion engine will sense dissatisfaction from the tone of voice and facial expression. The analysis results are sent to the server.

[0530] Step 7:

[0531] The server adjusts the floor plan proposal based on the emotion. The server receives feedback from the emotion engine and uses the generative AI model again to generate a new floor plan proposal based on the user's emotion. Specifically, it uses a prompt such as, "The user felt the room was dark, so please generate a brighter floor plan proposal." The new floor plan proposal is then saved on the server.

[0532] Step 8:

[0533] The server sends the new floor plan to the device. The server then sends the new floor plan to the device and presents it to the user. Specifically, the server sends the new floor plan to the device again as an image or 3D model. The new floor plan is then displayed on the device.

[0534] Step 9:

[0535] The user performs the final confirmation. The user checks the new floor plan and provides final feedback. Specifically, this process is repeated until the user is satisfied, and finally, a satisfactory floor plan is finalized. The final floor plan is saved in the system.

[0536] (Application example 1)

[0537] Next, a description will be given of Application Example 1 of Embodiment 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."

[0538] With conventional design systems, it took a lot of time and effort for designers to create a draft plan, and it was difficult to efficiently present three-dimensional floor plan proposals to customers. Furthermore, it was not possible to reflect user emotions and feedback in real time, making it difficult to provide optimal design proposals. In addition, the generation and adjustment of interior designs had to be done manually, which was inefficient.

[0539] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes: a means for an architect to use in drafting a plan and to show a three-dimensional floor plan to a customer; a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels; a means for pre-entering conditions in accordance with building regulations; a means including an emotion engine that recognizes a user's emotions, analyzing the user's emotions from their facial expressions, tone of voice, and word choice, and adjusting the floor plan based on the feedback; a means for displaying interior design proposals in 3D using a smart device; a means for generating interior design proposals using a generative AI model; and a means for readjusting the design proposals based on the results of the emotion analysis. This enables an architect to efficiently draft a plan and present three-dimensional floor plan proposals to a customer, thereby providing an optimal design proposal that reflects the user's emotions and feedback in real time.

[0540] An "architect" is an engineer who specializes in designing buildings and interiors.

[0541] A "draft plan" is a basic design concept or plan created by an architect in the early stages.

[0542] A "three-dimensional floor plan" is a diagram of the interior layout of a building that is represented in 3D rather than 2D.

[0543] "Land size" refers to the area of ​​the proposed construction site.

[0544] "Orientation" refers to information that indicates the direction in which the proposed construction site and building face.

[0545] "Necessary facilities" refers to the equipment and devices that must be installed within the building.

[0546] "Condition tolerance" refers to the range of conditions that are acceptable in a design.

[0547] A "floor plan simulation" is a virtual model of the interior layout of a building that is automatically generated based on input conditions.

[0548] "Building law" refers to the legal regulations and standards governing the design and construction of buildings.

[0549] An "emotion engine" is a system that analyzes emotions from a user's facial expressions, tone of voice, choice of words, etc.

[0550] A "smart device" is an electronic device that has internet connectivity and advanced computing capabilities.

[0551] An "interior design proposal" is a design proposal regarding the decoration and layout of the interior of a building.

[0552] A "generative AI model" is an algorithm that uses artificial intelligence to automatically generate designs and plans.

[0553] "Sentiment analysis" refers to the process of analyzing a user's emotions.

[0554] "Re-tuning a design proposal" is the process of revising a design based on user feedback and sentiment analysis results.

[0555] A system for implementing this invention is used by architects to draft plans and show three-dimensional floor plan proposals to clients. By inputting the land size and orientation, necessary facilities, and other conditions and tolerances for those conditions, the system automatically generates multiple floor plan simulations and presents them to the architect. It also includes an emotion engine that recognizes the user's emotions, analyzes their emotions from their facial expressions, tone of voice, and choice of words, and adjusts the floor plan proposal based on the feedback.

[0556] Hardware and software used

[0557] Hardware:

[0558] Smartphones (e.g., iPhone (registered trademark), Android devices)

[0559] Smart glasses (e.g., Google Glass(R), Microsoft(R) HoloLens(R))

[0560] software:

[0561] Generative AI models (e.g., OpenAI GPT-4 (registered trademark))

[0562] Sentiment analysis engine (e.g., Microsoft Azure Emotion API)

[0563] 3D modeling software

[0564] Data processing and calculation

[0565] Server Action:

[0566] 1. Acquiring input data: The server receives the store size, shape, necessary facilities, and other conditions entered by the user via a smartphone or smart glasses.

[0567] 2. Use of generative AI model: The server generates multiple interior design proposals using a generative AI model (e.g., GPT-4) based on the input data.

[0568] 3. 3D modeling: The server generates data for displaying the generated design proposal in three dimensions using 3D modeling software.

[0569] Terminal handling:

[0570] 1. Displaying design proposals: A smartphone or smart glasses displays the 3D design proposals sent from the server.

[0571] 2. Emotion analysis: The smart device uses an emotion analysis engine to analyze the user's facial expressions and tone of voice when looking at a design proposal, and recognizes the user's emotions.

[0572] User Action:

[0573] 1. Providing feedback: Users provide feedback on the design proposals using voice and facial expressions.

[0574] 2. Review the re-adjustment: The user reviews the re-adjusted design proposal based on the results of sentiment analysis.

[0575] Examples and prompts

[0576] Examples:

[0577] The user puts on the smart glasses and voice-inputs the size, shape, and necessary facilities of the store. Based on this information, the server generates multiple interior design proposals and displays them in 3D on the smart glasses' display. If the user says, "This design is a little dark," the emotion analysis engine detects the dissatisfaction, and the server re-presents a brighter design proposal.

[0578] Example prompt for a generative AI model:

[0579] The store is 50 square meters in size and rectangular in shape. The necessary equipment is counters, shelves, and lighting. Based on these conditions, generate three different interior design proposals.

[0580] In this way, designers can efficiently draft plans and present three-dimensional floor plans to customers, providing optimal design proposals that reflect user sentiment and feedback in real time.

[0581] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0582] Step 1:

[0583] Obtaining input data

[0584] The server receives the store's size, shape, necessary facilities, and other conditions entered by the user through a smartphone or smart glasses. This input data is sent to the server and stored in a database. Specifically, the user enters the conditions using voice or touch input, and the data is sent to the server.

[0585] Step 2:

[0586] Using generative AI models

[0587] The server generates multiple interior design proposals using a generative AI model (e.g., GPT-4) based on the input data obtained in step 1. The input data is input to the generative AI model as a prompt sentence, and the design proposals are output in text format. Specifically, the prompt sentence is generated as follows:

[0588] The store is 50 square meters in size and rectangular in shape. The necessary equipment is counters, shelves, and lighting. Based on these conditions, generate three different interior design proposals.

[0589] The generated design proposals are stored on the server.

[0590] Step 3:

[0591] 3D modeling

[0592] The server generates data for displaying the design proposal generated in step 2 in 3D using 3D modeling software. Specifically, it converts the text-based design proposal into a 3D model that can be visually confirmed by the user. The generated 3D model data is sent from the server to the terminal.

[0593] Step 4:

[0594] Displaying design ideas

[0595] The terminal (smartphone or smart glasses) displays the 3D design proposal sent from the server. The user can check the three-dimensional interior design proposal through the smart device's display. Specifically, the 3D model is displayed on the smart glasses' display.

[0596] Step 5:

[0597] Emotion analysis

[0598] The device uses an emotion analysis engine (e.g., Microsoft Azure Emotion API) to analyze the user's facial expressions and tone of voice when viewing a design proposal, and recognizes the user's emotions. Specifically, the device's camera and microphone are used to capture the user's facial expressions and voice, and the results are sent to the emotion analysis engine. The analysis results are then sent to a server.

[0599] Step 6:

[0600] Providing feedback

[0601] Users can provide feedback on design proposals using voice and facial expressions. For example, if a user says, "This design is a little dark," the voice data is sent from the device to the server.

[0602] Step 7:

[0603] Re-adjusting the design

[0604] The server re-uses the generative AI model to refine the design proposal based on the sentiment analysis results obtained in step 5 and the feedback obtained in step 6. Specifically, it adds the sentiment analysis results to the prompt text and re-inputs it into the generative AI model:

[0605] The user said, "This design is a bit dark." Based on this, generate some brighter interior design ideas.

[0606] The re-adjusted design proposal is then re-modeled in 3D and sent to the device.

[0607] Step 8:

[0608] Check readjustment

[0609] The device displays the re-adjusted design proposal for the user to review again. Specifically, the re-adjusted 3D model is displayed on the smart glasses display. The user can review the re-adjusted design proposal and repeat this process until they are satisfied.

[0610] Example 2

[0611] Next, a description will be given of Example 2 of Form 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."

[0612] With conventional design systems, it was difficult for designers to provide floor plan proposals and interior designs that accurately reflected the user's emotions and desires. Furthermore, the selection of wall and floor materials and the generation of interior images that took the user's emotions into consideration were not automated, placing a heavy burden on designers and preventing an efficient design process. Furthermore, there was a lack of a way to check the generated interior images in real time, making it difficult to increase user satisfaction.

[0613] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0614] In this invention, the server includes: means for an architect to use in drafting plans and to show three-dimensional floor plan proposals to a customer; means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance; means for inputting conditions in accordance with building regulations in advance; means including an emotion engine that recognizes the user's emotions; means for the emotion engine to analyze the user's emotions and adjust the selection of wall and floor materials and the generation of images of fixtures and interior fittings based on the analyzed emotions; means for generating interior images using an image generation AI model based on information about the wall and floor materials selected by the architect; and means for transmitting the generated interior images to the architect's terminal and displaying them. This makes it possible to provide floor plan proposals and interior designs that accurately reflect the user's emotions and requests.

[0615] An "architect" is an engineer who specializes in designing buildings.

[0616] A "draft plan" is an early design drawing that shows the basic design concept and layout of a building.

[0617] A "three-dimensional floor plan" is a blueprint or model that represents the interior space of a building in three dimensions.

[0618] "Land size and orientation" refers to the area and orientation of the proposed construction site.

[0619] "Essential facilities" refers to the basic infrastructure and equipment that must be installed in a building.

[0620] "Condition tolerance" refers to the range of tolerance and the laxity of constraints in a design.

[0621] "Floor plan simulation" is the process of virtually testing the layout of the interior space of a building on a computer.

[0622] "Building laws" refer to legal regulations and standards regarding the design and construction of buildings.

[0623] An "emotion engine" is software or hardware that analyzes a user's emotions and adjusts the system's behavior based on the results.

[0624] An "image generation AI model" is an artificial intelligence algorithm that generates images based on input text or data.

[0625] "Reference knowledge" refers to information on standard materials and designs used in design.

[0626] A "terminal" is a device such as a computer or tablet used by a designer.

[0627] "User" refers to the final user or customer of the building designed by the architect.

[0628] MODE FOR CARRYING OUT THE INVENTION

[0629] This invention is a system that allows designers to provide floor plan proposals and interior designs that accurately reflect the user's feelings and desires. Specific embodiments of this system will be described below.

[0630] Hardware and software used

[0631] The server generates interior images using an image generation AI model based on information about the wall and floor materials selected by the designer. For image generation, an image generation AI model such as "DALL-E" is used. The server then sends the generated interior images to the designer's device.

[0632] The terminal sends information such as wall and floor materials selected by the architect to the server. It also has the function of displaying the generated images sent from the server. An operating system such as "Windows (registered trademark)" or "macOS (registered trademark)" is installed on the terminal.

[0633] Users express their feelings about the proposed floor plan and interior design. The emotion engine analyzes the user's emotions from their words and facial expressions, and adjusts the selection of wall and floor materials and the generation of fixtures and interior images based on those emotions.

[0634] Explanation of program processing

[0635] The server uses image generation AI to generate interior images based on "reference knowledge" such as the wall and floor materials selected by the architect. The generated images are presented to the architect. For example, if the architect selects "wood-grain flooring" and "white wall materials," the server inputs this information into the image generation AI and generates an interior image that matches the specified conditions. The generated images are sent to the architect's device, where they can be viewed.

[0636] The terminal sends information about the wall and floor materials selected by the designer to the server. It also has the function of displaying the generated images sent from the server. For example, the designer selects "wood-grain flooring" and "white wall materials" on the terminal and sends this information to the server. The server then sends the generated interior image to the terminal, where the designer can check it.

[0637] The user expresses their feelings about the proposed floor plan and interior. The emotion engine analyzes the user's emotions from their comments and facial expressions, and adjusts the selection of wall and floor materials and the generation of fixtures and interior images based on that. For example, if the user says, "I'd like a more subdued feel," the emotion engine analyzes this comment and the system selects wall and floor materials with more subdued colors and materials. For example, it selects "subdued wood-grain floor materials" and "light beige wall materials," and generates an interior image based on that.

[0638] Prompt Sentence Examples

[0639] Below are some example prompts to input to a generative AI model:

[0640] 1. "Generate an interior image of a living room with wood-grain flooring and white walls."

[0641] 2. "Generate an interior image of a living room with muted wood flooring and pale beige wall coverings."

[0642] Using these prompts, the image generation AI generates interior images that match the specified conditions.

[0643] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0644] Step 1:

[0645] The user expresses their feelings about the proposed floor plan and interior design. For example, they might say, "I'd like it to have a more calming feel." The device then sends the user's comments and facial expressions to the emotion engine. The emotion engine then analyzes the user's emotions and sends the results to the server.

[0646] Input: User's speech and facial expressions

[0647] Output: Parsed emotion data

[0648] Specifically, if a user says, "I'd like it to be more cheerful," the device converts this speech into text using speech recognition software (e.g., a speech recognition engine) and sends it to the emotion engine. The emotion engine then analyzes the "cheerful feeling" from the user's speech and sends the results to the server.

[0649] Step 2:

[0650] The designer selects "reference knowledge" such as wall and floor materials on the terminal. A list of wall and floor materials that the designer can choose from is displayed on the terminal. The designer selects the appropriate material from the list.

[0651] Input: Information on wall and floor materials selected by the architect

[0652] Output: Information on selected wall and floor materials

[0653] Specifically, the designer operates the interface on the terminal and selects "wood-grain flooring" and "white wall material." The terminal then prepares to send the selected information to the server.

[0654] Step 3:

[0655] The device sends information about the wall and floor materials selected by the designer to the server, which then generates prompt text to input into the image generation AI model based on the received information.

[0656] Input: Information on wall and floor materials selected by the architect

[0657] Output: Generated prompt statement

[0658] Specifically, the device sends information about "wood-grain flooring" and "white wall materials" to the server. Based on this information, the server generates a prompt message saying, "Please generate an interior image of a living room with wood-grain flooring and white wall materials."

[0659] Step 4:

[0660] The server inputs the generated prompt sentence into an image generation AI model (e.g., an image generation engine) to generate an interior image. The generated image is stored on the server.

[0661] Input: Generated prompt text

[0662] Output: Generated interior image

[0663] Specifically, the server inputs the prompt "Generate an interior image of a living room with wood-grain flooring and white walls" into the image generation AI model. The image generation AI model generates an interior image that meets the specified conditions and returns it to the server.

[0664] Step 5:

[0665] The server sends the generated interior image to the terminal, which displays the received image to the designer. The designer can then check the generated image and make further selections or adjustments as necessary.

[0666] Input: Generated interior image

[0667] Output: Interior image displayed on the device

[0668] Specifically, the server sends the generated interior image to the terminal. The terminal displays the received image to the designer, who then checks it. If the designer needs to make further adjustments, the same procedure is repeated.

[0669] (Application example 2)

[0670] Next, a description will be given of Application Example 2 of Form 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."

[0671] In conventional design systems, when designers create floor plan proposals, it is difficult to adjust them to reflect the user's emotions and preferences, making it difficult to increase user satisfaction. Furthermore, when selecting interior design in a physical store, it is not possible to make proposals that reflect the user's emotions in real time, making it difficult to make optimal choices. This creates a need for systems that can provide floor plan proposals and interior proposals that precisely meet the user's needs.

[0672] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0673] In this invention, the server includes: means for an architect to use in drafting plans and for showing three-dimensional floor plan proposals to customers; means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance; means for inputting conditions in accordance with building laws in advance; means including an emotion engine for analyzing the user's emotions and adjusting the proposal content; means for proposing optimal wall materials, floor materials, fixtures, and interior design to the user via a smart device; and means including an image generation AI for generating interior images based on the selected items. This makes it possible to propose floor plan proposals and interior design proposals that reflect the user's emotions in real time.

[0674] An "architect" is an engineer who specializes in designing buildings.

[0675] A "draft plan" is an early drawing or plan that shows the basic design concept of a building.

[0676] A "three-dimensional floor plan" is a blueprint or model that represents the interior space of a building in three dimensions.

[0677] "Land size" refers to the area of ​​the site on which a building is constructed.

[0678] "Orientation" refers to the direction in which a building is placed.

[0679] "Essential facilities" are the basic infrastructure and equipment that should be installed in a building.

[0680] "Condition tolerance" refers to the range or limits that are permissible in design and construction.

[0681] "Floor plan simulation" is the process of virtually testing the layout of the interior spaces of a building.

[0682] "Building laws" are legal regulations and standards governing the design and construction of buildings.

[0683] An "emotion engine" is a software module that analyzes the user's emotions and adjusts the system's behavior based on the results.

[0684] A "smart device" is an electronic device that has internet connectivity and advanced computing capabilities.

[0685] "Wall materials" are materials that make up the walls of buildings.

[0686] "Flooring" refers to materials that make up the floors of buildings.

[0687] "Fixtures" are fixed decorations and equipment installed inside a building.

[0688] "Interior" refers to the decoration and design of the interior space of a building.

[0689] "Image generation AI" is a technology that uses artificial intelligence to generate images.

[0690] A system for carrying out this invention comprises: means for an architect to use in drafting plans and to show a customer a three-dimensional floor plan; means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance; means for inputting conditions in accordance with building laws in advance; means including an emotion engine for analyzing the user's emotions and adjusting the content of proposals; means for proposing optimal wall materials, floor materials, fixtures, and interiors to the user via a smart device; and means including an image generation AI for generating interior images based on the selected items.

[0691] Hardware and software used

[0692] Smart devices: such as smart glasses or smartphones, capture images from the user's perspective and perform emotion analysis in real time.

[0693] EmotionEngine: A software module for analyzing user emotions.

[0694] ImageGenerator: A software module that generates interior images based on selected items.

[0695] ReferenceKnowledge: A database of wall materials, flooring materials, fixtures, and interior design provided by manufacturers.

[0696] Data processing and calculation

[0697] 1. Emotion Analysis: Images of users captured with smart devices are input into the Emotion Engine to analyze their emotions, allowing users to understand their preferences and needs in real time.

[0698] 2. Selection and Adjustment: Based on the analyzed emotions, the system selects the optimal wall materials, floor materials, fixtures, and interior design from ReferenceKnowledge. This enables the system to make optimal suggestions based on the user's emotions.

[0699] 3. Image generation: An interior image is generated using ImageGenerator based on the selected items, allowing for visually easy-to-understand suggestions to be presented to the user.

[0700] Specific examples

[0701] A user wears smart glasses and visits an interior design shop. When the user says, "I'd like it to have a brighter feel," the emotion engine analyzes the user's emotions, and the system selects bright-colored wall and floor materials, generates an interior image, and presents it to the user.

[0702] Prompt Sentence Examples

[0703] Analyze the user's emotions and select light-colored wall and floor materials. If the user says, "I'd like it to feel brighter," select light-colored wall and floor materials and generate an interior image.

[0704] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0705] Step 1:

[0706] A user wears a smart device (smart glasses or a smartphone) and visits an interior design shop. The smart device captures images from the user's point of view.

[0707] Input: An image captured from the user's point of view.

[0708] Output: The captured image data.

[0709] How it works: The smart device's camera captures images of the surroundings from the user's point of view in real time.

[0710] Step 2:

[0711] The captured image data is sent to the EmotionEngine, which analyzes the user's emotions.

[0712] Input: The captured image data.

[0713] Output: Parsed user emotion data.

[0714] Specific operation: EmotionEngine analyzes image data and identifies emotions from the user's facial expressions and voice.

[0715] Step 3:

[0716] Based on the analyzed emotional data, the optimal wall materials, flooring materials, fixtures, and interior design are selected from ReferenceKnowledge.

[0717] Input: Parsed user emotion data.

[0718] Output: Selection data for optimal wall materials, floor materials, fixtures, and interior design.

[0719] Specific operation: ReferenceKnowledge refers to the emotion data and selects items from the database that match the user's emotion.

[0720] Step 4:

[0721] Based on the selected items, an interior image is generated using ImageGenerator.

[0722] Input: Data for selecting the optimal wall materials, floor materials, fixtures, and interior.

[0723] Output: Generated interior image.

[0724] Specific operation: Based on the selected data, the ImageGenerator generates an interior image to present to the user.

[0725] Step 5:

[0726] The generated interior image is sent to the smart device and presented to the user.

[0727] Input: Generated interior images.

[0728] Output: Interior image presented to the user.

[0729] Specific operation: The generated interior image is displayed on the smart device display, allowing the user to visually confirm it.

[0730] Example 3

[0731] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0732] Conventional floor plan simulation systems have difficulty generating floor plan proposals that comply with building laws and local government ordinances, and are unable to automatically generate optimal floor plan proposals that reflect the user's emotions and feedback. This makes it difficult to provide floor plan proposals that meet the user's requirements.

[0733] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0734] In this invention, the server includes a means for an architect to use in drafting plans and for showing three-dimensional floor plan proposals to the customer, a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels, a means for inputting conditions in accordance with building laws in advance, a means for recognizing the user's emotions and automatically generating optimal floor plan proposals based on those emotions, and a means for analyzing the user's feedback and generating new floor plan proposals based on the analysis results. This makes it possible to generate floor plan proposals that do not violate laws and provide optimal floor plan proposals that correspond to the user's emotions.

[0735] An "architect" is an engineer who specializes in designing buildings.

[0736] A "draft plan" is an early design drawing that shows the basic design and layout of a building.

[0737] A "three-dimensional floor plan" is a blueprint that represents the interior space of a building in three dimensions.

[0738] "Land size and orientation" refers to the area of ​​land on which a building can be constructed and the direction in which the land faces.

[0739] "Essential facilities" are the basic facilities and equipment that should be installed in a building.

[0740] "Condition tolerance" refers to the range or limits of conditions that are acceptable in the design of a building.

[0741] "Floor plan simulation" is the process of virtually testing the layout of the interior spaces of a building.

[0742] "Building laws" are legal regulations and standards governing the design and construction of buildings.

[0743] "Local ordinances" are building rules and regulations that apply in a particular area.

[0744] "User's emotions" refer to the user's psychological reactions and feedback to the floor plan proposal.

[0745] An "optimal floor plan" is the layout of the interior space of a building that best suits the user's needs and feelings.

[0746] "Feedback" refers to opinions and impressions provided by users.

[0747] "Analysis results" are the conclusions and data drawn by the emotion engine based on user feedback.

[0748] The "new floor plan proposal" is the layout of the interior space of a building that has been redesigned to reflect user feedback and analysis results.

[0749] "Wall and floor materials" are materials used for the walls and floors of buildings.

[0750] "Reference knowledge" is information about building materials and designs provided by manufacturers.

[0751] An "image generation model" is an algorithm or program that allows a computer to generate images.

[0752] MODE FOR CARRYING OUT THE INVENTION

[0753] The present invention is a system for generating floor plan proposals that comply with building regulations and provide optimal floor plan proposals that correspond to the user's feelings. Specific embodiments of this system will be described below.

[0754] System configuration

[0755] This system consists of three main components: a server, a terminal, and a user.

[0756] The server stores legal information such as building laws and local ordinances in a database. The server uses Python to analyze the legal information and executes an algorithm to generate floor plan proposals. The server also uses TensorFlow to implement an emotion engine and analyze user feedback.

[0757] The device receives user input and sends it to the server. When the user provides feedback on the floor plan, the device sends the feedback to the emotion engine. The device communicates with the server using HTTP requests.

[0758] The user provides feedback on the proposed floor plan, for example, saying, "I want it to feel more open." This feedback is sent to the emotion engine via the device.

[0759] Program processing

[0760] The server references legal information stored in a database, such as building laws and local government ordinances, and generates floor plan proposals using Python scripts. For example, it determines the size and layout of rooms based on building laws.

[0761] The device receives the user's request and sends it to the server using an HTTP request. This request includes the user's request. The server sends the generated floor plan in JSON format to the device, and the device receives this data and displays it to the user.

[0762] The user provides feedback on the displayed floor plan. For example, the user may comment, "I want it to feel more open." The device then sends the user's feedback to the emotion engine. This feedback is sent as text data.

[0763] The emotion engine uses TensorFlow to analyze user feedback and understand the user's emotions. For example, from the feedback "I want a sense of openness," it can be determined that the user desires a large space. The emotion engine then sends the analysis results to the server in JSON format.

[0764] The server generates a new floor plan based on the analysis results received from the emotion engine. For example, it may enlarge the living room window and rearrange the rooms to create a more open feel. The new floor plan is then displayed to the user via their device.

[0765] Examples and prompts

[0766] Examples:

[0767] If a user provides feedback such as "I want a more open feeling," the emotion engine analyzes this feedback and understands the "open feeling" the user desires. Based on the analysis results, the server generates a floor plan that increases the open feeling by enlarging the living room window and rearranging the rooms. The new floor plan is displayed to the user via their device.

[0768] Example prompt sentence:

[0769] "If a user comments on a proposed floor plan that they would like it to be more open, please explain how the emotion engine analyzes this and how the server generates a floor plan."

[0770] This system can generate legally valid floor plan proposals and provide optimal floor plan proposals that match the user's feelings. The flow of the specification process in the third embodiment will be described with reference to FIG.

[0771] Program processing flow

[0772] Step 1:

[0773] The user requests a floor plan simulation.

[0774] Input: The user inputs "I would like to see the floor plan for a 3LDK apartment" through the terminal interface.

[0775] Specific operation: The user selects the type of floor plan and conditions on the device screen and sends a simulation request.

[0776] Step 2:

[0777] The terminal sends the user's request to the server.

[0778] Input: User request (e.g., "3LDK floor plan")

[0779] Output: Data sent to the server as an HTTP request

[0780] Specific operation: The terminal receives user input, generates an HTTP request, and sends it to the server.

[0781] Step 3:

[0782] The server generates a floor plan based on the legal information.

[0783] Input: User request, legal information stored in the database

[0784] Output: Generated floor plan (JSON format)

[0785] How it works: The server uses Python scripts to analyze legal information and generate floor plans, for example, determining room sizes and layouts based on building laws.

[0786] Step 4:

[0787] The server sends the generated floor plan to the terminal.

[0788] Input: Generated floor plan (JSON format)

[0789] Output: Floor plan data sent to the device

[0790] Specific operation: The server sends the generated floor plan in JSON format to the device. The device receives this data and displays it to the user.

[0791] Step 5:

[0792] The user provides feedback on the floor plan.

[0793] Input: User feedback on the displayed floor plan (e.g., "I want it to feel more open")

[0794] Output: Feedback text data

[0795] Specific operation: The user looks at the displayed floor plan and enters feedback. For example, the user may comment, "I want it to feel more open."

[0796] Step 6:

[0797] The device sends the user's feedback to the emotion engine.

[0798] Input: User feedback (text data)

[0799] Output: Feedback data sent to the emotion engine

[0800] Specific operation: The device receives the user's feedback and sends it to the emotion engine. This feedback is sent as text data.

[0801] Step 7:

[0802] The emotion engine analyzes the user's emotions.

[0803] Input: User feedback (text data)

[0804] Output: Analysis results (user's feelings and specific requests)

[0805] Specific operation: The emotion engine uses TensorFlow to analyze user feedback and understand the user's emotions. For example, from the feedback "I want a sense of openness," it understands that the user desires a large space.

[0806] Step 8:

[0807] The emotion engine sends the analysis results to the server.

[0808] Input: Analysis results (user's feelings and specific requests)

[0809] Output: Analysis result data sent to the server

[0810] Specific operation: The emotion engine sends the analysis results in JSON format to the server.

[0811] Step 9:

[0812] The server generates new floor plan proposals based on the analysis results.

[0813] Input: Analysis results (user's feelings and specific requests)

[0814] Output: New floor plan (JSON format)

[0815] Specific operation: The server generates a new floor plan based on the analysis results received from the emotion engine. For example, it enlarges the living room window and rearranges the rooms to create a more open feeling.

[0816] Step 10:

[0817] The server sends the new floor plan to the device.

[0818] Input: New floor plan (JSON format)

[0819] Output: New floor plan data sent to the device

[0820] Specific operation: The server sends the new floor plan in JSON format to the device. The device receives this data and displays it to the user.

[0821] (Application example 3)

[0822] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0823] Conventional floor plan design systems struggled to generate floor plan proposals that complied with building laws and local government ordinances, and were unable to reflect users' feelings and requests in real time. This made it difficult to provide optimal floor plan proposals that would increase user satisfaction. Furthermore, when designers created plans, there was a lack of a way to present users with three-dimensional floor plan proposals in real time. This made it impossible to respond quickly to user requests, resulting in an inefficient design process.

[0824] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0825] In this invention, the server includes: means for an architect to use in drafting plans and for showing three-dimensional floor plan proposals to customers; means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels; means for inputting conditions in accordance with building laws in advance; means for including an emotion engine that recognizes the user's emotions, analyzing the emotions from the user's reactions, and automatically generating optimal floor plan proposals based on those emotions; and means for displaying floor plan proposals in real time using a smart device. This makes it possible to reflect the user's emotions and requests in real time and provide optimal floor plan proposals that comply with building laws.

[0826] An "architect" is an engineer who specializes in designing buildings.

[0827] A "draft plan" is an early drawing or plan that shows the basic design and concept of a building.

[0828] A "three-dimensional floor plan" is a blueprint or model that represents the internal structure of a building in three dimensions.

[0829] "Land size and orientation" refers to the area and orientation of the site on which the building will be constructed.

[0830] "Essential facilities" refers to the basic infrastructure and equipment that must be installed in a building.

[0831] "Condition tolerance" refers to the range and degree of constraints that are permissible in a design.

[0832] "Floor plan simulation" is the process of virtually arranging the internal structure of a building and verifying that arrangement.

[0833] "Building laws" refer to legal regulations and standards regarding the design and construction of buildings.

[0834] An "emotion engine" is software that analyzes the user's emotions and controls the system's operation based on the results.

[0835] "Smart devices" refer to electronic devices that have internet connectivity and advanced computing capabilities.

[0836] "Real-time display" refers to the instantaneous presentation of data or information to a user.

[0837] A system for carrying out this invention includes a means for an architect to use in drafting a plan and to show a customer a three-dimensional floor plan proposal, a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels, a means for inputting conditions in accordance with building laws in advance, a means including an emotion engine that recognizes the user's emotions, analyzing emotions from the user's reactions, and automatically generating an optimal floor plan proposal based on the emotions, and a means for displaying the floor plan proposal in real time using a smart device.

[0838] System Program

[0839] The server executes the following program: First, it uses the camera on the smart device (e.g., smart glasses) to capture a picture of the user's face and acquires the video data. Next, it uses an emotion engine to analyze the user's emotions. It uses voice recognition technology to convert the user's comments (e.g., "I want a more open feeling") into text data and analyzes it. It then references a legal information database to generate a layout plan that complies with building laws and local government ordinances. The generated layout plan is displayed in real time on the smart device's display.

[0840] Hardware and software used

[0841] Hardware: Smart glasses (camera, display)

[0842] Software: OpenCV (cv2), emotion engine, layout generation engine, legal information database

[0843] Specific examples

[0844] When a user wears smart glasses and says, "I want more openness" while walking around the store, the system analyzes the user's emotions and proposes open layouts in real time that comply with building regulations. For example, if a user says, "I want larger windows," the system analyzes that request, generates a floor plan that includes larger windows, and displays it on the smart glasses' display.

[0845] Prompt Sentence Examples

[0846] "Design an application that allows a user to wear smart glasses and walk around a store, analyzing their speech and emotions, and then recommending optimal layout options in real time that comply with building regulations."

[0847] In this way, it is possible to reflect the user's feelings and requests in real time and provide optimal floor plan proposals that comply with building regulations.

[0848] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0849] Step 1:

[0850] The server captures the user's face using the smart glasses' camera and acquires the video data. The input is the camera video, and the output is the image data of the user's face. This image data is used for subsequent emotion analysis.

[0851] Step 2:

[0852] The server inputs the acquired image data of the user's face into the emotion engine and analyzes the user's emotions. The input is image data of the user's face, and the output is analyzed emotion data. The emotion engine analyzes the image data and identifies the user's emotion (e.g., joy, sadness, surprise, etc.).

[0853] Step 3:

[0854] The user speaks through the smart glasses. The terminal converts the user's speech into text data using speech recognition technology. The input is voice data, and the output is text data. This text data is used to analyze the user's request.

[0855] Step 4:

[0856] The server analyzes the text data and identifies the user's desires. The input is text data, and the output is the user's desire data. For example, a statement such as "I want a more open feeling" is identified as a "desire for a more open feeling."

[0857] Step 5:

[0858] The server references a legal information database and generates a layout plan that complies with building laws and local government ordinances. The input is the user's request data and legal information, and the output is a layout plan. The layout generation engine generates the optimal floor plan plan based on the user's request and legal information.

[0859] Step 6:

[0860] The server displays the generated layout plan on the smart glasses display in real time. The input is the layout plan, and the output is the floor plan displayed on the smart glasses display. The user can check the proposed floor plan in real time.

[0861] In this way, it is possible to reflect the user's feelings and requests in real time and provide optimal floor plan proposals that comply with building regulations.

[0862] 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.

[0863] 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> ) 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.

[0864] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0865] 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.

[0866] [Second embodiment]

[0867] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0868] 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.

[0869] 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).

[0870] 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.

[0871] 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.

[0872] 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).

[0873] 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.

[0874] 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.

[0875] 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.

[0876] 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.

[0877] In the smart glasses 214, 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.

[0878] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0879] "Example 1"

[0880] The system of the present invention is used by architects to create draft plans. Specifically, the architect inputs the size and orientation of the land, the necessary facilities, and other conditions and tolerances for those conditions into the system. Based on this information, the system automatically generates multiple floor plan simulations and presents them to the architect. This allows the architect to efficiently show the client three-dimensional floor plan proposals.

[0881] "Example 2"

[0882] Furthermore, the system of this invention has the ability to select only from "reference knowledge" prepared by manufacturers of wall and flooring materials. Designers can use this function to select not only the floor plan but also fixtures and interiors that fit their image. The selected fixtures and interiors are generated by image generation AI and presented to the designer. This allows the designer to provide a floor plan proposal that more precisely meets the customer's requests.

[0883] "Example 3"

[0884] The system of the present invention also has the ability to pre-load conditions that comply with building laws. Specifically, the system stores legal information such as building laws and local government ordinances in a database, and takes this legal information into account when generating floor plan simulations. This makes it possible to generate floor plan proposals that do not violate laws.

[0885] The processing flow of each embodiment will be described below.

[0886] "Example 1"

[0887] Step 1: The architect inputs the size and orientation of the land, the necessary facilities, and other conditions and tolerances for the conditions into the system.

[0888] Step 2: Based on this information, the system automatically generates multiple floor plan simulations.

[0889] Step 3: The generated floor plan simulation is presented to the architect, who then uses it to present a three-dimensional floor plan proposal to the client.

[0890] "Example 2"

[0891] Step 1: The designer uses the system's "reference knowledge" function to select wall and floor materials.

[0892] Step 2: The selected features and interior are generated using image generation AI.

[0893] Step 3: The generated images of fixtures and interiors are presented to the architect, who then uses them to present a floor plan to the client.

[0894] "Example 3"

[0895] Step 1: The system maintains legal information such as building codes and local government ordinances in a database.

[0896] Step 2: The system takes this legal information into account when generating the simulated floor plan.

[0897] Step 3: This makes it possible to generate floor plan proposals that do not violate any laws.

[0898] Example 1

[0899] Next, a description will be given of Example 1 of Form 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."

[0900] Previous systems used by architects to draft plans had limited means of showing floor plan proposals in three dimensions, making it difficult to efficiently propose them to clients. Furthermore, even if the land size, orientation, necessary facilities, and other conditions and their tolerances were input, the system lacked the functionality to automatically generate multiple floor plan simulations. Furthermore, there were insufficient means to consider conditions in accordance with building laws in advance, placing a heavy burden on architects.

[0901] 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. In this invention, the server includes a means for receiving input data and performing preprocessing, a means for inputting a prompt sentence to the generation AI model and generating a floor plan simulation, and a means for visualizing the generated floor plan simulation. This allows the architect to efficiently generate multiple floor plan simulations and propose them to the customer in three dimensions. In addition, by taking into account the conditions in accordance with building laws in advance, the burden on the architect can be reduced.

[0902] An "architect" is an engineer who specializes in designing buildings.

[0903] "Drafting a plan" is the initial stage of creating a basic design for a building.

[0904] The "customer" is the client who requests the architect to design a building.

[0905] A "three-dimensional floor plan" is a blueprint that represents the floor plan of a building in three dimensions.

[0906] "Land size" refers to the area of ​​land available for building a structure.

[0907] "Land orientation" refers to the direction of the land on which a building is to be constructed.

[0908] "Necessary facilities" are facilities and equipment that must be installed in a building.

[0909] "Other conditions" are additional requirements or constraints that must be taken into account in the design of a building.

[0910] "Condition tolerance" refers to the degree to which conditions are applied flexibly in the design.

[0911] "Floor plan simulation" is the process of virtually calculating and verifying the floor plan of a building.

[0912] "Building laws" are legal regulations and standards governing the design and construction of buildings.

[0913] "Input data" is information provided by a user to a system.

[0914] "Preprocessing" is the process of analyzing input data and converting it into a format suitable for subsequent processing.

[0915] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate data.

[0916] A "prompt sentence" is an instruction sentence input to a generative AI model.

[0917] "Visualization" is the process of representing data or information visually.

[0918] "User" refers to the designers and other users of this system.

[0919] This invention is a system that allows architects to create draft plans and show three-dimensional floor plan proposals to clients. The system automatically generates multiple floor plan simulations and presents them to architects by inputting the land size and orientation, necessary facilities, and other conditions and tolerances for those conditions.

[0920] The user (architect) first uses a device (PC or tablet) to input the land size, orientation, required facilities, other conditions, and their tolerance levels. For example, the user might input "Land size: 200 square meters," "Land orientation: south-facing," "Required facilities: 3LDK, 2 parking spaces, garden," "Other conditions: barrier-free," and "Condition tolerance level: high."

[0921] The terminal sends the data entered by the user to the server. Specifically, the terminal converts the input data into JSON format and sends it to the server using an HTTP request. The server receives the data sent from the terminal and performs preprocessing. Preprocessing involves formatting the data and removing unnecessary information.

[0922] The server generates a prompt based on the preprocessed data and inputs it into a generative AI model (for example, a general-purpose generative AI model). An example of a prompt might be, "Please propose a floor plan for a 200-square-meter plot of land facing south, with 3 bedrooms, a living room, kitchen, kitchen, and kitchen, two parking spaces, and a garden. The conditions are highly tolerant." The generative AI model generates multiple floor plan simulations based on this prompt.

[0923] The server inputs the floor plan simulation obtained from the generative AI model into 3D modeling software (e.g., general-purpose 3D modeling software) and visualizes it. This displays the proposed floor plan in three dimensions. The visualized data is generated as an image file or 3D model file and sent to the terminal as an HTTP response.

[0924] The device displays the visualized data received from the server to the user, who can then check multiple floor plan proposals on the device screen and efficiently propose them to the customer.

[0925] This system allows designers to efficiently generate multiple floor plan simulations and propose them to customers in three dimensions. It also reduces the burden on designers by taking into account building regulations in advance.

[0926] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0927] Step 1:

[0928] The user inputs the input data into the terminal. The user inputs the land size, orientation, required facilities, other conditions, and their tolerance levels into the terminal. For example, the user might input "Land size: 200 square meters," "Land orientation: south-facing," "Required facilities: 3LDK, 2 parking spaces, garden," "Other conditions: barrier-free," and "Condition tolerance level: high." The input data is collected through an input form on the terminal.

[0929] Step 2:

[0930] The terminal sends the input data to the server. The terminal converts the data entered by the user into JSON format and sends it to the server using an HTTP request. The input data is sent to the server as a JSON object containing the land size, orientation, required facilities, other conditions, and their tolerances.

[0931] Step 3:

[0932] The server receives the data and performs preprocessing. The server receives the JSON data sent from the device and formats the data and removes unnecessary information. For example, it checks the format of the input data and whether any information is missing. The preprocessed data is converted into a format suitable for the generative AI model.

[0933] Step 4:

[0934] The server inputs a prompt statement into the generative AI model and generates a floor plan simulation. The server generates a prompt statement based on the preprocessed data and inputs it into the generative AI model. An example of a prompt statement might be, "Please propose a floor plan for a 200 square meter plot of land facing south, with 3 bedrooms, living room, kitchen, kitchenette, parking for two cars, and a garden, and that is barrier-free. The conditions are highly tolerant." The generative AI model generates multiple floor plan simulations based on this prompt statement. The generated floor plan simulations are returned to the server in text or data format.

[0935] Step 5:

[0936] The server visualizes the generated floor plan simulation using 3D modeling software. The server inputs the floor plan simulation obtained from the generative AI model into 3D modeling software and visualizes it. For example, general-purpose 3D modeling software is used to display the proposed floor plan in three dimensions. The visualized data is generated as an image file or a 3D model file.

[0937] Step 6:

[0938] The server sends the visualized data to the terminal. The server sends the visualized floor plan simulation data to the terminal as an HTTP response. The visualization data is sent to the terminal as an image file or a 3D model file.

[0939] Step 7:

[0940] The device displays a floor plan simulation to the user. The device then displays the visualization data received from the server to the user. The user can check multiple floor plan proposals on the device screen and make efficient proposals to the customer. For example, a 3D model can be displayed on the device display, allowing the user to freely rotate and zoom.

[0941] (Application example 1)

[0942] Next, a description will be given of Application Example 1 of Form 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."

[0943] Conventional floor plan simulation systems used by designers have difficulty efficiently presenting three-dimensional floor plan proposals, even when users input conditions such as the size and orientation of the land and the necessary equipment. Furthermore, there was a lack of systems that could automatically generate optimal furniture layout plans and allow users to check them in a 3D view when simulating the layout and furniture arrangement of their home. This made it difficult for users to efficiently arrange and purchase furniture.

[0944] 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.

[0945] In this invention, the server includes: a means for an architect to draft a plan and show the customer a three-dimensional floor plan; a means for presenting multiple floor plan simulations by selecting the land size and orientation, necessary facilities, and other conditions and their tolerance; a means for inputting conditions in accordance with building regulations in advance; a means for a generative AI model to generate multiple furniture arrangement plans based on the floor plan information entered by the user; a means for rendering and displaying the generated plans as 3D models; and a means for saving the plans selected by the user and generating a shopping list. This enables users to efficiently simulate the floor plan and furniture arrangement of their home, check the optimal furniture arrangement plan in a 3D view, and generate a shopping list.

[0946] An "architect" is an engineer who specializes in designing buildings and interiors.

[0947] A "draft plan" is a document or drawing created by an architect at an early stage that shows the basic concept and ideas of the design.

[0948] A "three-dimensional floor plan" is a blueprint or model that represents the interior space of a building in three dimensions.

[0949] "Land size" refers to the area of ​​the site on which the building is constructed.

[0950] "Orientation" is information that indicates the direction in which the building faces.

[0951] "Necessary facilities" refers to the basic facilities and equipment that should be installed in a building.

[0952] "Condition tolerance" refers to the range and flexibility of conditions that are acceptable in the design.

[0953] "Floor plan simulation" is a process of virtually testing the layout of the interior space of a building based on input conditions.

[0954] "Building laws" refer to legal regulations and standards governing the design and construction of buildings.

[0955] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate data based on specific conditions.

[0956] A "furniture arrangement plan" is a design proposal that shows how furniture should be arranged in the interior space of a building.

[0957] A "3D model" is digital data that represents an object or space in three-dimensional space.

[0958] "Rendering" is the process of generating images to visually represent a 3D model.

[0959] A "shopping list" is a document or data that lists the furniture and equipment selected by a user.

[0960] The system for implementing this invention is used by architects to draft plans and show three-dimensional floor plan proposals to clients. The system automatically generates and presents multiple floor plan simulations by inputting the land size and orientation, necessary facilities, and other conditions and tolerances for those conditions. Furthermore, based on the floor plan information entered by the user, a generative AI model generates multiple furniture layout plans, which are then rendered and displayed as 3D models.

[0961] Hardware and software used

[0962] 1. Hardware:

[0963] Smartphone (iOS or Android)

[0964] GPU for 3D rendering

[0965] 2. Software:

[0966] Development environment: Unity (3D rendering), TensorFlow (generative AI model)

[0967] Database: Firebase (storing user data)

[0968] API: Google Maps API (location information acquisition)

[0969] Data processing and calculation

[0970] 1. User Input:

[0971] Using a smartphone application, users input the land size, orientation, required amenities, and other conditions and tolerances for those conditions.

[0972] 2. Generative AI Model:

[0973] The server uses a generative AI model to generate multiple furniture layout plans based on the floor plan information entered by the user.

[0974] The generative AI model is built using TensorFlow and generates optimal furniture placement plans based on user input.

[0975] 3. 3D rendering:

[0976] The server renders the generated furniture layout plan as a 3D model and displays it on a smartphone.

[0977] Unity is used for 3D rendering to generate visually realistic models.

[0978] 4. Data storage and shopping list generation:

[0979] The plan selected by the user is stored in Firebase for future reference.

[0980] It also generates a shopping list based on the selected plan and provides it to the user.

[0981] Specific examples

[0982] 1. User Input:

[0983] Land size: 100 square meters

[0984] Orientation: South

[0985] Required facilities: kitchen, living room, bathroom, bedroom

[0986] 2. Prompt for the generative AI model:

[0987] The land area is 100 square meters, facing south. The required facilities are a kitchen, living room, bathroom, and bedroom. Please generate the optimal furniture layout plan based on these conditions.

[0988] 3. Example output:

[0989] Plan 1: Open floor plan with integrated kitchen and living room

[0990] Plan 2: A plan that prioritizes privacy with a separate living room and bedroom

[0991] In this way, the system provides a generative AI model that automatically generates multiple furniture layout plans based on information entered by the user and allows users to check them in a 3D view. This allows users to efficiently simulate their home layout and furniture placement, check the optimal furniture layout plan in 3D view, and generate a shopping list.

[0992] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0993] Step 1:

[0994] The user launches the smartphone application and inputs the land size, orientation, required facilities, and other conditions and tolerances for those conditions. The input data is sent from the smartphone device to the server. The input data includes the land size (e.g., 100 square meters), orientation (e.g., facing south), and required facilities (e.g., kitchen, living room, bathroom, bedroom).

[0995] Step 2:

[0996] The server generates a prompt for the generative AI model based on the received input data. The generated prompt reflects the conditions entered by the user. For example, a prompt might be generated that reads, "The land is 100 square meters in size and faces south. The required facilities are a kitchen, living room, bathroom, and bedroom. Based on these conditions, please generate the optimal furniture layout plan."

[0997] Step 3:

[0998] The server inputs the generated prompt sentences into a generative AI model to generate multiple furniture layout plans. The generative AI model is built using TensorFlow and generates the optimal furniture layout plan based on the input prompt sentences. The output is multiple furniture layout plans.

[0999] Step 4:

[1000] The server renders the generated furniture layout plan as a 3D model using Unity, generating a visually realistic 3D model. The output is a 3D model.

[1001] Step 5:

[1002] The server then sends the rendered 3D model to the smartphone device and displays it to the user, who can then view the generated furniture layout plans in 3D through the smartphone application.

[1003] Step 6:

[1004] The user selects the most suitable plan from the displayed furniture layout plans, and the selected plan is sent from the smartphone device to the server.

[1005] Step 7:

[1006] The server saves the selected plan in Firebase for future reference, and generates a shopping list based on the selected plan and provides it to the user. The shopping list includes a list of furniture and equipment included in the selected plan.

[1007] Through the above processing steps, users can efficiently simulate the layout and furniture arrangement of their home, check the optimal furniture arrangement plan in a 3D view, and generate a shopping list.

[1008] Example 2

[1009] Next, a description will be given of Example 2 of Form 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."

[1010] With conventional design support systems, it was difficult for designers to concretely express detailed images of floor plans and interiors, and it was also difficult to precisely respond to customer requests. Furthermore, there were limited options for wall and floor materials, restricting design freedom. This often prevented designers from making satisfactory proposals to customers, making the design process inefficient.

[1011] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1012] In this invention, the server includes means for the designer to select wall and floor materials from reference knowledge, means for the designer to input images of the floor plan and interior, means for the server to collect data on the selected fixtures and interior, means for the server to generate images using image generation AI, means for the server to present the generated images to the designer, and means for the designer to check the generated images and make corrections as necessary. This enables the designer to quickly and accurately generate and propose detailed images of the floor plan and interior based on the customer's requests.

[1013] An "architect" is an engineer who specializes in designing buildings and designs floor plans and interiors.

[1014] A "draft plan" is an early stage plan that shows the basic design and layout of a building.

[1015] A "three-dimensional floor plan" is a blueprint or model that represents the floor plan of a building in three dimensions.

[1016] "Land size and orientation" refers to the area and orientation of the land on which the building will be constructed.

[1017] "Essential facilities" refers to the basic facilities and equipment that should be installed in a building.

[1018] "Condition tolerance" refers to the range and flexibility of conditions that are acceptable in the design.

[1019] "Floor plan simulation" is the process of virtually trying out a designed floor plan and visually confirming the results.

[1020] "Building laws" refer to legal regulations and standards governing the design and construction of buildings.

[1021] "Reference knowledge" refers to standard information and data provided by manufacturers of wall and flooring materials, etc.

[1022] "Image generation AI" refers to artificial intelligence technology that generates images based on input text or data.

[1023] "Fixtures" refers to decorations and structures installed inside and outside a building.

[1024] "Interior" refers to the design and decoration of the interior space of a building.

[1025] "Collecting data" refers to the process of gathering and organizing the necessary information or data.

[1026] "Generating an image" refers to creating a visual picture or model based on input information.

[1027] "Modifying" refers to making changes or adjustments to the generated image or design.

[1028] This invention is a system used by architects when designing the layout and interior of buildings, and allows them to select from "reference knowledge" provided by manufacturers of wall and flooring materials, among other things, and generate specific images using image generation AI. The system is operated by the user (architect) using a dedicated terminal, and the server collects data and generates images.

[1029] Hardware and software used

[1030] Device: A device such as a computer or tablet used by an architect.

[1031] Server: A server for collecting data, processing, and generating images.

[1032] Image generation AI: Image generation models such as DALL-E.

[1033] Data processing and calculation

[1034] 1. A user logs into the system

[1035] The user accesses the system using a terminal and enters their user ID and password on the login screen. The server performs authentication, and if authentication is successful, the main screen is displayed.

[1036] 2. The user selects wall and floor materials from reference knowledge.

[1037] The user browses through a list of wall and flooring materials offered by manufacturers on the system interface and selects the desired material, which is then sent to the server and temporarily stored.

[1038] 3. The user inputs the floor plan and interior image

[1039] The user inputs a specific image of the floor plan and interior into the text box. For example, they can input a request such as "I want wood-grain flooring in the living room and white walls."

[1040] 4. The server collects data on the selected features and interior.

[1041] The server collects data on the selected wall and floor materials from the database, including images of the materials, texture information, and manufacturer information.

[1042] 5. The server generates the image using image generation AI

[1043] The server sends a prompt to the image generation AI based on the collected data and the image entered by the user. The prompt specifically describes the user's request. The image generation AI analyzes the prompt and generates a corresponding image.

[1044] 6. The server presents the generated image to the user

[1045] The server receives the images generated by the image generation AI and sends them to the user's device, where the user can view the generated images on the system interface.

[1046] 7. The user checks the generated image and makes corrections if necessary.

[1047] The user can review the generated image and make any necessary modifications or regenerate it, for example, changing the wall color or adjusting the furniture placement. Once modifications are complete, the user saves the final design and is ready to present it to the client.

[1048] Specific examples

[1049] For example, if an architect inputs a request such as "Use wood-grain flooring and white walls in the living room," the system will process it as follows:

[1050] 1. The designer logs into the system.

[1051] 2. The architect selects wood-grain flooring and white wall coverings from reference knowledge.

[1052] 3. The architect inputs an image of "wood-grain flooring in the living room and white walls."

[1053] 4. The server retrieves images and texture information for "white wall material" and "wood-grain floor material" from the database.

[1054] 5. The server sends the prompt "Use wood-grain flooring and white walls in the living room" to the image generation AI and receives the generated image.

[1055] 6. The server sends the generated image to the designer's terminal, and the designer checks the image on the interface.

[1056] 7. The architect types "change the wall color to blue" and sends the prompt to the image generation AI again. A new image is generated and presented to the architect.

[1057] Prompt Sentence Examples

[1058] "The living room will have wood-grain flooring and white walls. The furniture will be modern, with a gray sofa and a glass table."

[1059] By inputting this prompt into the image generation AI, an image of the living room the designer envisions is generated.

[1060] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1061] Step 1:

[1062] A user logs in to the system.

[1063] Input: User ID and password.

[1064] Data processing: The server checks the entered user ID and password against the database and performs authentication.

[1065] Output: If authentication is successful, display the main screen.

[1066] Specific operation: The user enters the user ID and password on the login screen of the terminal and clicks the "Login" button. The server accesses the database and verifies the authentication information. If authentication is successful, the main screen is displayed on the terminal.

[1067] Step 2:

[1068] The user selects wall and floor materials from reference knowledge.

[1069] Input: A list of wall and flooring materials.

[1070] Data processing: The server temporarily stores information about the selected wall and floor materials.

[1071] Output: Information about the selected wall and floor coverings.

[1072] Specific operation: The user selects wall and floor materials using drop-down menus and search functions on the system interface. The selected materials are sent to the server and temporarily stored.

[1073] Step 3:

[1074] The user inputs the floor plan and interior image.

[1075] Input: A concrete image (text) of the floor plan and interior.

[1076] Data processing: The server analyzes the input image and generates a prompt.

[1077] Output: The generated prompt statement.

[1078] Specific behavior: The user enters "I want wood-effect flooring and white walls in the living room" into the text box and clicks the "Submit" button. The server parses the entered text and generates a prompt.

[1079] Step 4:

[1080] The server collects data on the selected fixtures and interiors.

[1081] Input: Information about the selected wall and floor covering.

[1082] Data processing: The server retrieves images, texture information, and manufacturer information of the selected material from the database.

[1083] Output: Collected data.

[1084] Specific operation: The server accesses the database and obtains images, texture information, and manufacturer information of the selected wall or floor material.

[1085] Step 5:

[1086] The server generates the image using image generation AI.

[1087] Input: Prompt statement and collected data.

[1088] Data processing: The server sends a prompt to the image generation AI, which then generates a corresponding image.

[1089] Output: The generated image.

[1090] Specific operation: The server sends the prompt "Use wood-grain flooring and white walls in the living room" to the image generation AI, which analyzes the prompt and generates the corresponding image.

[1091] Step 6:

[1092] The server presents the generated image to the user.

[1093] Input: The generated image.

[1094] Data processing: The server sends the generated image to the user's device.

[1095] Output: The image displayed on the user's device.

[1096] Specific operation: The server sends the generated image to the user's terminal, and the user checks the image on the interface.

[1097] Step 7:

[1098] The user checks the generated image and makes corrections as necessary.

[1099] Input: User correction instructions.

[1100] Data processing: The server receives the correction instructions and sends the prompt text to the image generation AI again.

[1101] Output: The rectified image.

[1102] Specific operation: The user checks the generated image, inputs "change the wall color to blue," and sends the prompt to the image generation AI again. A new image is generated and presented to the user.

[1103] (Application example 2)

[1104] Next, a description will be given of Application Example 2 of Form 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."

[1105] With conventional design systems, when proposing floor plans and interiors, designers had to manually select materials and furniture and create images, which was time-consuming and labor-intensive. Even in the interior design of brick-and-mortar stores, it was difficult for store owners to have a concrete image, making it difficult to confirm and modify the design. This made it difficult to precisely meet customer requests, potentially reducing satisfaction.

[1106] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1107] In this invention, the server includes: a means for an architect to draft a plan and show a three-dimensional floor plan to a customer; a means for presenting multiple floor plan simulations by selecting the size and orientation of the lot, necessary equipment, and other conditions and their tolerance; a means for inputting conditions in accordance with building regulations in advance; a means for selecting only from "reference knowledge" provided by manufacturers of wall and floor materials, etc., and then using image generation AI to generate not only the floor plan but also fixtures and interior fittings that match the image; a means for supporting the interior design of a physical store by allowing a store owner to select wall materials, flooring materials, furniture, etc. and simulate the store layout and design; a means for using image generation AI to generate a realistic image of the store interior based on the selected materials and furniture and present it to the store owner; and a means for the store owner to review and modify the generated image. This enables architects and store owners to efficiently create floor plans and interior designs that precisely meet customer requests.

[1108] An "architect" is an engineer who specializes in designing buildings and interiors.

[1109] A "draft plan" is a basic design concept or plan created by an architect in the early stages.

[1110] A "three-dimensional floor plan" is a blueprint or model that represents the internal structure of a building in three dimensions.

[1111] The land area refers to the area of ​​the site on which a building is constructed.

[1112] "Orientation" refers to information that indicates the direction in which a building faces.

[1113] "Essential facilities" refers to the basic infrastructure and equipment that must be installed in a building.

[1114] "Condition tolerance" refers to the range and flexibility of conditions that are allowed in a design.

[1115] "Floor plan simulation" is a process in which an architect virtually tests out design proposals to find the optimal floor plan.

[1116] "Building laws" refer to legal regulations and standards regarding the design and construction of buildings.

[1117] "Reference knowledge" refers to information and data on wall and floor materials provided by manufacturers.

[1118] "Image generation AI" is a technology that uses artificial intelligence to generate images from text or data.

[1119] A "brick and mortar store" is a commercial establishment or store that exists in a physical location.

[1120] "Store owner" refers to the owner or manager of a physical store.

[1121] "Materials" refers to materials and parts used in architecture and interior design.

[1122] "Furniture" refers to interior items placed inside a building.

[1123] "Layout" refers to the design of the layout and structure within a building or store.

[1124] "Simulation" is a process of virtually recreating a real-world situation and conducting trial and error.

[1125] "Realistic store interior image" refers to a visual representation that faithfully reproduces the interior of an actual store.

[1126] "Verification and correction" refers to the process of reviewing the generated designs and images and making changes as necessary.

[1127] The system for implementing this invention aims to enable designers and store owners to efficiently create floor plans and interior designs that precisely meet customer needs. This system is realized using the following hardware and software.

[1128] Hardware

[1129] Server: Processes data and runs image-generating AI models.

[1130] Devices: Devices such as smartphones and tablets used by designers and store owners.

[1131] Network: An internet connection to connect the server and your device.

[1132] software

[1133] Image generation AI model: Uses OpenAI's API to generate images based on prompt text.

[1134] Database: Stores "reference knowledge" such as wall and floor materials.

[1135] User interface: An application that allows designers and store owners to select materials and layouts and check simulation results.

[1136] Data processing and calculation

[1137] 1. Selection of materials and conditions: The user (architect or store owner) selects conditions such as wall materials, flooring materials, furniture, and layout.

[1138] 2. Generate prompt sentence: Generate prompt sentence based on selected conditions.

[1139] 3. Image generation: The generated prompt sentences are input into an image generation AI model to generate a realistic image of the store interior.

[1140] 4. Image presentation: The generated image is presented to the user for review and correction.

[1141] Specific examples

[1142] For example, when simulating the interior design of a cafe, the user selects the following conditions:

[1143] Wall material: White brick

[1144] Flooring: Wooden flooring

[1145] Layout: Cafe style layout

[1146] The prompt generated based on this condition is as follows:

[1147] Walls: White brick, Floors: Wooden flooring, Layout: Cafe-style layout

[1148] By inputting this prompt into an image-generating AI model, a realistic image of the cafe's interior design is generated, which is then presented to the user, who can review it and make any necessary adjustments.

[1149] In this way, designers and store owners can efficiently create designs and respond precisely to customer requests.

[1150] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1151] Step 1:

[1152] The user uses a terminal to select conditions such as wall materials, floor materials, furniture, and layout.

[1153] Input: User-selected conditions (wall materials, floor materials, furniture, layout)

[1154] Output: Data for selected conditions

[1155] How it works: Through the application interface, users tap or click to select options such as wall and flooring materials, furniture, and layout. The selected conditions are saved on the device.

[1156] Step 2:

[1157] The terminal generates a prompt based on the selected conditions.

[1158] Input: Data for selected conditions

[1159] Output: Generated prompt statement

[1160] Specific operation: The terminal converts the selected conditions into text and generates a prompt sentence. For example, a prompt sentence of the form "Wall material: white brick, Floor material: wooden flooring, Layout: cafe-style layout" is generated.

[1161] Step 3:

[1162] The terminal sends the generated prompt to the server.

[1163] Input: Generated prompt text

[1164] Output: The prompt sent to the server

[1165] Specific operation: The terminal sends the generated prompt text as an HTTP request to the server, which receives the request.

[1166] Step 4:

[1167] The server receives the prompt text and inputs it into the image generation AI model.

[1168] Input: The prompt sent to the server

[1169] Output: Input data to the image generation AI model

[1170] Specific operation: The server analyzes the received prompt text and converts it into a format suitable for the image generation AI model. The converted data is then input into the image generation AI model.

[1171] Step 5:

[1172] The server uses an image generation AI model to generate an image based on the prompt text.

[1173] Input: Input data to the image generation AI model

[1174] Output: The generated image

[1175] How it works: The image generation AI model generates a realistic image of the store interior based on the input prompt. The generated image is stored on the server.

[1176] Step 6:

[1177] The server transmits the generated image to the terminal.

[1178] Input: Generated image

[1179] Output: Image sent to the device

[1180] Specific operation: The server sends the generated image to the terminal as an HTTP response. The terminal receives this response.

[1181] Step 7:

[1182] The terminal presents the received image to the user.

[1183] Input: Image sent to the device

[1184] Output: The image presented to the user

[1185] Specific operation: The device displays the received image in the application interface, allowing the user to review the image and make any necessary corrections.

[1186] Example 3

[1187] Next, a description will be given of Example 3 of Form Example 3. 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."

[1188] Conventional floor plan simulation systems have the problem that it is difficult for designers to generate floor plan proposals that comply with building laws and local government ordinances when drafting plans. Furthermore, there is a lack of a way to check whether the floor plan proposal entered by the user violates the law, which can result in the creation of a floor plan that violates the law. Furthermore, there is a lack of a way to quickly return the verification results to the user, which makes it difficult to achieve an efficient design process.

[1189] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1190] In this invention, the server includes a means for an architect to use in drafting plans and for showing three-dimensional floor plan proposals to a customer, a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels, a means for inputting conditions in accordance with building laws in advance, a means for comparing the floor plan proposal entered by the user with legal information, and a means for returning the comparison results to the user. This makes it possible to efficiently generate floor plan proposals that comply with laws and quickly return the comparison results to the user.

[1191] An "architect" is an engineer who specializes in designing buildings, and is responsible for drafting architectural plans and designing floor plans.

[1192] A "draft plan" is an early proposal for the basic design and floor plan of a building, and is created as a preliminary step to detailed design.

[1193] "Customer" refers to an individual or corporation that requests the design and construction of a building, and is the party that receives proposals for floor plans and architectural plans from the architect.

[1194] A "three-dimensional floor plan" is a blueprint or model that represents the floor plan of a building in three dimensions, making it easier to visually understand the internal structure of the building.

[1195] "Land size" refers to the area of ​​the site on which a building will be constructed, and is an important factor in architectural planning.

[1196] "Orientation" refers to the direction or orientation of the site on which a building is constructed, and is a factor that affects the layout and design of a building.

[1197] "Necessary facilities" refers to the basic facilities and equipment that must be installed in a building, including, for example, electrical equipment and water supply and drainage facilities.

[1198] "Condition tolerance" refers to the range and restrictions of conditions that are permissible in architectural plans, including, for example, building height and building coverage ratio.

[1199] "Floor plan simulation" is the process of virtually designing the floor plan of a building and generating multiple floor plan proposals based on various conditions.

[1200] "Building laws" refers to legal regulations regarding the design and construction of buildings, including, for example, the Building Standards Act and local government ordinances.

[1201] "Legal information" refers to specific data and regulations related to building laws, which are stored in a database.

[1202] "Verification" is the process of comparing the floor plan entered by the user with legal information to determine whether there are any matches or mismatches.

[1203] "Matching result" refers to the information obtained as a result of the matching process, including, for example, a determination of whether or not a law has been violated.

[1204] MODE FOR CARRYING OUT THE INVENTION

[1205] The present invention provides a system for efficiently generating floor plan proposals that comply with building regulations and quickly returning collation results to the user. Specific embodiments of this system will be described below.

[1206] Generate a program for the system

[1207] The server generates a program that stores legal information, such as building codes and local ordinances, in a database. This program takes legal information into account when users simulate floor plans. The hardware used includes a standard server computer, and the software uses the MySQL database management system and the Python programming language.

[1208] Explaining the program's processing in natural language

[1209] The server uses the legal information stored in the database to verify the floor plan entered by the user. Specifically, it performs the following data processing and calculations:

[1210] 1. A user inputs a floor plan proposal. For example, the user inputs the building height as "10 meters" and the lot area as "200 square meters" into a web application form.

[1211] 2. The server receives the JSON data {"height": 10, "area": ​​200} sent by the user.

[1212] 3. The server queries the MySQL database to get the building code information for the area. For example, the query might return {"max_height": 8, "max_area": ​​250}.

[1213] 4. The server compares the acquired legal information with the proposed floor plan entered by the user. For example, it verifies that the building height entered by the user (10 meters) exceeds the legal maximum height of 8 meters. It also verifies that the site area (200 square meters) is within the maximum area (250 square meters).

[1214] 5. The server returns the result of the check to the user. If the law is violated, an error message containing the specific details of the violation is returned. If the law is not violated, the server notifies the user that the proposed floor plan complies with the law.

[1215] Add examples to your description

[1216] As a concrete example, consider the case where a user sets the height of a building to 10 meters. The server references the information stored in the database under the Building Standards Act and verifies that the building height limit for that area is 8 meters. In this case, the server returns an error message to the user stating, "The building height exceeds the legal limit. Please set the height to 8 meters or less."

[1217] Example prompts to input to a generative AI model:

[1218] "If you set the building height at 10 metres, check whether it violates the Building Standards Act."

[1219] In this way, the system can generate legally compliant floor plan proposals. The flow of the specification process in the third embodiment will be described with reference to FIG.

[1220] Program processing flow

[1221] Step 1:

[1222] The user inputs a floor plan.

[1223] Specifically, a user enters information such as the building's height and lot area into a web application form. For example, the user enters the building's height as "10 meters" and the lot area as "200 square meters."

[1224] Input: Building height "10 meters", site area "200 square meters"

[1225] Output: Floor plan data entered by the user

[1226] Step 2:

[1227] The server receives the input floor plan.

[1228] Specifically, the server receives the JSON data {"height": 10, "area": ​​200} sent by the user.

[1229] Input: Floor plan data entered by the user

[1230] Output: Floor plan data received by the server

[1231] Step 3:

[1232] The server retrieves the legal information from the database.

[1233] Specifically, the server queries the MySQL database to get the building code information for the area, for example, {"max_height": 8, "max_area": ​​250} .

[1234] Input: Floor plan data received by the server

[1235] Output: Legal information retrieved from the database

[1236] Step 4:

[1237] The server compares the floor plan with legal information.

[1238] Specifically, the server compares the acquired legal information with the proposed floor plan entered by the user. For example, it verifies that the building height entered by the user (10 meters) exceeds the legal maximum height of 8 meters. It also verifies that the site area (200 square meters) is within the maximum area of ​​250 square meters.

[1239] Input: Legal information retrieved from the database, floor plan data entered by the user

[1240] Output: Matching result (whether it violates the law or not)

[1241] Step 5:

[1242] The server returns the match result to the user.

[1243] Specifically, the server returns the results of the comparison to the user. If the law is violated, an error message is returned containing the specific details of the violation. For example, a message such as "The building height exceeds the legal limit. Please set the height to 8 meters or less" is returned. If the violation is not present, the user is notified that the proposed floor plan complies with the law.

[1244] Input: Matching result

[1245] Output: A message of the match result returned to the user

[1246] (Application example 3)

[1247] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1248] With conventional architectural design systems, it was difficult for designers to generate floor plan proposals that took legal and safety standards into account when creating draft plans. Furthermore, when it came to layout design to optimize the placement of machinery and equipment within a factory, there was a lack of a way to automatically generate optimal layout proposals that took legal and safety standards into account. This made it difficult to achieve an efficient and safe factory layout.

[1249] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1250] In this invention, the server includes a means for an architect to use in drafting plans and for showing three-dimensional floor plan proposals to a customer, a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary equipment, and other conditions and their tolerance levels, a means for inputting conditions in accordance with building regulations in advance, a means for designing a layout to optimize the placement of machinery and equipment within a factory, and a means for generating layout proposals that take laws and safety standards into consideration. This makes it possible to automatically generate floor plan proposals and factory layout proposals that take laws and safety standards into consideration.

[1251] An "architect" is an engineer who specializes in architectural and interior design.

[1252] A "draft plan" is the basic design concept or plan created by an architect in the early stages.

[1253] A "three-dimensional floor plan" is a blueprint that represents the internal structure of a building in three dimensions.

[1254] "Land size" refers to the area of ​​land available for constructing a building.

[1255] "Orientation" refers to the direction or orientation in which a building or facility is located.

[1256] "Necessary facilities" is a general term for machines and equipment required within a building or factory.

[1257] "Condition tolerance" refers to the range and limits that are permissible in design and layout.

[1258] A "floor plan simulation" is a simulation for virtually arranging and evaluating the internal structure of a building.

[1259] "Building law" refers to legal regulations and standards governing the design and construction of buildings.

[1260] "Layout of machinery and equipment within a factory" refers to planning the optimal layout of the machinery and equipment used within a factory.

[1261] "Layout design" is the planning of the physical arrangement and structure within a specific space.

[1262] "Legal and safety standards" refers to legal regulations and safety standards that must be observed in design and layout.

[1263] A "layout proposal" is a proposal for the physical arrangement or structure within a particular space.

[1264] A system for carrying out this invention includes means for an architect to use in drafting plans and showing a three-dimensional floor plan to a client, means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and tolerances for those conditions, means for inputting conditions in accordance with building laws in advance, means for designing a layout to optimize the placement of machinery and facilities within a factory, and means for generating a layout plan that takes into account laws and safety standards.

[1265] Program processing explanation

[1266] The server uses a Python program to utilize generative AI models and legal databases. The server receives factory specifications and local legal requirements as input and generates a layout based on them. Specifically, it performs the following processes:

[1267] 1. Data entry: The server receives the factory specifications (e.g., type of machinery, space size) and local legal requirements.

[1268] 2. Data processing: The server retrieves the relevant laws and safety standards from the legal database and integrates them with the factory specifications.

[1269] 3. Layout generation: The server uses a generative AI model to generate an optimal layout plan that takes into account legal and safety standards.

[1270] 4. Result output: The server presents the generated layout proposal to the user.

[1271] Specific examples

[1272] For example, when used in a factory in Tokyo, the following prompt sentences are input into the generative AI model:

[1273] Factory specifications: There are machine 1, machine 2 and machine 3, the space is 1000 square meters.

[1274] Region: Tokyo

[1275] Example prompt sentence:

[1276] Factory specifications: Machine 1, Machine 2, Machine 3, space 1000 square meters, location Tokyo. Generate the optimal layout taking into account laws and safety standards.

[1277] In this way, the server can automatically generate floor plan and factory layout proposals that take into account laws and safety standards.

[1278] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1279] Step 1:

[1280] The server receives factory specifications (e.g., machine type, space size) and local legal requirements as input from the user. Specifically, the user enters the factory specifications and local information into an input form on their terminal and sends it to the server. The input data includes the machine type, installation space size, and local area name.

[1281] Step 2:

[1282] The server retrieves the relevant laws and safety standards from the legal database based on the received regional information. Specifically, the server sends the regional information as a query to the legal database and retrieves data on the relevant laws and safety standards. The input is regional information, and the output is data on the relevant laws and safety standards.

[1283] Step 3:

[1284] The server integrates the factory specifications with the acquired legal and safety standard data. Specifically, it merges the factory specification data with the legal data to create integrated data to input into the generative AI model. The input is the factory specification data and legal data, and the output is the integrated data.

[1285] Step 4:

[1286] The server uses a generative AI model to generate an optimal layout plan based on the integrated data. Specifically, the integrated data is input into the generative AI model, which then generates an optimal layout plan that takes into account laws and safety standards. The input is the integrated data, and the output is the optimal layout plan.

[1287] Step 5:

[1288] The server presents the generated layout plan to the user. Specifically, the server sends the generated layout plan to the user's device so that the user can visually check it. The input is the optimal layout plan, and the output is the layout plan presented to the user.

[1289] In this way, the server can automatically generate floor plan and factory layout proposals that take into account laws and safety standards and provide them to users.

[1290] 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.

[1291] "Example 1"

[1292] The system described in claim 4 includes an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their facial expressions, tone of voice, choice of words, etc. For example, if the user says, "This room is dark," the emotion engine will sense dissatisfaction from the user's tone of voice, and the system will suggest a brighter floor plan.

[1293] "Example 2"

[1294] The system described in claim 5 includes an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their reactions and adjusts the selection of wall and floor materials and the image generation of fixtures and interiors based on the analysis. For example, if the user comments, "I'd like a more subdued feel" in response to a proposed floor plan, the emotion engine analyzes the user's desired "subdued feel," and the system selects wall and floor materials with more subdued colors and materials, and adjusts the image generation of fixtures and interiors accordingly.

[1295] "Example 3"

[1296] The system described in claim 6 includes an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their reactions and automatically generates an optimal floor plan based on the analysis. For example, if the user comments, "I want a more open feeling" in response to a proposed floor plan, the emotion engine analyzes the "open feeling" desired by the user, and the system automatically generates a more open floor plan.

[1297] The processing flow of each embodiment will be described below.

[1298] "Example 1"

[1299] Step 1: The user starts the system and inputs the necessary information (land size, orientation, required facilities, etc.).

[1300] Step 2: The system generates multiple floor plan options based on the input information and presents them to the user.

[1301] Step 3: The user provides feedback on the floor plan. This feedback can include not only words, but also facial expressions and tone of voice.

[1302] Step 4: The emotion engine analyzes emotions from user feedback.

[1303] Step 5: The system adjusts the floor plan proposal based on the analysis results of the emotion engine and presents it to the user again.

[1304] "Example 2"

[1305] Step 1: The user starts the system and inputs the necessary information (land size, orientation, required facilities, etc.).

[1306] Step 2: The system generates multiple floor plan options based on the input information and presents them to the user.

[1307] Step 3: The user provides feedback on the floor plan. This feedback can include not only words, but also facial expressions and tone of voice.

[1308] Step 4: The emotion engine analyzes emotions from user feedback.

[1309] Step 5: Based on the analysis results of the emotion engine, the system adjusts the selection of wall and floor materials and the image generation of fixtures and interiors, and presents them again to the user.

[1310] "Example 3"

[1311] Step 1: The user starts the system and inputs the necessary information (land size, orientation, required facilities, etc.).

[1312] Step 2: The system generates multiple floor plan options based on the input information and presents them to the user.

[1313] Step 3: The user provides feedback on the floor plan. This feedback can include not only words, but also facial expressions and tone of voice.

[1314] Step 4: The emotion engine analyzes emotions from user feedback.

[1315] Step 5: The system automatically generates an optimal floor plan based on the analysis results of the emotion engine and presents it to the user again.

[1316] Example 1

[1317] Next, a description will be given of Example 1 of Form 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."

[1318] With conventional design support systems, when a designer drafts a plan, they have to manually create a floor plan while taking into account conditions such as the size and orientation of the land and the necessary facilities, which is time-consuming and labor-intensive. It is also difficult to reflect the user's feelings and feedback in real time, making it impossible to quickly provide optimal floor plan proposals. Furthermore, the design process is complicated because it is necessary to manually check conditions that comply with building laws.

[1319] The specification process by the specification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means used by an architect to create a draft plan and to show a three-dimensional floor plan to a customer, a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels, a means for inputting conditions in accordance with building laws in advance, a means for analyzing the user's emotions and adjusting the floor plan based on those emotions, and a means for generating floor plan proposals using a generative AI model. This enables the architect to efficiently generate optimal floor plan proposals and make flexible proposals that respond to the user's emotions.

[1320] An "architect" is an engineer who specializes in architectural and interior design.

[1321] "Drafting the plan" refers to the design proposal that the architect creates at an early stage.

[1322] A "3D floor plan" refers to a diagram of the interior layout of a building presented in 2D or 3D visual format.

[1323] "Land size" refers to the area of ​​the proposed construction site.

[1324] "Orientation" refers to the direction in which the proposed construction site or building faces.

[1325] "Necessary facilities" refers to the basic equipment and facilities that should be installed within the building.

[1326] "Other conditions" refers to additional requirements or constraints that must be considered in the design.

[1327] "Condition tolerance" refers to the flexibility and tolerance for design conditions.

[1328] "Floor plan simulation" refers to a virtual model of the interior layout of a building that is automatically generated based on input conditions.

[1329] "Building laws" refers to legal regulations and standards governing the design and construction of buildings.

[1330] "Analyzing emotions" refers to reading a user's emotions from their facial expressions, tone of voice, choice of words, etc.

[1331] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to generate new information or suggestions from data.

[1332] A "prompt" refers to an instruction or question that is input into a generative AI model.

[1333] The present invention is a system used by architects to draft plans, and includes a function to analyze the user's emotions and adjust the floor plan proposal based on those emotions. Specific embodiments of this system are described below.

[1334] Hardware and software used

[1335] Hardware: High-performance server (e.g., high-performance server equipment)

[1336] Software: Generative AI models (e.g., advanced generative AI algorithms), emotion engines (e.g., emotion analysis software)

[1337] Details of data processing and calculation

[1338] 1. Data Entry:

[1339] The user (designer) inputs the land size, orientation, necessary facilities, other conditions and their tolerances through the system interface.

[1340] Specifically, you enter information such as "Land size: 200 square meters," "Orientation: South-facing," "Required facilities: Kitchen, living room, two bedrooms, bathroom," "Other conditions: Barrier-free, lots of natural light," and "Condition tolerance: High" into the input form.

[1341] 2. Data transmission:

[1342] The terminal transmits the data entered by the user to the server in real time.

[1343] Specifically, when you press the submit button on the input form, the data is sent to the server in JSON format.

[1344] 3. Generate floor plan simulation:

[1345] Based on the received data, the server uses a generative AI model to generate multiple floor plan simulations.

[1346] Specifically, the server inputs prompt text into the generative AI model, using prompt text such as, "The land is 200 square meters and faces south. The required facilities are a kitchen, living room, two bedrooms, and a bathroom. It must be barrier-free and have plenty of natural light. The conditions are highly tolerant. Please generate a floor plan based on this."

[1347] 4. Floor plan presentation:

[1348] The server transmits the generated floor plan proposals to the terminal.

[1349] Specifically, the generated floor plan is sent to the device as an image or 3D model so that the user can check it.

[1350] 5. Emotion analysis:

[1351] As the user reviews the proposed floor plan, the device uses an emotion engine to analyze the user's facial expressions, tone of voice, and choice of words.

[1352] Specifically, if a user says, "This room is dark," the emotion engine will sense dissatisfaction from the tone of voice and facial expression.

[1353] 6. Adjusting the floor plan:

[1354] The server receives feedback from the emotion engine and again uses the generative AI model to generate new floor plan suggestions based on the user's emotions.

[1355] Specifically, a prompt such as "The user feels that the room is dark, so please generate a brighter floor plan" is used.

[1356] 7. Presenting a new floor plan:

[1357] The server sends the new floor plan to the terminal and presents it to the user.

[1358] Specifically, the new floor plan is sent to the device again as an image or 3D model.

[1359] Specific examples

[1360] Example input:

[1361] Land size: 200 square meters

[1362] Orientation: South

[1363] Required facilities: kitchen, living room, two bedrooms, bathroom

[1364] Other requirements: Barrier-free access, plenty of natural light

[1365] Condition tolerance: High

[1366] Example prompt sentence:

[1367] The land area is 200 square meters and faces south. The required facilities are a kitchen, living room, two bedrooms, and a bathroom. It must be barrier-free and have plenty of natural light. The conditions are highly tolerant. Please generate a floor plan based on this.

[1368] This system allows designers to efficiently generate optimal floor plan proposals and make flexible suggestions that reflect the user's emotions.

[1369] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1370] Step 1:

[1371] The user inputs the data. The user (architect) enters the land size, orientation, required facilities, other conditions, and their tolerance levels through the system interface. Specifically, the user enters information such as "Land size: 200 square meters," "Orientation: South-facing," "Required facilities: Kitchen, living room, two bedrooms, bathroom," "Other conditions: Barrier-free access, lots of natural light," and "Condition tolerance: High" into the input form. The input data is sent to the system.

[1372] Step 2:

[1373] The terminal sends data to the server. The terminal sends the data entered by the user to the server in real time. Specifically, when the submit button on the input form is pressed, the data is sent to the server in JSON format. The input data reaches the server and proceeds to the next processing step.

[1374] Step 3:

[1375] The server generates a floor plan simulation. Based on the received data, the server uses a generative AI model to generate multiple floor plan simulations. Specifically, the server inputs a prompt statement into the generative AI model, such as, "The land is 200 square meters in size and faces south. The required facilities are a kitchen, living room, two bedrooms, and a bathroom. It must be barrier-free and have plenty of natural light. The conditions are highly tolerant. Please generate a floor plan proposal based on this." The generated floor plan proposals are saved on the server.

[1376] Step 4:

[1377] The server sends the generated floor plan to the terminal. The server then sends the multiple floor plan plans it has generated to the terminal. Specifically, the generated floor plan plans are sent to the terminal as images or 3D models so that the user can check them. The sent floor plan plans are displayed on the terminal.

[1378] Step 5:

[1379] The user reviews the floor plan. The user reviews the floor plan presented on the device. Specifically, the user rotates the floor plan on the device screen and zooms in and out to view the details. The user's feedback advances to the next processing step.

[1380] Step 6:

[1381] The device analyzes the user's emotions. Using an emotion engine, the device analyzes the user's facial expressions, tone of voice, and choice of words. For example, if the user says, "This room is dark," the emotion engine will sense dissatisfaction from the tone of voice and facial expression. The analysis results are sent to the server.

[1382] Step 7:

[1383] The server adjusts the floor plan proposal based on the emotion. The server receives feedback from the emotion engine and uses the generative AI model again to generate a new floor plan proposal based on the user's emotion. Specifically, it uses a prompt such as, "The user felt the room was dark, so please generate a brighter floor plan proposal." The new floor plan proposal is then saved on the server.

[1384] Step 8:

[1385] The server sends the new floor plan to the device. The server then sends the new floor plan to the device and presents it to the user. Specifically, the server sends the new floor plan to the device again as an image or 3D model. The new floor plan is then displayed on the device.

[1386] Step 9:

[1387] The user performs the final confirmation. The user checks the new floor plan and provides final feedback. Specifically, this process is repeated until the user is satisfied, and finally, a satisfactory floor plan is finalized. The final floor plan is saved in the system.

[1388] (Application example 1)

[1389] Next, a description will be given of Application Example 1 of Form 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."

[1390] With conventional design systems, it took a lot of time and effort for designers to create a draft plan, and it was difficult to efficiently present three-dimensional floor plan proposals to customers. Furthermore, it was not possible to reflect user emotions and feedback in real time, making it difficult to provide optimal design proposals. In addition, the generation and adjustment of interior designs had to be done manually, which was inefficient.

[1391] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes: a means for an architect to use in drafting a plan and to show a three-dimensional floor plan to a customer; a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels; a means for pre-entering conditions in accordance with building regulations; a means including an emotion engine that recognizes a user's emotions, analyzing the user's emotions from their facial expressions, tone of voice, and word choice, and adjusting the floor plan based on the feedback; a means for displaying interior design proposals in 3D using a smart device; a means for generating interior design proposals using a generative AI model; and a means for readjusting the design proposals based on the results of the emotion analysis. This enables an architect to efficiently draft a plan and present three-dimensional floor plan proposals to a customer, thereby providing an optimal design proposal that reflects the user's emotions and feedback in real time.

[1392] An "architect" is an engineer who specializes in designing buildings and interiors.

[1393] A "draft plan" is a basic design concept or plan created by an architect in the early stages.

[1394] A "three-dimensional floor plan" is a diagram of the interior layout of a building that is represented in 3D rather than 2D.

[1395] "Land size" refers to the area of ​​the proposed construction site.

[1396] "Orientation" refers to information that indicates the direction in which the proposed construction site and building face.

[1397] "Necessary facilities" refers to the equipment and devices that must be installed within the building.

[1398] "Condition tolerance" refers to the range of conditions that are acceptable in a design.

[1399] A "floor plan simulation" is a virtual model of the interior layout of a building that is automatically generated based on input conditions.

[1400] "Building law" refers to the legal regulations and standards governing the design and construction of buildings.

[1401] An "emotion engine" is a system that analyzes emotions from a user's facial expressions, tone of voice, choice of words, etc.

[1402] A "smart device" is an electronic device that has internet connectivity and advanced computing capabilities.

[1403] An "interior design proposal" is a design proposal regarding the decoration and layout of the interior of a building.

[1404] A "generative AI model" is an algorithm that uses artificial intelligence to automatically generate designs and plans.

[1405] "Sentiment analysis" refers to the process of analyzing a user's emotions.

[1406] "Re-tuning a design proposal" is the process of revising a design based on user feedback and sentiment analysis results.

[1407] A system for implementing this invention is used by architects to draft plans and show three-dimensional floor plan proposals to clients. By inputting the land size and orientation, necessary facilities, and other conditions and tolerances for those conditions, the system automatically generates multiple floor plan simulations and presents them to the architect. It also includes an emotion engine that recognizes the user's emotions, analyzes their emotions from their facial expressions, tone of voice, and choice of words, and adjusts the floor plan proposal based on the feedback.

[1408] Hardware and software used

[1409] Hardware:

[1410] Smartphone (e.g. iPhone, Android device)

[1411] Smart glasses (e.g. Google Glass, Microsoft HoloLens)

[1412] software:

[1413] Generative AI models (e.g., OpenAI GPT-4)

[1414] Sentiment analysis engine (e.g. Microsoft Azure Emotion API)

[1415] 3D modeling software

[1416] Data processing and calculation

[1417] Server Action:

[1418] 1. Acquiring input data: The server receives the store size, shape, necessary facilities, and other conditions entered by the user via a smartphone or smart glasses.

[1419] 2. Use of generative AI model: The server generates multiple interior design proposals using a generative AI model (e.g., GPT-4) based on the input data.

[1420] 3. 3D modeling: The server generates data for displaying the generated design proposal in three dimensions using 3D modeling software.

[1421] Terminal handling:

[1422] 1. Displaying design proposals: A smartphone or smart glasses displays the 3D design proposals sent from the server.

[1423] 2. Emotion analysis: The smart device uses an emotion analysis engine to analyze the user's facial expressions and tone of voice when looking at a design proposal, and recognizes the user's emotions.

[1424] User Action:

[1425] 1. Providing feedback: Users provide feedback on the design proposals using voice and facial expressions.

[1426] 2. Review the re-adjustment: The user reviews the re-adjusted design proposal based on the results of sentiment analysis.

[1427] Examples and prompts

[1428] Examples:

[1429] The user puts on the smart glasses and voice-inputs the size, shape, and necessary facilities of the store. Based on this information, the server generates multiple interior design proposals and displays them in 3D on the smart glasses' display. If the user says, "This design is a little dark," the emotion analysis engine detects the dissatisfaction, and the server re-presents a brighter design proposal.

[1430] Example prompt for a generative AI model:

[1431] The store is 50 square meters in size and rectangular in shape. The necessary equipment is counters, shelves, and lighting. Based on these conditions, generate three different interior design proposals.

[1432] In this way, designers can efficiently draft plans and present three-dimensional floor plans to customers, providing optimal design proposals that reflect user sentiment and feedback in real time.

[1433] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1434] Step 1:

[1435] Obtaining input data

[1436] The server receives the store's size, shape, necessary facilities, and other conditions entered by the user through a smartphone or smart glasses. This input data is sent to the server and stored in a database. Specifically, the user enters the conditions using voice or touch input, and the data is sent to the server.

[1437] Step 2:

[1438] Using generative AI models

[1439] The server generates multiple interior design proposals using a generative AI model (e.g., GPT-4) based on the input data obtained in step 1. The input data is input to the generative AI model as a prompt sentence, and the design proposals are output in text format. Specifically, the prompt sentence is generated as follows:

[1440] The store is 50 square meters in size and rectangular in shape. The necessary equipment is counters, shelves, and lighting. Based on these conditions, generate three different interior design proposals.

[1441] The generated design proposals are stored on the server.

[1442] Step 3:

[1443] 3D modeling

[1444] The server generates data for displaying the design proposal generated in step 2 in 3D using 3D modeling software. Specifically, it converts the text-based design proposal into a 3D model that can be visually confirmed by the user. The generated 3D model data is sent from the server to the terminal.

[1445] Step 4:

[1446] Displaying design ideas

[1447] The terminal (smartphone or smart glasses) displays the 3D design proposal sent from the server. The user can check the three-dimensional interior design proposal through the smart device's display. Specifically, the 3D model is displayed on the smart glasses' display.

[1448] Step 5:

[1449] Emotion analysis

[1450] The device uses an emotion analysis engine (e.g., Microsoft Azure Emotion API) to analyze the user's facial expressions and tone of voice when viewing a design proposal, and recognizes the user's emotions. Specifically, the device's camera and microphone are used to capture the user's facial expressions and voice, and the results are sent to the emotion analysis engine. The analysis results are then sent to a server.

[1451] Step 6:

[1452] Providing feedback

[1453] Users can provide feedback on design proposals using voice and facial expressions. For example, if a user says, "This design is a little dark," the voice data is sent from the device to the server.

[1454] Step 7:

[1455] Re-adjusting the design

[1456] The server re-uses the generative AI model to refine the design proposal based on the sentiment analysis results obtained in step 5 and the feedback obtained in step 6. Specifically, it adds the sentiment analysis results to the prompt text and re-inputs it into the generative AI model:

[1457] The user said, "This design is a bit dark." Based on this, generate some brighter interior design ideas.

[1458] The re-adjusted design proposal is then re-modeled in 3D and sent to the device.

[1459] Step 8:

[1460] Check readjustment

[1461] The device displays the re-adjusted design proposal for the user to review again. Specifically, the re-adjusted 3D model is displayed on the smart glasses display. The user can review the re-adjusted design proposal and repeat this process until they are satisfied.

[1462] Example 2

[1463] Next, a description will be given of Example 2 of Form 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."

[1464] With conventional design systems, it was difficult for designers to provide floor plan proposals and interior designs that accurately reflected the user's emotions and desires. Furthermore, the selection of wall and floor materials and the generation of interior images that took the user's emotions into consideration were not automated, placing a heavy burden on designers and preventing an efficient design process. Furthermore, there was a lack of a way to check the generated interior images in real time, making it difficult to increase user satisfaction.

[1465] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1466] In this invention, the server includes: means for an architect to use in drafting plans and to show three-dimensional floor plan proposals to a customer; means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance; means for inputting conditions in accordance with building regulations in advance; means including an emotion engine that recognizes the user's emotions; means for the emotion engine to analyze the user's emotions and adjust the selection of wall and floor materials and the generation of images of fixtures and interior fittings based on the analyzed emotions; means for generating interior images using an image generation AI model based on information about the wall and floor materials selected by the architect; and means for transmitting the generated interior images to the architect's terminal and displaying them. This makes it possible to provide floor plan proposals and interior designs that accurately reflect the user's emotions and requests.

[1467] An "architect" is an engineer who specializes in designing buildings.

[1468] A "draft plan" is an early design drawing that shows the basic design concept and layout of a building.

[1469] A "three-dimensional floor plan" is a blueprint or model that represents the interior space of a building in three dimensions.

[1470] "Land size and orientation" refers to the area and orientation of the proposed construction site.

[1471] "Essential facilities" refers to the basic infrastructure and equipment that must be installed in a building.

[1472] "Condition tolerance" refers to the range of tolerance and the laxity of constraints in a design.

[1473] "Floor plan simulation" is the process of virtually testing the layout of the interior space of a building on a computer.

[1474] "Building laws" refer to legal regulations and standards regarding the design and construction of buildings.

[1475] An "emotion engine" is software or hardware that analyzes a user's emotions and adjusts the system's behavior based on the results.

[1476] An "image generation AI model" is an artificial intelligence algorithm that generates images based on input text or data.

[1477] "Reference knowledge" refers to information on standard materials and designs used in design.

[1478] A "terminal" is a device such as a computer or tablet used by a designer.

[1479] "User" refers to the final user or customer of the building designed by the architect.

[1480] MODE FOR CARRYING OUT THE INVENTION

[1481] This invention is a system that allows designers to provide floor plan proposals and interior designs that accurately reflect the user's feelings and desires. Specific embodiments of this system will be described below.

[1482] Hardware and software used

[1483] The server generates interior images using an image generation AI model based on information about the wall and floor materials selected by the designer. For image generation, an image generation AI model such as "DALL-E" is used. The server then sends the generated interior images to the designer's device.

[1484] The terminal sends information about the wall and floor materials selected by the designer to the server. It also has the function of displaying the generated images sent from the server. An operating system such as Windows or macOS is installed on the terminal.

[1485] Users express their feelings about the proposed floor plan and interior design. The emotion engine analyzes the user's emotions from their words and facial expressions, and adjusts the selection of wall and floor materials and the generation of fixtures and interior images based on those emotions.

[1486] Explanation of program processing

[1487] The server uses image generation AI to generate interior images based on "reference knowledge" such as the wall and floor materials selected by the architect. The generated images are presented to the architect. For example, if the architect selects "wood-grain flooring" and "white wall materials," the server inputs this information into the image generation AI and generates an interior image that matches the specified conditions. The generated images are sent to the architect's device, where they can be viewed.

[1488] The terminal sends information about the wall and floor materials selected by the designer to the server. It also has the function of displaying the generated images sent from the server. For example, the designer selects "wood-grain flooring" and "white wall materials" on the terminal and sends this information to the server. The server then sends the generated interior image to the terminal, where the designer can check it.

[1489] The user expresses their feelings about the proposed floor plan and interior. The emotion engine analyzes the user's emotions from their comments and facial expressions, and adjusts the selection of wall and floor materials and the generation of fixtures and interior images based on that. For example, if the user says, "I'd like a more subdued feel," the emotion engine analyzes this comment and the system selects wall and floor materials with more subdued colors and materials. For example, it selects "subdued wood-grain floor materials" and "light beige wall materials," and generates an interior image based on that.

[1490] Prompt Sentence Examples

[1491] Below are some example prompts to input to a generative AI model:

[1492] 1. "Generate an interior image of a living room with wood-grain flooring and white walls."

[1493] 2. "Generate an interior image of a living room with muted wood flooring and pale beige wall coverings."

[1494] Using these prompts, the image generation AI generates interior images that match the specified conditions.

[1495] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1496] Step 1:

[1497] The user expresses their feelings about the proposed floor plan and interior design. For example, they might say, "I'd like it to have a more calming feel." The device then sends the user's comments and facial expressions to the emotion engine. The emotion engine then analyzes the user's emotions and sends the results to the server.

[1498] Input: User's speech and facial expressions

[1499] Output: Parsed emotion data

[1500] Specifically, if a user says, "I'd like it to be more cheerful," the device converts this speech into text using speech recognition software (e.g., a speech recognition engine) and sends it to the emotion engine. The emotion engine then analyzes the "cheerful feeling" from the user's speech and sends the results to the server.

[1501] Step 2:

[1502] The designer selects "reference knowledge" such as wall and floor materials on the terminal. A list of wall and floor materials that the designer can choose from is displayed on the terminal. The designer selects the appropriate material from the list.

[1503] Input: Information on wall and floor materials selected by the architect

[1504] Output: Information on selected wall and floor materials

[1505] Specifically, the designer operates the interface on the terminal and selects "wood-grain flooring" and "white wall material." The terminal then prepares to send the selected information to the server.

[1506] Step 3:

[1507] The device sends information about the wall and floor materials selected by the designer to the server, which then generates prompt text to input into the image generation AI model based on the received information.

[1508] Input: Information on wall and floor materials selected by the architect

[1509] Output: Generated prompt statement

[1510] Specifically, the device sends information about "wood-grain flooring" and "white wall materials" to the server. Based on this information, the server generates a prompt message saying, "Please generate an interior image of a living room with wood-grain flooring and white wall materials."

[1511] Step 4:

[1512] The server inputs the generated prompt sentence into an image generation AI model (e.g., an image generation engine) to generate an interior image. The generated image is stored on the server.

[1513] Input: Generated prompt text

[1514] Output: Generated interior image

[1515] Specifically, the server inputs the prompt "Generate an interior image of a living room with wood-grain flooring and white walls" into the image generation AI model. The image generation AI model generates an interior image that meets the specified conditions and returns it to the server.

[1516] Step 5:

[1517] The server sends the generated interior image to the terminal, which displays the received image to the designer. The designer can then check the generated image and make further selections or adjustments as necessary.

[1518] Input: Generated interior image

[1519] Output: Interior image displayed on the device

[1520] Specifically, the server sends the generated interior image to the terminal. The terminal displays the received image to the designer, who then checks it. If the designer needs to make further adjustments, the same procedure is repeated.

[1521] (Application example 2)

[1522] Next, a description will be given of Application Example 2 of Form 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."

[1523] In conventional design systems, when designers create floor plan proposals, it is difficult to adjust them to reflect the user's emotions and preferences, making it difficult to increase user satisfaction. Furthermore, when selecting interior design in a physical store, it is not possible to make proposals that reflect the user's emotions in real time, making it difficult to make optimal choices. This creates a need for systems that can provide floor plan proposals and interior proposals that precisely meet the user's needs.

[1524] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1525] In this invention, the server includes: means for an architect to use in drafting plans and for showing three-dimensional floor plan proposals to customers; means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance; means for inputting conditions in accordance with building laws in advance; means including an emotion engine for analyzing the user's emotions and adjusting the proposal content; means for proposing optimal wall materials, floor materials, fixtures, and interior design to the user via a smart device; and means including an image generation AI for generating interior images based on the selected items. This makes it possible to propose floor plan proposals and interior design proposals that reflect the user's emotions in real time.

[1526] An "architect" is an engineer who specializes in designing buildings.

[1527] A "draft plan" is an early drawing or plan that shows the basic design concept of a building.

[1528] A "three-dimensional floor plan" is a blueprint or model that represents the interior space of a building in three dimensions.

[1529] "Land size" refers to the area of ​​the site on which a building is constructed.

[1530] "Orientation" refers to the direction in which a building is placed.

[1531] "Essential facilities" are the basic infrastructure and equipment that should be installed in a building.

[1532] "Condition tolerance" refers to the range or limits that are permissible in design and construction.

[1533] "Floor plan simulation" is the process of virtually testing the layout of the interior spaces of a building.

[1534] "Building laws" are legal regulations and standards governing the design and construction of buildings.

[1535] An "emotion engine" is a software module that analyzes the user's emotions and adjusts the system's behavior based on the results.

[1536] A "smart device" is an electronic device that has internet connectivity and advanced computing capabilities.

[1537] "Wall materials" are materials that make up the walls of buildings.

[1538] "Flooring" refers to materials that make up the floors of buildings.

[1539] "Fixtures" are fixed decorations and equipment installed inside a building.

[1540] "Interior" refers to the decoration and design of the interior space of a building.

[1541] "Image generation AI" is a technology that uses artificial intelligence to generate images.

[1542] A system for carrying out this invention comprises: means for an architect to use in drafting plans and to show a customer a three-dimensional floor plan; means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance; means for inputting conditions in accordance with building laws in advance; means including an emotion engine for analyzing the user's emotions and adjusting the content of proposals; means for proposing optimal wall materials, floor materials, fixtures, and interiors to the user via a smart device; and means including an image generation AI for generating interior images based on the selected items.

[1543] Hardware and software used

[1544] Smart devices: such as smart glasses or smartphones, capture images from the user's perspective and perform emotion analysis in real time.

[1545] EmotionEngine: A software module for analyzing user emotions.

[1546] ImageGenerator: A software module that generates interior images based on selected items.

[1547] ReferenceKnowledge: A database of wall materials, flooring materials, fixtures, and interior design provided by manufacturers.

[1548] Data processing and calculation

[1549] 1. Emotion Analysis: Images of users captured with smart devices are input into the Emotion Engine to analyze their emotions, allowing users to understand their preferences and needs in real time.

[1550] 2. Selection and Adjustment: Based on the analyzed emotions, the system selects the optimal wall materials, floor materials, fixtures, and interior design from ReferenceKnowledge. This enables the system to make optimal suggestions based on the user's emotions.

[1551] 3. Image generation: An interior image is generated using ImageGenerator based on the selected items, allowing for visually easy-to-understand suggestions to be presented to the user.

[1552] Specific examples

[1553] A user wears smart glasses and visits an interior design shop. When the user says, "I'd like it to have a brighter feel," the emotion engine analyzes the user's emotions, and the system selects bright-colored wall and floor materials, generates an interior image, and presents it to the user.

[1554] Prompt Sentence Examples

[1555] Analyze the user's emotions and select light-colored wall and floor materials. If the user says, "I'd like it to feel brighter," select light-colored wall and floor materials and generate an interior image.

[1556] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1557] Step 1:

[1558] A user wears a smart device (smart glasses or a smartphone) and visits an interior design shop. The smart device captures images from the user's point of view.

[1559] Input: An image captured from the user's point of view.

[1560] Output: The captured image data.

[1561] How it works: The smart device's camera captures images of the surroundings from the user's point of view in real time.

[1562] Step 2:

[1563] The captured image data is sent to the EmotionEngine, which analyzes the user's emotions.

[1564] Input: The captured image data.

[1565] Output: Parsed user emotion data.

[1566] Specific operation: EmotionEngine analyzes image data and identifies emotions from the user's facial expressions and voice.

[1567] Step 3:

[1568] Based on the analyzed emotional data, the optimal wall materials, flooring materials, fixtures, and interior design are selected from ReferenceKnowledge.

[1569] Input: Parsed user emotion data.

[1570] Output: Selection data for optimal wall materials, floor materials, fixtures, and interior design.

[1571] Specific operation: ReferenceKnowledge refers to the emotion data and selects items from the database that match the user's emotion.

[1572] Step 4:

[1573] Based on the selected items, an interior image is generated using ImageGenerator.

[1574] Input: Data for selecting the optimal wall materials, floor materials, fixtures, and interior.

[1575] Output: Generated interior image.

[1576] Specific operation: Based on the selected data, the ImageGenerator generates an interior image to present to the user.

[1577] Step 5:

[1578] The generated interior image is sent to the smart device and presented to the user.

[1579] Input: Generated interior images.

[1580] Output: Interior image presented to the user.

[1581] Specific operation: The generated interior image is displayed on the smart device display, allowing the user to visually confirm it.

[1582] Example 3

[1583] Next, a description will be given of Example 3 of Form Example 3. 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."

[1584] Conventional floor plan simulation systems have difficulty generating floor plan proposals that comply with building laws and local government ordinances, and are unable to automatically generate optimal floor plan proposals that reflect the user's emotions and feedback. This makes it difficult to provide floor plan proposals that meet the user's requirements.

[1585] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1586] In this invention, the server includes a means for an architect to use in drafting plans and for showing three-dimensional floor plan proposals to the customer, a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels, a means for inputting conditions in accordance with building laws in advance, a means for recognizing the user's emotions and automatically generating optimal floor plan proposals based on those emotions, and a means for analyzing the user's feedback and generating new floor plan proposals based on the analysis results. This makes it possible to generate floor plan proposals that do not violate laws and provide optimal floor plan proposals that correspond to the user's emotions.

[1587] An "architect" is an engineer who specializes in designing buildings.

[1588] A "draft plan" is an early design drawing that shows the basic design and layout of a building.

[1589] A "three-dimensional floor plan" is a blueprint that represents the interior space of a building in three dimensions.

[1590] "Land size and orientation" refers to the area of ​​land on which a building can be constructed and the direction in which the land faces.

[1591] "Essential facilities" are the basic facilities and equipment that should be installed in a building.

[1592] "Condition tolerance" refers to the range or limits of conditions that are acceptable in the design of a building.

[1593] "Floor plan simulation" is the process of virtually testing the layout of the interior spaces of a building.

[1594] "Building laws" are legal regulations and standards governing the design and construction of buildings.

[1595] "Local ordinances" are building rules and regulations that apply in a particular area.

[1596] "User's emotions" refer to the user's psychological reactions and feedback to the floor plan proposal.

[1597] An "optimal floor plan" is the layout of the interior space of a building that best suits the user's needs and feelings.

[1598] "Feedback" refers to opinions and impressions provided by users.

[1599] "Analysis results" are the conclusions and data drawn by the emotion engine based on user feedback.

[1600] The "new floor plan proposal" is the layout of the interior space of a building that has been redesigned to reflect user feedback and analysis results.

[1601] "Wall and floor materials" are materials used for the walls and floors of buildings.

[1602] "Reference knowledge" is information about building materials and designs provided by manufacturers.

[1603] An "image generation model" is an algorithm or program that allows a computer to generate images.

[1604] MODE FOR CARRYING OUT THE INVENTION

[1605] The present invention is a system for generating floor plan proposals that comply with building regulations and provide optimal floor plan proposals that correspond to the user's feelings. Specific embodiments of this system will be described below.

[1606] System configuration

[1607] This system consists of three main components: a server, a terminal, and a user.

[1608] The server stores legal information such as building laws and local ordinances in a database. The server uses Python to analyze the legal information and executes an algorithm to generate floor plan proposals. The server also uses TensorFlow to implement an emotion engine and analyze user feedback.

[1609] The device receives user input and sends it to the server. When the user provides feedback on the floor plan, the device sends the feedback to the emotion engine. The device communicates with the server using HTTP requests.

[1610] The user provides feedback on the proposed floor plan, for example, saying, "I want it to feel more open." This feedback is sent to the emotion engine via the device.

[1611] Program processing

[1612] The server references legal information stored in a database, such as building laws and local government ordinances, and generates floor plan proposals using Python scripts. For example, it determines the size and layout of rooms based on building laws.

[1613] The device receives the user's request and sends it to the server using an HTTP request. This request includes the user's request. The server sends the generated floor plan in JSON format to the device, and the device receives this data and displays it to the user.

[1614] The user provides feedback on the displayed floor plan. For example, the user may comment, "I want it to feel more open." The device then sends the user's feedback to the emotion engine. This feedback is sent as text data.

[1615] The emotion engine uses TensorFlow to analyze user feedback and understand the user's emotions. For example, from the feedback "I want a sense of openness," it can be determined that the user desires a large space. The emotion engine then sends the analysis results to the server in JSON format.

[1616] The server generates a new floor plan based on the analysis results received from the emotion engine. For example, it may enlarge the living room window and rearrange the rooms to create a more open feel. The new floor plan is then displayed to the user via their device.

[1617] Examples and prompts

[1618] Examples:

[1619] If a user provides feedback such as "I want a more open feeling," the emotion engine analyzes this feedback and understands the "open feeling" the user desires. Based on the analysis results, the server generates a floor plan that increases the open feeling by enlarging the living room window and rearranging the rooms. The new floor plan is displayed to the user via their device.

[1620] Example prompt sentence:

[1621] "If a user comments on a proposed floor plan that they would like it to be more open, please explain how the emotion engine analyzes this and how the server generates a floor plan."

[1622] This system can generate legally valid floor plan proposals and provide optimal floor plan proposals that match the user's feelings. The flow of the specification process in the third embodiment will be described with reference to FIG.

[1623] Program processing flow

[1624] Step 1:

[1625] The user requests a floor plan simulation.

[1626] Input: The user inputs "I would like to see the floor plan for a 3LDK apartment" through the terminal interface.

[1627] Specific operation: The user selects the type of floor plan and conditions on the device screen and sends a simulation request.

[1628] Step 2:

[1629] The terminal sends the user's request to the server.

[1630] Input: User request (e.g., "3LDK floor plan")

[1631] Output: Data sent to the server as an HTTP request

[1632] Specific operation: The terminal receives user input, generates an HTTP request, and sends it to the server.

[1633] Step 3:

[1634] The server generates a floor plan based on the legal information.

[1635] Input: User request, legal information stored in the database

[1636] Output: Generated floor plan (JSON format)

[1637] How it works: The server uses Python scripts to analyze legal information and generate floor plans, for example, determining room sizes and layouts based on building laws.

[1638] Step 4:

[1639] The server sends the generated floor plan to the terminal.

[1640] Input: Generated floor plan (JSON format)

[1641] Output: Floor plan data sent to the device

[1642] Specific operation: The server sends the generated floor plan in JSON format to the device. The device receives this data and displays it to the user.

[1643] Step 5:

[1644] The user provides feedback on the floor plan.

[1645] Input: User feedback on the displayed floor plan (e.g., "I want it to feel more open")

[1646] Output: Feedback text data

[1647] Specific operation: The user looks at the displayed floor plan and enters feedback. For example, the user may comment, "I want it to feel more open."

[1648] Step 6:

[1649] The device sends the user's feedback to the emotion engine.

[1650] Input: User feedback (text data)

[1651] Output: Feedback data sent to the emotion engine

[1652] Specific operation: The device receives the user's feedback and sends it to the emotion engine. This feedback is sent as text data.

[1653] Step 7:

[1654] The emotion engine analyzes the user's emotions.

[1655] Input: User feedback (text data)

[1656] Output: Analysis results (user's feelings and specific requests)

[1657] Specific operation: The emotion engine uses TensorFlow to analyze user feedback and understand the user's emotions. For example, from the feedback "I want a sense of openness," it understands that the user desires a large space.

[1658] Step 8:

[1659] The emotion engine sends the analysis results to the server.

[1660] Input: Analysis results (user's feelings and specific requests)

[1661] Output: Analysis result data sent to the server

[1662] Specific operation: The emotion engine sends the analysis results in JSON format to the server.

[1663] Step 9:

[1664] The server generates new floor plan proposals based on the analysis results.

[1665] Input: Analysis results (user's feelings and specific requests)

[1666] Output: New floor plan (JSON format)

[1667] Specific operation: The server generates a new floor plan based on the analysis results received from the emotion engine. For example, it enlarges the living room window and rearranges the rooms to create a more open feeling.

[1668] Step 10:

[1669] The server sends the new floor plan to the device.

[1670] Input: New floor plan (JSON format)

[1671] Output: New floor plan data sent to the device

[1672] Specific operation: The server sends the new floor plan in JSON format to the device. The device receives this data and displays it to the user.

[1673] (Application example 3)

[1674] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1675] Conventional floor plan design systems struggled to generate floor plan proposals that complied with building laws and local government ordinances, and were unable to reflect users' feelings and requests in real time. This made it difficult to provide optimal floor plan proposals that would increase user satisfaction. Furthermore, when designers created plans, there was a lack of a way to present users with three-dimensional floor plan proposals in real time. This made it impossible to respond quickly to user requests, resulting in an inefficient design process.

[1676] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1677] In this invention, the server includes: means for an architect to use in drafting plans and for showing three-dimensional floor plan proposals to customers; means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels; means for inputting conditions in accordance with building laws in advance; means for including an emotion engine that recognizes the user's emotions, analyzing the emotions from the user's reactions, and automatically generating optimal floor plan proposals based on those emotions; and means for displaying floor plan proposals in real time using a smart device. This makes it possible to reflect the user's emotions and requests in real time and provide optimal floor plan proposals that comply with building laws.

[1678] An "architect" is an engineer who specializes in designing buildings.

[1679] A "draft plan" is an early drawing or plan that shows the basic design and concept of a building.

[1680] A "three-dimensional floor plan" is a blueprint or model that represents the internal structure of a building in three dimensions.

[1681] "Land size and orientation" refers to the area and orientation of the site on which the building will be constructed.

[1682] "Essential facilities" refers to the basic infrastructure and equipment that must be installed in a building.

[1683] "Condition tolerance" refers to the range and degree of constraints that are permissible in a design.

[1684] "Floor plan simulation" is the process of virtually arranging the internal structure of a building and verifying that arrangement.

[1685] "Building laws" refer to legal regulations and standards regarding the design and construction of buildings.

[1686] An "emotion engine" is software that analyzes the user's emotions and controls the system's operation based on the results.

[1687] "Smart devices" refer to electronic devices that have internet connectivity and advanced computing capabilities.

[1688] "Real-time display" refers to the instantaneous presentation of data or information to a user.

[1689] A system for carrying out this invention includes a means for an architect to use in drafting a plan and to show a customer a three-dimensional floor plan proposal, a means for presenting multiple floor plan simulations by selecting the size and orientation of the land, necessary facilities, and other conditions and their tolerance levels, a means for inputting conditions in accordance with building laws in advance, a means including an emotion engine that recognizes the user's emotions, analyzing emotions from the user's reactions, and automatically generating an optimal floor plan proposal based on the emotions, and a means for displaying the floor plan proposal in real time using a smart device.

[1690] System Program

[1691] The server executes the following program: First, it uses the camera on the smart device (e.g., smart glasses) to capture a picture of the user's face and acquires the video data. Next, it uses an emotion engine to analyze the user's emotions. It uses voice recognition technology to convert the user's comments (e.g., "I want a more open feeling") into text data and analyzes it. It then references a legal information database to generate a layout plan that complies with building laws and local government ordinances. The generated layout plan is displayed in real time on the smart device's display.

[1692] Hardware and software used

[1693] Hardware: Smart glasses (camera, display)

[1694] Software: OpenCV (cv2), emotion engine, layout generation engine, legal information database

[1695] Specific examples

[1696] When a user wears smart glasses and says, "I want more openness" while walking around the store, the system analyzes the user's emotions and proposes open layouts in real time that comply with building regulations. For example, if a user says, "I want larger windows," the system analyzes that request, generates a floor plan that includes larger windows, and displays it on the smart glasses' display.

[1697] Prompt Sentence Examples

[1698] "Design an application that allows a user to wear smart glasses and walk around a store, analyzing their speech and emotions, and then recommending optimal layout options in real time that comply with building regulations."

[1699] In this way, it is possible to reflect the user's feelings and requests in real time and provide optimal floor plan proposals that comply with building regulations.

[1700] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1701] Step 1:

[1702] The server captures the user's face using the smart glasses' camera and acquires the video data. The input is the camera video, and the output is the image data of the user's face. This image data is used for subsequent emotion analysis.

[1703] Step 2:

[1704] The server inputs the acquired image data of the user's face into the emotion engine and analyzes the user's emotions. The input is image data of the user's face, and the output is analyzed emotion data. The emotion engine analyzes the image data and identifies the user's emotion (e.g., joy, sadness, surprise, etc.).

[1705] Step 3:

[1706] The user speaks through the smart glasses. The terminal converts the user's speech into text data using speech recognition technology. The input is voice data, and the output is text data. This text data is used to analyze the user's request.

[1707] Step 4:

[1708] The server analyzes the text data and identifies the user's desires. The input is text data, and the output is the user's desire data. For example, a statement such as "I want a more open feeling" is identified as a "desire for a more open feeling."

[1709] Step 5:

[1710] The server references a legal information database and generates a layout plan that complies with building laws and local government ordinances. The input is the user's request data and legal information, and the output is a layout plan. The layout generation engine generates the optimal floor plan plan based on the user's request and legal information.

[1711] Step 6:

[1712] The server displays the generated layout plan on the smart glasses display in real time. The input is the layout plan, and the output is the floor plan displayed on the smart glasses display. The user can check the proposed floor plan in real time.

[1713] In this way, it is possible to reflect the user's feelings and requests in real time and provide optimal floor plan proposals that comply with building regulations.

[1714] 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.

[1715] 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> ) 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.

[1716] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1717] 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.

[1718] [Third embodiment]

[1719] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1720] 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.

[1721] 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).

[1722] 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.

[1723] 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.

[1724] 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).

[1725] 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.

[1726] 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.

[1727] 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.

[1728] 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.

[1729] 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.

[1730] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1731] "Example 1"

[1732] The system of the present invention is used by architects to create draft plans. Specifically, the architect inputs the size and orientation of the land, the necessary facilities, and other conditions and tolerances for those conditions into the system. Based on this information, the system automatically generates multiple floor plan simulations and presents them to the architect. This allows the architect to efficiently show the client three-dimensional floor plan proposals.

[1733] "Example 2"

[1734] Furthermore, the system of this invention has the ability to select only from "reference knowledge" prepared by manufacturers of wall and flooring materials. Designers can use this function to select not only the floor plan but also fixtures and interiors that fit their image. The selected fixtures and interiors are generated by image generation AI and presented to the designer. This allows the designer to provide a floor plan proposal that more precisely meets the customer's requests.

[1735] "Example 3"

[1736] The system of the present invention also has the ability to pre-load conditions that comply with building laws. Specifically, the system stores legal information such as building laws and local government ordinances in a database, and takes this legal information into account when generating floor plan simulations. This makes it possible to generate floor plan proposals that do not violate any laws.

[1737] The processing flow of each embodiment will be described below.

[1738] "Example 1"

[1739] Step 1: The architect inputs the size and orientation of the land, the necessary facilities, and other conditions and tolerances for the conditions into the system.

[1740] Step 2: Based on this information, the system automatically generates multiple floor plan simulations.

[1741] Step 3: The generated floor plan simulation is presented to the architect, who then uses it to present a three-dimensional floor plan proposal to the client.

[1742] "Example 2"

[1743] Step 1: The designer uses the system's "reference knowledge" function to select wall and floor materials.

[1744] Step 2: The selected features and interior are generated using image generation AI.

[1745] Step 3: The generated images of fixtures and interiors are presented to the architect, who then uses them to present a floor plan to the client.

[1746] "Example 3"

[1747] Step 1: The system maintains legal information such as building codes and local government ordinances in a database.

[1748] Step 2: The system takes this legal information into account when generating the simulated floor plan.

[1749] Step 3: This makes it possible to generate floor plan proposals that do not violate any laws.

[1750] Example 1

[1751] Next, a description will be given of Example 1 of Form 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."

[1752] Previous systems used by architects to draft plans had limited means of showing floor plan proposals in three dimensions, making it difficult to efficiently propose them to clients. Furthermore, even if the land size, orientation, necessary facilities, and other conditions and their tolerances were input, the system lacked the functionality to automatically generate multiple floor plan simulations. Furthermore, there were insufficient means to consider conditions in accordance with building laws in advance, placing a heavy burden on architects.

[1753] 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. In this invention, the server includes a means for receiving input data and performing preprocessing, a means for inputting a prompt sentence to the generation AI model and generating a floor plan simulation, and a means for visualizing the generated floor plan simulation. This allows the designer to efficiently generate multiple floor plan simulations and propose them to the customer in three dimensions. In addition, by taking into account conditions in accordance with building laws in advance, the burden on the designer can be reduced.

[1754] An "architect" is an engineer who specializes in designing buildings.

[1755] "Drafting a plan" is the initial stage of creating a basic design for a building.

[1756] The "customer" is the client who requests the architect to design a building.

[1757] A "three-dimensional floor plan" is a blueprint that represents the floor plan of a building in three dimensions.

[1758] "Land size" refers to the area of ​​land available for building a structure.

[1759] "Land orientation" refers to the direction of the land on which a building is to be constructed.

[1760] "Necessary facilities" are facilities and equipment that must be installed in a building.

[1761] "Other conditions" are additional requirements or constraints that must be taken into account in the design of a building.

[1762] "Condition tolerance" refers to the degree to which conditions are applied flexibly in the design.

[1763] "Floor plan simulation" is the process of virtually calculating and verifying the floor plan of a building.

[1764] "Building laws" are legal regulations and standards governing the design and construction of buildings.

[1765] "Input data" is information provided by a user to a system.

[1766] "Preprocessing" is the process of analyzing input data and converting it into a format suitable for subsequent processing.

[1767] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate data.

[1768] A "prompt sentence" is an instruction sentence input to a generative AI model.

[1769] "Visualization" is the process of representing data or information visually.

[1770] "User" refers to the designers and other users of this system.

[1771] This invention is a system that allows architects to create draft plans and show three-dimensional floor plan proposals to clients. The system automatically generates multiple floor plan simulations and presents them to architects by inputting the land size and orientation, necessary facilities, and other conditions and tolerances for those conditions.

[1772] The user (architect) first uses a device (PC or tablet) to input the land size, orientation, required facilities, other conditions, and their tolerance levels. For example, the user might input "Land size: 200 square meters," "Land orientation: south-facing," "Required facilities: 3LDK, 2 parking spaces, garden," "Other conditions: barrier-free," and "Condition tolerance level: high."

[1773] The terminal sends the data entered by the user to the server. Specifically, the terminal converts the input data into JSON format and sends it to the server using an HTTP request. The server receives the data sent from the terminal and performs preprocessing. Preprocessing involves formatting the data and removing unnecessary information.

[1774] The server generates a prompt based on the preprocessed data and inputs it into a generative AI model (for example, a general-purpose generative AI model). An example of a prompt might be, "Please propose a floor plan for a 200-square-meter plot of land facing south, with 3 bedrooms, a living room, kitchen, kitchen, and kitchen, two parking spaces, and a garden. The conditions are highly tolerant." The generative AI model generates multiple floor plan simulations based on this prompt.

[1775] The server inputs the floor plan simulation obtained from the generative AI model into 3D modeling software (e.g., general-purpose 3D modeling software) and visualizes it. This displays the proposed floor plan in three dimensions. The visualized data is generated as an image file or 3D model file and sent to the terminal as an HTTP response.

[1776] The device displays the visualized data received from the server to the user, who can then check multiple floor plan proposals on the device screen and efficiently propose them to the customer.

[1777] This system allows designers to efficiently generate multiple floor plan simulations and propose them to customers in three dimensions. It also reduces the burden on designers by taking into account building regulations in advance.

[1778] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1779] Step 1:

[1780] The user inputs the input data into the terminal. The user inputs the land size, orientation, required facilities, other conditions, and their tolerance levels into the terminal. For example, the user might input "Land size: 200 square meters," "Land orientation: south-facing," "Required facilities: 3LDK, 2 parking spaces, garden," "Other conditions: barrier-free," and "Condition tolerance level: high." The input data is collected through an input form on the terminal.

[1781] Step 2:

[1782] The terminal sends the input data to the server. The terminal converts the data entered by the user into JSON format and sends it to the server using an HTTP request. The input data is sent to the server as a JSON object containing the land size, orientation, required facilities, other conditions, and their tolerances.

[1783] Step 3:

[1784] The server receives the data and performs preprocessing. The server receives the JSON data sent from the device and formats the data and removes unnecessary information. For example, it checks the format of the input data and whether any information is missing. The preprocessed data is converted into a format suitable for the generative AI model.

[1785] Step 4:

[1786] The server inputs a prompt statement into the generative AI model and generates a floor plan simulation. The server generates a prompt statement based on the preprocessed data and inputs it into the generative AI model. An example of a prompt statement might be, "Please propose a floor plan for a 200 square meter plot of land facing south, with 3 bedrooms, living room, kitchen, kitchenette, parking for two cars, and a garden, and that is barrier-free. The conditions are highly tolerant." The generative AI model generates multiple floor plan simulations based on this prompt statement. The generated floor plan simulations are returned to the server in text or data format.

[1787] Step 5:

[1788] The server visualizes the generated floor plan simulation using 3D modeling software. The server inputs the floor plan simulation obtained from the generative AI model into 3D modeling software and visualizes it. For example, general-purpose 3D modeling software is used to display the proposed floor plan in three dimensions. The visualized data is generated as an image file or a 3D model file.

[1789] Step 6:

[1790] The server sends the visualized data to the terminal. The server sends the visualized floor plan simulation data to the terminal as an HTTP response. The visualization data is sent to the terminal as an image file or a 3D model file.

[1791] Step 7:

[1792] The device displays a floor plan simulation to the user. The device then displays the visualization data received from the server to the user. The user can check multiple floor plan proposals on the device screen and make efficient proposals to the customer. For example, a 3D model can be displayed on the device display, allowing the user to freely rotate and zoom.

[1793] (Application example 1)

[1794] Next, a description will be given of Application Example 1 of Form 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."

[1795] Conventional floor plan simulation systems used by designers have difficulty efficiently presenting three-dimensional floor plan proposals, even when users input conditions such as the size and orientation of the land and the necessary equipment. Furthermore, there was a lack of systems that could automatically generate optimal furniture layout plans and allow users to check them in a 3D view when simulating the layout and furniture arrangement of their home. This made it difficult for users to efficiently arrange and purchase furniture.

[1796] 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.

[1797] In this invention, the server includes: a means for an architect to draft a plan and show the customer a three-dimensional floor plan; a means for presenting multiple floor plan simulations by selecting the land size and orientation, necessary facilities, and other conditions and their tolerance; a means for inputting conditions in accordance with building regulations in advance; a means for a generative AI model to generate multiple furniture arrangement plans based on the floor plan information entered by the user; a means for rendering and displaying the generated plans as 3D models; and a means for saving the plans selected by the user and generating a shopping list. This enables users to efficiently simulate the floor plan and furniture arrangement of their home, check the optimal furniture arrangement plan in a 3D view, and generate a shopping list.

[1798] An "architect" is an engineer who specializes in designing buildings and interiors.

[1799] A "draft plan" is a document or drawing created by an architect at an early stage that shows the basic concept and ideas of the design.

[1800] A "three-dimensional floor plan" is a blueprint or model that represents the interior space of a building in three dimensions.

[1801] "Land size" refers to the area of ​​the site on which the building is constructed.

[1802] "Orientation" is information that indicates the direction in which the building faces.

[1803] "Necessary facilities" refers to the basic facilities and equipment that should be installed in a building.

[1804] "Condition tolerance" refers to the range and flexibility of conditions that are acceptable in the design.

[1805] "Floor plan simulation" is a process of virtually testing the layout of the interior space of a building based on input conditions.

[1806] "Building laws" refer to legal regulations and standards governing the design and construction of buildings.

[1807] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate data based on specific conditions.

[1808] A "furniture arrangement plan" is a design proposal that shows how furniture should be arranged in the interior space of a building.

[1809] A "3D model" is digital data that represents an object or space in three-dimensional space.

[1810] "Rendering" is the process of generating images to visually represent a 3D model.

[1811] A "shopping list" is a document or data that lists the furniture and equipment selected by a user.

[1812] The system for implementing this invention is used by architects to draft plans and show three-dimensional floor plan proposals to clients. The system automatically generates and presents multiple floor plan simulations by inputting the land size and orientation, necessary facilities, and other conditions and tolerances for those conditions. Furthermore, based on the floor plan information entered by the user, a generative AI model generates multiple furniture layout plans, which are then rendered and displayed as 3D models.

[1813] Hardware and software used

[1814] 1. Hardware:

[1815] Smartphone (iOS or Android)

[1816] GPU for 3D rendering

[1817] 2. Software:

[1818] Development environment: Unity (3D rendering), TensorFlow (generative AI model)

[1819] Database: Firebase (storing user data)

[1820] API: Google Maps API (location information acquisition)

[1821] Data processing and calculation

[1822] 1. User Input:

[1823] Using a smartphone application, users input the land size, orientation, required amenities, and other conditions and tolerances for those conditions.

[1824] 2. Generative AI Model:

[1825] The server uses a generative AI model to generate multiple furniture layout plans based on the floor plan information entered by the user.

[1826] The generative AI model is built using TensorFlow and generates optimal furniture placement plans based on user input.

[1827] 3. 3D rendering:

[1828] The server renders the generated furniture layout plan as a 3D model and displays it on a smartphone.

[1829] Unity is used for 3D rendering to generate visually realistic models.

[1830] 4. Data storage and shopping list generation:

[1831] The plan selected by the user is stored in Firebase for future reference.

[1832] It also generates a shopping list based on the selected plan and provides it to the user.

[1833] Specific examples

[1834] 1. User Input:

[1835] Land size: 100 square meters

[1836] Orientation: South

[1837] Required facilities: kitchen, living room, bathroom, bedroom

[1838] 2. Prompt for the generative AI model:

[1839] The land area is 100 square meters, facing south. The required facilities are a kitchen, living room, bathroom, and bedroom. Please generate the optimal furniture layout plan based on these conditions.

[1840] 3. Example output:

[1841] Plan 1: Open floor plan with integrated kitchen and living room

[1842] Plan 2: A plan that prioritizes privacy with a separate living room and bedroom

[1843] In this way, the system provides a generative AI model that automatically generates multiple furniture layout plans based on information entered by the user and allows users to check them in a 3D view. This allows users to efficiently simulate their home layout and furniture placement, check the optimal furniture layout plan in 3D view, and generate a shopping list.

[1844] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1845] Step 1:

[1846] The user launches the smartphone application and inputs the land size, orientation, required facilities, and other conditions and tolerances for those conditions. The input data is sent from the smartphone device to the server. The input data includes the land size (e.g., 100 square meters), orientation (e.g., facing south), and required facilities (e.g., kitchen, living room, bathroom, bedroom).

[1847] Step 2:

[1848] The server generates a prompt for the generative AI model based on the received input data. The generated prompt reflects the conditions entered by the user. For example, a prompt might be generated that reads, "The land is 100 square meters in size and faces south. The required facilities are a kitchen, living room, bathroom, and bedroom. Based on these conditions, please generate the optimal furniture layout plan."

[1849] Step 3:

[1850] The server inputs the generated prompt sentences into a generative AI model to generate multiple furniture layout plans. The generative AI model is built using TensorFlow and generates the optimal furniture layout plan based on the input prompt sentences. The output is multiple furniture layout plans.

[1851] Step 4:

[1852] The server renders the generated furniture layout plan as a 3D model using Unity, generating a visually realistic 3D model. The output is a 3D model.

[1853] Step 5:

[1854] The server then sends the rendered 3D model to the smartphone device and displays it to the user, who can then view the generated furniture layout plans in 3D through the smartphone application.

[1855] Step 6:

[1856] The user selects the most suitable plan from the displayed furniture layout plans, and the selected plan is sent from the smartphone device to the server.

[1857] Step 7:

[1858] The server saves the selected plan in Firebase for future reference, and generates a shopping list based on the selected plan and provides it to the user. The shopping list includes a list of furniture and equipment included in the selected plan.

[1859] Through the above processing steps, users can efficiently simulate the layout and furniture arrangement of their home, check the optimal furniture arrangement plan in a 3D view, and generate a shopping list.

[1860] Example 2

[1861] Next, a description will be given of Example 2 of Form 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."

[1862] With conventional design support systems, it was difficult for designers to concretely express detailed images of floor plans and interiors, and it was also difficult to precisely respond to customer requests. Furthermore, there were limited options for wall and floor materials, restricting design freedom. This often prevented designers from making satisfactory proposals to customers, making the design process inefficient.

[1863] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1864] In this invention, the server includes means for the designer to select wall and floor materials from reference knowledge, means for the designer to input images of the floor plan and interior, means for the server to collect data on the selected fixtures and interior, means for the server to generate images using image generation AI, means for the server to present the generated images to the designer, and means for the designer to check the generated images and make corrections as necessary. This enables the designer to quickly and accurately generate and propose detailed images of the floor plan and interior based on the customer's requests.

[1865] An "architect" is an engineer who specializes in designing buildings and designs floor plans and interiors.

[1866] A "draft plan" is an early stage plan that shows the basic design and layout of a building.

[1867] A "three-dimensional floor plan" is a blueprint or model that represents the floor plan of a building in three dimensions.

[1868] "Land size and orientation" refers to the area and orientation of the land on which the building will be constructed.

[1869] "Essential facilities" refers to the basic facilities and equipment that should be installed in a building.

[1870] "Condition tolerance" refers to the range and flexibility of conditions that are acceptable in the design.

[1871] "Floor plan simulation" is the process of virtually trying out a designed floor plan and visually confirming the results.

[1872] "Building laws" refer to legal regulations and standards governing the design and construction of buildings.

[1873] "Reference knowledge" refers to standard information and data provided by manufacturers of wall and flooring materials, etc.

[1874] "Image generation AI" refers to artificial intelligence technology that generates images based on input text or data.

[1875] "Fixtures" refers to decorations and structures installed inside and outside a building.

[1876] "Interior" refers to the design and decoration of the interior space of a building.

[1877] "Collecting data" refers to the process of gathering and organizing the necessary information or data.

[1878] "Generating an image" refers to creating a visual picture or model based on input information.

[1879] "Modifying" refers to making changes or adjustments to the generated image or design.

[1880] This invention is a system used by architects when designing the layout and interior of buildings, and allows them to select from "reference knowledge" provided by manufacturers of wall and flooring materials, among other things, and generate specific images using image generation AI. The system is operated by the user (architect) using a dedicated terminal, and the server collects data and generates images.

[1881] Hardware and software used

[1882] Device: A device such as a computer or tablet used by an architect.

[1883] Server: A server for collecting data, processing, and generating images.

[1884] Image generation AI: Image generation models such as DALL-E.

[1885] Data processing and calculation

[1886] 1. A user logs into the system

[1887] The user accesses the system using a terminal and enters their user ID and password on the login screen. The server performs authentication, and if authentication is successful, the main screen is displayed.

[1888] 2. The user selects wall and floor materials from reference knowledge.

[1889] The user browses through a list of wall and flooring materials offered by manufacturers on the system interface and selects the desired material, which is then sent to the server and temporarily stored.

[1890] 3. The user inputs the floor plan and interior image

[1891] The user inputs a specific image of the floor plan and interior into the text box. For example, they can input a request such as "I want wood-grain flooring in the living room and white walls."

[1892] 4. The server collects data on the selected features and interior.

[1893] The server collects data on the selected wall and floor materials from the database, including images of the materials, texture information, and manufacturer information.

[1894] 5. The server generates the image using image generation AI

[1895] The server sends a prompt to the image generation AI based on the collected data and the image entered by the user. The prompt specifically describes the user's request. The image generation AI analyzes the prompt and generates a corresponding image.

[1896] 6. The server presents the generated image to the user

[1897] The server receives the images generated by the image generation AI and sends them to the user's device, where the user can view the generated images on the system interface.

[1898] 7. The user checks the generated image and makes corrections if necessary.

[1899] The user can review the generated image and make any necessary modifications or regenerate it, for example, changing the wall color or adjusting the furniture placement. Once modifications are complete, the user saves the final design and is ready to present it to the client.

[1900] Specific examples

[1901] For example, if an architect inputs a request such as "Use wood-grain flooring and white walls in the living room," the system will process it as follows:

[1902] 1. The designer logs into the system.

[1903] 2. The architect selects wood-grain flooring and white wall coverings from reference knowledge.

[1904] 3. The architect inputs an image of "wood-grain flooring in the living room and white walls."

[1905] 4. The server retrieves images and texture information for "white wall material" and "wood-grain floor material" from the database.

[1906] 5. The server sends the prompt "Use wood-grain flooring and white walls in the living room" to the image generation AI and receives the generated image.

[1907] 6. The server sends the generated image to the designer's terminal, and the designer checks the image on the interface.

[1908] 7. The architect types "change the wall color to blue" and sends the prompt to the image generation AI again. A new image is generated and presented to the architect.

[1909] Prompt Sentence Examples

[1910] "The living room will have wood-grain flooring and white walls. The furniture will be modern, with a gray sofa and a glass table."

[1911] By inputting this prompt into the image generation AI, an image of the living room the designer envisions is generated.

[1912] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1913] Step 1:

[1914] A user logs in to the system.

[1915] Input: User ID and password.

[1916] Data processing: The server checks the entered user ID and password against the database and performs authentication.

[1917] Output: If authentication is successful, display the main screen.

[1918] Specific operation: The user enters the user ID and password on the login screen of the terminal and clicks the "Login" button. The server accesses the database and verifies the authentication information. If authentication is successful, the main screen is displayed on the terminal.

[1919] Step 2:

[1920] The user selects wall and floor materials from reference knowledge.

[1921] Input: A list of wall and flooring materials.

[1922] Data processing: The server temporarily stores information about the selected wall and floor materials.

[1923] Output: Information about the selected wall and floor coverings.

[1924] Specific operation: The user selects wall and floor materials using drop-down menus and search functions on the system interface. The selected materials are sent to the server and temporarily stored.

[1925] Step 3:

[1926] The user inputs the floor plan and interior image.

[1927] Input: A concrete image (text) of the floor plan and interior.

[1928] Data processing: The server analyzes the input image and generates a prompt.

[1929] Output: The generated prompt statement.

[1930] Specific behavior: The user enters "I want wood-effect flooring and white walls in the living room" into the text box and clicks the "Submit" button. The server parses the entered text and generates a prompt.

[1931] Step 4:

[1932] The server collects data on the selected fixtures and interiors.

[1933] Input: Information about the selected wall and floor covering.

[1934] Data processing: The server retrieves images, texture information, and manufacturer information of the selected material from the database.

[1935] Output: Collected data.

[1936] Specific operation: The server accesses the database and obtains images, texture information, and manufacturer information of the selected wall or floor material.

[1937] Step 5:

[1938] The server generates the image using image generation AI. 【1939...

Claims

1. A means for presenting a plurality of simulations of floor plans by selecting the size and orientation of the land, necessary facilities, design conditions, and tolerances of the design conditions; A means to incorporate conditions in accordance with building laws in advance, A means for recognizing a user's emotion; means for analyzing feedback from said users; means for adjusting the simulation of the floor plan based on at least one of the recognized user emotion and the analyzed feedback; A system including:

2. A means for generating an interior design that matches selected building materials from reference knowledge, which is information on building materials provided by manufacturers, using the image generation model; The system of claim 1 .

3. means for generating a shopping list of items required for the floor plan selected by the user; The system of claim 1 .

Images