System

Abstract

To provide a system for automatically and efficiently performing from design to construction of a house by utilizing generated AI.SOLUTION: A generating means for generating a house design drawing conforming to the Building Standard Law by using the generated AI, a transmitting means for transmitting the generated house design drawing to the user's terminals, a generating means for generating an execution plan and a material list based on the final design drawing and transmitting them to a factory, a manufacturing means for manufacturing parts of the house by a 3D printer based on the material list generated in the factory, and an assembling means for transporting the manufactured parts to the site and assembling the house by an execution team. AI.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 recent years, the housing market has been demanding the rapid provision of low-cost, high-quality housing. However, with conventional construction methods, the process from design to construction takes a long time and is expensive, resulting in problems such as housing shortages and rising costs. It is also difficult to provide housing that complies with the Building Standards Act in a short period of time. It is necessary to solve these issues and establish a method for providing housing quickly and at low cost that meets user demand. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that utilizes generative AI to automatically and efficiently carry out the entire process from home design to construction. Specifically, the system includes an input means for users to input basic home requirements, a transmission means for transmitting the required data to a server, a generation means for generating home blueprints that comply with the Building Standards Act using generative AI, a regeneration means for transmitting the generated blueprints to the user's device and receiving and adjusting correction data, a generation means for generating a construction plan and materials list based on the final blueprints, a fabrication means for producing parts using a 3D printer in a factory, and an assembly means for transporting the produced parts to the site and quickly assembling them. This makes it possible to provide high-quality homes at low cost in a short period of time.

[0006] "User" refers to an individual or organization seeking to provide housing.

[0007] "Terminal" refers to the electronic device used by a user to input requirements and view blueprints.

[0008] "Input means" refers to a device or software having an interface for a user to input basic housing requirements.

[0009] "Transmission means" refers to a device or software for transmitting input request data to a server.

[0010] "Server" refers to a computer system that analyzes the received request data and generates a house blueprint using generation AI.

[0011] "Generation means" refers to the function of using generation AI to create residential blueprints that comply with the Building Standards Act based on the user's requests.

[0012] "Generative AI" refers to software or models that use artificial intelligence techniques to generate optimal home blueprints.

[0013] The "regeneration means" refers to a function for readjusting the design drawing by reflecting modified data from the user.

[0014] A "construction plan" refers to a plan that shows the construction schedule and procedures for a house based on the final design drawings.

[0015] "Materials List" refers to a list containing a list of materials required for construction.

[0016] "Factory" refers to a facility where housing components are fabricated based on construction plans and material lists.

[0017] "Means of production" refers to the function of using a 3D printer to produce housing components based on a materials list.

[0018] A "3D printer" refers to a device that creates three-dimensional objects based on three-dimensional data.

[0019] "Assembly means" refers to the function of assembling parts transported to the site to complete the house. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0041] The present invention relates to a system in which a user inputs basic requirements for a house, a server generates blueprints based on the requirements using AI, and the server then promptly carries out construction. A specific embodiment of this system will be described below.

[0042] 1. Inputting user requirements and generating design drawings

[0043] User inputs request

[0044] The user starts up a terminal (such as a PC or smartphone) and inputs basic housing requirements, including the floor plan, budget, and types of materials, into an input form interactively.

[0045] Server receives requested data

[0046] The device sends the desired data entered by the user to the server. The server analyzes the received data and activates the generation AI to generate blueprints that comply with the Building Standards Act. The generation AI uses pre-trained data to create blueprints that best meet the user's needs.

[0047] 2. Check and fine-tune the design

[0048] The server sends the blueprint

[0049] The generated blueprint is sent from the server to the user's device, where the user can view the blueprint on their device screen. For example, detailed layouts such as the layout of the living room and the location of windows are displayed.

[0050] User enters corrections

[0051] The user can check the blueprint and send any necessary corrections to the server from their device. For example, they can make specific changes such as "move the window a little further to the left" or "add a balcony."

[0052] Server Regeneration

[0053] The server restarts the generation AI based on the correction information received from the user and regenerates the blueprint, thus completing the final blueprint that meets the user's wishes.

[0054] 3. Generate construction plans and material lists

[0055] The server generates the construction plan and material list

[0056] The server creates a construction plan based on the final design drawings and generates a list of required materials. The construction plan includes the order of work and deadlines, while the material list lists the specific types and quantities of materials.

[0057] Sending to partner factories

[0058] The generated construction plan and materials list are sent from the server to a partner factory, which prepares a 3D printer and produces the house components based on the information sent.

[0059] 4. 3D printed parts production and assembly

[0060] In-factory production

[0061] The partner factory uses 3D printers to produce each part of the house based on the materials list, and the parts are checked under strict quality control.

[0062] Parts transportation and on-site assembly

[0063] The manufactured parts are transported to the construction site, where the construction team quickly assembles the parts to complete the house according to the construction plan provided by the server, which details, for example, the order in which wall panels should be assembled and the steps for laying the foundation.

[0064] Specific examples

[0065] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[0066] 1. User inputs request

[0067] A newlywed couple enters their requirements for a one-bedroom, one-room kitchen, a budget of 20 million yen, and a steel-reinforced concrete structure into a terminal.

[0068] 2. The server creates the blueprint

[0069] The server receives the requested data and creates the optimal design using a generation AI.

[0070] 3. User makes corrections

[0071] Check the blueprint and enter any modifications you would like to make, such as "change the window position" or "make the living room larger."

[0072] 4. The server regenerates

[0073] Generate a new blueprint that reflects the modifications and confirm it.

[0074] 5. Generate construction plans and material lists

[0075] A construction plan and material list are generated based on the finalized drawings and sent to the factory.

[0076] 6. Manufacturing parts in factories

[0077] Parts are manufactured using 3D printers and quality controlled.

[0078] 7. On-site assembly

[0079] The parts are transported to the site and assembled by the construction team to complete the home.

[0080] The above is an embodiment of the present invention. This system makes it possible to provide high-quality housing at low cost in a short period of time.

[0081] The processing flow will be explained below.

[0082] Specific processing steps of the program

[0083] Step 1: User input

[0084] 1.1 User starts terminal

[0085] The user turns on a device such as a smartphone or PC and opens a dedicated application or web browser.

[0086] 1.2 User fills out request form

[0087] The user enters basic information about the home they are looking for (e.g., layout, budget, materials to be used, etc.) into the input form and presses the submit button.

[0088] Step 2: Receiving and analyzing the requested data on the server

[0089] 2.1 The device sends the requested data to the server

[0090] The terminal transmits the request data input by the user to the server.

[0091] 2.2 The server receives the requested data

[0092] The server receives the transmitted request data and begins analyzing it.

[0093] Step 3: Generate blueprints on the server

[0094] 3.1 The server starts the generated AI

[0095] The server activates a generation AI based on the analyzed request data and generates a blueprint.

[0096] 3.2 Server generates blueprint

[0097] The generation AI generates house blueprints that best meet the user's needs while complying with the Building Standards Act.

[0098] Step 4: Check and modify the blueprint

[0099] 4.1 The server sends the blueprint to the device

[0100] The server sends the generated design drawings to the user's terminal.

[0101] 4.2 User checks the design drawing

[0102] The user checks the blueprint on the terminal and considers whether there are any problems with the contents.

[0103] 4.3 User enters corrections

[0104] The user inputs modifications to the blueprint (e.g., changing the position of a window, adding a room, etc.) into the terminal and sends them to the server.

[0105] Step 5: Regenerate the blueprint on the server

[0106] 5.1 Server receives modified data

[0107] The server receives the correction data sent by the user.

[0108] 5.2 Server restarts generated AI

[0109] The server will restart the generation AI and regenerate the blueprint based on the modified data.

[0110] 5.3 The server confirms the final design

[0111] The server checks whether the new design meets the user's requirements and confirms the final design.

[0112] Step 6: Generate construction plan and materials list

[0113] 6.1 Server creates construction plan

[0114] The server will create a detailed construction plan based on the final design drawings.

[0115] 6.2 Server generates ingredients list

[0116] The server generates a list of materials required for construction.

[0117] 6.3 Server sends data to factory

[0118] The server transmits the construction plan and material list to the subcontract factory.

[0119] Step 7: Factory parts production

[0120] 7.1 Factory receives data

[0121] The subcontract factory receives the construction plan and material list sent from the server.

[0122] 7.2 Factories prepare for 3D printers

[0123] The factory sets up the 3D printer and begins producing parts based on the materials list.

[0124] 7.3 3D printers produce parts

[0125] A 3D printer will create the components of the house according to the specified design.

[0126] Step 8: Transport and assemble the parts

[0127] 8.1 Factory packs and transports parts

[0128] The factory packs the completed parts and transports them to the construction site.

[0129] 8.2 Installation team receives parts

[0130] The construction team receives the parts on site and performs the necessary checks.

[0131] 8.3 The construction team assembles the house

[0132] The construction team quickly assembles the house based on the construction plan provided by the server, resulting in the completion of a high-quality home in a short period of time.

[0133] The above is the specific flow of program processing. This system allows users to obtain low-cost housing efficiently and quickly.

[0134] Example 1

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

[0136] The conventional housing design and construction process is time-consuming and costly, and it is difficult to accurately reflect the user's needs. Furthermore, there are many uncertainties in the design changes and material procurement processes, which frequently result in project delays and budget overruns. The purpose of this invention is to solve these problems and enable housing design and construction that quickly and accurately meets the user's needs.

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

[0138] In this invention, the server includes an input means for a user to input basic requirements for a home, a transmission means for transmitting the user's requirement data to the server, a generation means for receiving the requirement data and generating a home blueprint using a generative AI model, a transmission means for transmitting the generated home blueprint to the user's terminal, a regeneration means for receiving correction data from the user and readjusting the blueprint using the generative AI model, a generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a manufacturing facility, a manufacturing means for manufacturing home components using a 3D printer based on the generated materials list at the manufacturing facility, and an assembly means for transporting the manufactured components to a site and having a construction team assemble the home. This makes it possible to quickly and accurately reflect user requirements and provide high-quality homes in a short period of time.

[0139] "Basic housing requirements" refer to the user's desired housing conditions, such as layout, budget, and materials to be used.

[0140] "Input means" refers to a device or software interface that allows a user to input basic housing requirements.

[0141] The "transmission means" refers to a device or software that has the function of transmitting the user's requested data to the server.

[0142] "Server" refers to the machine and software that processes data received from users, generates house blueprints, and draws up construction plans.

[0143] A "generative AI model" is an artificial intelligence program that uses machine learning technology to automatically generate house blueprints from training data.

[0144] "Generation means" refers to devices or software that have the function of using generative AI models to create house blueprints, construction plans, and material lists.

[0145] A "terminal" is a device such as a personal computer or smartphone operated by a user.

[0146] A "regeneration means" is a device or software that has the function of readjusting a design using a generative AI model based on correction data from the user.

[0147] A "construction plan" refers to a plan that shows the series of work processes and schedule required to build a house.

[0148] A "materials list" is a list that lists the types and quantities of materials needed to build a house.

[0149] A "manufacturing facility" is a place where housing components are produced using 3D printers and high-precision machine tools.

[0150] A "production tool" is any equipment or software used to produce parts based on a materials list at a manufacturing facility.

[0151] "Assembly means" refers to the equipment and methods for transporting fabricated components to the site and assembling the home.

[0152] MODE FOR CARRYING OUT THE INVENTION

[0153] The present invention relates to a system in which a user inputs basic requirements for a house, a server generates blueprints based on those requirements using AI, and the server then promptly carries out construction. A specific method for implementing this system is described below.

[0154] Hardware and Software Configuration

[0155] 1. Terminal

[0156] Hardware: PC, smartphone

[0157] Software: Web browser

[0158] 2. Server

[0159] Hardware: High-performance servers (e.g. cloud servers in a data center)

[0160] Software: drafting software (e.g., AutoCAD, Revit), generative AI (e.g., GPT-4)

[0161] 3. Manufacturing Facilities

[0162] Hardware: 3D printers, high-precision machine tools

[0163] Software: Parts production management software (e.g., Siemens NX)

[0164] Specific operation of the system

[0165] 1. User request input

[0166] Users use a device (PC or smartphone) to input their basic housing requirements on a web browser. Specific requirements such as floor plan, budget, and types of materials are entered interactively in the input form.

[0167] 2. Receipt and analysis of requested data by the server

[0168] The device sends the input request data to the server, which then uses a data analysis module to extract elements such as floor plan, budget, and type of materials, and formats them as input data for the generative AI model.

[0169] 3. Server-based blueprint generation

[0170] The server inputs the formatted request data into a generative AI model (e.g., GPT-4). The prompt text used is something like, "Please generate a blueprint for a 1LDK house with a budget of 20 million yen and steel-framed concrete construction." The generative AI generates the blueprint, and the server receives the results.

[0171] 4. Submit your blueprints

[0172] The generated blueprint is sent from the server to the user's device, where the user can view it in a web browser. This blueprint includes detailed information such as the floor plan, interior, and window placement.

[0173] 5. Check and correct the design drawings

[0174] The user checks the blueprint and inputs any modifications they wish to make, such as "move the window a little further to the left" or "add a balcony." The modification data is then sent from the terminal to the server.

[0175] 6. Server Regeneration

[0176] The server re-runs the generative AI model based on the corrections received from the user and regenerates the blueprint. This process can be repeated until a new blueprint is generated.

[0177] 7. Generate construction plans and material lists

[0178] Once the final design drawings are finalized, the server automatically generates a construction plan and materials list based on them. The construction plan includes the order of work and deadlines, while the materials list includes the specific types and quantities of materials.

[0179] 8. Transmission of Information to Manufacturing Facilities

[0180] The server sends the construction plan and materials list to a manufacturing facility, which uses the information to create the home's components using 3D printers and high-precision machine tools.

[0181] 9. Parts production, transportation and assembly

[0182] The parts manufactured at the manufacturing facility are transported to the construction site under quality control, and the construction team quickly assembles the parts according to the construction plan provided by the server to complete the home.

[0183] Specific examples

[0184] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[0185] 1. User inputs request

[0186] The newlyweds input their requirements into the terminal: "1LDK," "budget of 20 million yen," and "steel-reinforced concrete construction."

[0187] 2. The server creates the blueprint

[0188] The server receives the requested data and uses the generation AI to input a prompt such as, "Please generate a blueprint for a 1LDK house with a budget of 20 million yen and steel-reinforced concrete construction," and creates the optimal blueprint.

[0189] 3. User makes corrections

[0190] Check the blueprint and enter corrections such as "change the window position" or "make the living room larger."

[0191] 4. The server regenerates

[0192] Regenerate a new blueprint that reflects the modifications and confirm.

[0193] 5. Generate construction plans and material lists

[0194] Based on the finalized drawings, a construction plan and material list are generated and sent to the manufacturing facility.

[0195] 6. Parts are made in a manufacturing facility

[0196] Parts are produced using 3D printers and quality control is performed.

[0197] 7. On-site assembly

[0198] The parts are transported to the site and assembled by the construction team to complete the home.

[0199] This system makes it possible to quickly reflect user requests and provide high-quality housing in a short period of time.

[0200] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0201] Step 1:

[0202] The user inputs the basic requirements for the home from the evaluation device (PC, smartphone, etc.). The user inputs the floor plan, budget, type of materials, etc. into a dedicated form in a web browser. The input data is sent from the evaluation device to the server.

[0203] Step 2:

[0204] The server receives the request data sent from the device and stores it in a database. The server then launches a data analysis module, analyzes the request data, extracts information such as floor plan, budget, and type of materials, and formats it as input data for the generative AI model. This formatted data becomes the output of the analysis.

[0205] Step 3:

[0206] The server launches a generative AI model based on the formatted request data. A prompt sentence is used as input for the generative AI model. For example, the input text is "Please generate blueprints for a 1LDK house with a budget of 20 million yen and steel-framed concrete construction." The generative AI model generates the blueprint data, which is received by the server. The generated blueprint data is the output.

[0207] Step 4:

[0208] The server sends the generated blueprint data to the user's device, which then displays the received blueprint data in a web browser. The user can then check the blueprint, including the floor plan, interior, and window placement.

[0209] Step 5:

[0210] The user checks the blueprint and inputs any modifications they would like to make into the terminal, for example, by inputting specific requests such as "move the window a little further to the left" or "add a balcony." The inputted modifications are then sent back to the server.

[0211] Step 6:

[0212] The server receives the modified data sent by the user and again analyzes the modifications using the data analysis module. Based on the modified information obtained through the analysis, the generative AI model is launched again. An updated prompt such as "Please regenerate the blueprint for a 1LDK house with windows repositioned and a balcony added, with a budget of 20 million yen and steel-concrete construction" is used. The generative AI model generates new blueprint data, which is received by the server. The new blueprint data becomes the output.

[0213] Step 7:

[0214] The server automatically generates a construction plan and materials list based on the final design drawing data. The construction plan includes the order of processes and deadlines, while the materials list includes the specific types and quantities of materials. The generated construction plan and materials list are output.

[0215] Step 8:

[0216] The server then sends the generated construction plan and materials list to the manufacturing facility, which uses the received information to produce the home's components using 3D printers and high-precision machine tools. The manufactured components are the output.

[0217] Step 9:

[0218] The parts manufactured at the manufacturing facility undergo quality control before being transported to the construction site. The construction team quickly assembles the parts according to the construction plan provided by the server to complete the house. The completed house is the final output.

[0219] (Application example 1)

[0220] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0221] The present invention relates to a system that allows a user to input basic housing requirements, quickly and accurately generates house blueprints based on those requirements, and automates the entire process from manufacturing parts in a factory to assembling them on-site. However, in conventional systems, the generation of blueprints that reflect the user's requirements and the quality control of manufactured parts are often performed manually, resulting in efficiency issues. Furthermore, insufficient quality control can lead to problems after construction, resulting in additional costs and time.

[0222] 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.

[0223] In this invention, the server includes: an input means for a user to input basic housing requirements; a transmission means for transmitting the user's requirement data to the server; a generation means for receiving the requirement data and generating a housing blueprint that complies with the Building Standards Act using a generation AI; a transmission means for transmitting the generated housing blueprint to the user's terminal; a regeneration means for receiving correction data from the user and readjusting the blueprint using the generation AI; a generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a manufacturing facility; a manufacturing means for manufacturing housing components using a 3D printer based on the generated materials list at the manufacturing facility; an AI-controlled quality control means for quality control of the manufactured components; and an assembly means for transporting the manufactured components to a site and assembling the housing by a construction team. This enables the system to quickly and accurately generate blueprints that reflect the user's requirements, accurately manage the quality of the manufactured components, and realize efficient, high-quality housing construction.

[0224] A "user" is an individual or group that inputs basic housing requirements and uses the system to participate in the process from creating blueprints to construction.

[0225] "Input means" refers to an interface device that allows users to input basic housing requirements, and refers to a terminal such as a computer or smartphone.

[0226] The "transmission means" is a communication means for transmitting the request data entered by the user to the server, and is a technology for connecting to the Internet and performing data communication.

[0227] "Request data" refers to specific desired information such as the layout of the house, budget, materials to be used, etc., entered by the user.

[0228] "Generative AI" is an artificial intelligence model that automatically generates residential blueprints based on user request data, and is a technology for outputting blueprints that comply with the Building Standards Act.

[0229] "Generation means" refers to the process and function for receiving the requested data and generating a house blueprint using generation AI.

[0230] "Regeneration means" refers to the process and functionality for receiving correction data from the user and re-adjusting the design using the generation AI.

[0231] The "server" is a computer system that receives requested data, launches the generation AI, generates and transmits blueprints, and generates a construction plan and material list based on the final blueprints.

[0232] A "construction plan" is a detailed plan that describes the order, schedule, and specific steps required to build a house.

[0233] A "materials list" is a list that lists the types and quantities of materials required to build a house.

[0234] "Manufacturing facility" refers to a factory or manufacturing base where housing components are produced using 3D printers based on construction plans and material lists.

[0235] A "3D printer" is a device that produces three-dimensional parts based on blueprint data, and is a production device used in manufacturing facilities.

[0236] "Means of production" refers to the technology and process used to produce housing components using a 3D printer.

[0237] "Quality control measures" are artificial intelligence-controlled technologies that automatically check the quality of manufactured parts and correct or remanufacture them as necessary.

[0238] "Means of assembly" refers to the processes and techniques used to transport the fabricated components to the site and assemble the home by the construction team.

[0239] 1. Inputting user requirements and generating design drawings

[0240] User inputs request

[0241] The user turns on a device (e.g., a PC or smartphone) and inputs their basic housing requirements. Specifically, they input the house's layout, budget, materials to be used, etc. into a dedicated interface. This interface is designed using prompts from the generative AI model, allowing the user to input information intuitively.

[0242] Server receives requested data

[0243] The device sends the user's requested data to the server. The server analyzes the received data and activates a generative AI model to generate a home design plan that complies with the Building Standards Act. The generative AI model uses pre-trained data to create a design plan that best suits the user's needs.

[0244] 2. Check and fine-tune the design

[0245] The server sends the blueprint

[0246] The generated design drawing is sent from the server to the user's device, where the user can view the drawing on the device screen and check the detailed layout, such as the layout of the living room and the location of windows.

[0247] User enters corrections

[0248] The user can check the blueprint and, if necessary, send any modifications they wish to make to the server from their device. For example, they can input specific modifications such as "move the window a little further to the left" or "add a balcony." This allows the user to obtain the final blueprint they desire.

[0249] Server Regeneration

[0250] The server restarts the generation AI based on the correction information received from the user and regenerates the blueprint, thus completing the final blueprint that meets the user's wishes.

[0251] 3. Generate construction plans and material lists

[0252] The server generates the construction plan and material list

[0253] The server creates a construction plan based on the final design drawings and generates a list of required materials. The construction plan includes the order of work and deadlines, while the material list lists the specific types and quantities of materials.

[0254] 4. Factory production and quality control

[0255] Parts production at manufacturing facilities

[0256] Based on the construction plan and materials list sent from the server, the manufacturing facility uses 3D printers to produce the house components. The produced components are automatically checked by quality control measures controlled by artificial intelligence. Any parts that fail are remanufactured.

[0257] 5. On-site assembly

[0258] Parts transportation and on-site assembly

[0259] Once quality control is complete, the parts are transported to the site, where the construction team quickly assembles them according to the construction plan provided by the server to complete the home.

[0260] Examples and prompts

[0261] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[0262] 1. Inputting requirements: A newlywed couple inputs their requirements for a 1LDK apartment with a budget of 20 million yen and a steel-reinforced concrete structure into the terminal.

[0263] 2. Blueprint generation: The server receives the requested data and creates the optimal blueprint using the generation AI.

[0264] 3. Entering modifications: The user checks the blueprint and enters modifications such as "changing the window position" or "making the living room larger."

[0265] 4. Regenerate: The server generates a new blueprint that reflects the modifications.

[0266] Example prompt sentence:

[0267] "Control the 3D printer based on this blueprint and create the required parts."

[0268] "The basic requirements are 'a 2LDK with a spacious living room, a budget of 30 million yen, and a wooden building.' Please generate the optimal design based on this and go through the process of manufacturing the parts."

[0269] In this way, the present invention makes it possible to realize a house design that quickly and accurately reflects the user's requests, and to efficiently build a high-quality house.

[0270] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0271] Step 1:

[0272] The user inputs basic housing requirements.

[0273] Specifically, users use a device such as a computer or smartphone to input information such as the house's layout, budget, and materials used into a dedicated interface. This interface is designed based on prompts from the generative AI model, allowing for intuitive input.

[0274] Input: Basic housing requirements (floor plan, budget, materials used, etc.)

[0275] Output: Request data

[0276] Step 2:

[0277] The terminal transmits the requested data to the server.

[0278] The input request data is transmitted from the terminal to the server, which then receives the user's request.

[0279] Input: Request data

[0280] Output: Sends the requested data to the server

[0281] Step 3:

[0282] The server receives the requested data and generates a house blueprint using generation AI.

[0283] The server analyzes the received request data and activates a generative AI model to generate blueprints that comply with the Building Standards Act. The generative AI model uses pre-trained data to create optimal blueprints.

[0284] Input: Request data

[0285] Output: Generated house plan

[0286] Step 4:

[0287] The server sends the generated design drawings to the user's device.

[0288] The generated blueprints are sent from the server to the user's device, where the user can view them on the device screen.

[0289] Input: Generated house plan

[0290] Output: Sending the blueprint to the user's device

[0291] Step 5:

[0292] The user checks the design drawings and inputs requests for corrections as necessary.

[0293] The user checks the blueprint and enters any requested modifications, such as "changing the position of a window" or "adding a balcony," into a dedicated interface.

[0294] Input: Initial blueprint

[0295] Output: Corrected data

[0296] Step 6:

[0297] The server receives the modified data from the user and regenerates the blueprint using the generation AI.

[0298] The server restarts the generative AI model based on the correction data received from the user and regenerates the blueprint, resulting in a final blueprint that meets the user's wishes.

[0299] Input: Correction data

[0300] Output: Regenerated blueprint

[0301] Step 7:

[0302] The server generates a construction plan and materials list based on the final design drawings and sends them to the manufacturing facility.

[0303] The server then creates a construction plan based on the final design drawings, generating a materials list, which includes the order of steps and deadlines, and the materials list includes the specific types and quantities of materials required. This data is then sent to the manufacturing facility.

[0304] Input: Regenerated blueprint

[0305] Output: Creation and transmission of construction plans and material lists

[0306] Step 8:

[0307] A manufacturing facility will use 3D printers to create the components for the home.

[0308] The manufacturing facility uses 3D printers to create the components of the home based on the construction plans and materials list submitted.

[0309] Input: Construction plan and materials list

[0310] Output: Produced parts

[0311] Step 9:

[0312] Control the quality of manufactured parts.

[0313] The manufacturing facility's artificial intelligence-controlled quality control measures are used to automatically check the quality of the parts produced, and any parts that fail are remanufactured.

[0314] Input: Produced parts

[0315] Output: Quality controlled parts

[0316] Step 10:

[0317] The manufactured parts are transported to the site, and the construction team assembles the house.

[0318] Once quality control is complete, the parts are transported to the site, where the construction team quickly assembles the house according to the construction plan provided by the server, resulting in a high-quality home.

[0319] Input: Quality-controlled parts, construction plans

[0320] Output: Completed house

[0321] 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.

[0322] The present invention combines an emotion engine with a system in which a user inputs basic housing requirements, uses AI to generate blueprints, and then quickly carries out construction. A specific embodiment of this system is described below.

[0323] 1. Inputting user requirements and generating design drawings

[0324] User inputs request

[0325] Users use the device to input their basic housing requirements, including the layout, budget, materials to be used, etc. The system also has a built-in emotion engine that recognizes the user's emotions in real time.

[0326] Receipt and analysis of requested data by the server

[0327] The request data sent from the device is sent to the server. The server analyzes the received request data and uses an emotion engine to determine the user's emotional state. Based on this information, the generation AI generates a blueprint, but the design content is adjusted according to the user's emotional response.

[0328] 2. Check and correct the design drawings

[0329] The server sends the blueprint

[0330] The generated blueprint is sent from the server to the user's device. When the user checks the blueprint on their device, the emotion engine monitors the user's reaction. For example, the user's emotional state (joy, anxiety, etc.) is analyzed in real time.

[0331] User enters corrections

[0332] When the user checks the blueprint and inputs corrections, the emotion engine is also running, and suggestions based on the user's emotional state (e.g., automatic corrections for stressful parts) can be made. The corrections are then sent to the server.

[0333] Server Regeneration

[0334] The server restarts the generation AI based on the correction data and information from the emotion engine, and regenerates the blueprint, resulting in a blueprint that optimally reflects the user's wishes and emotional state.

[0335] 3. Generate construction plans and material lists

[0336] The server creates a construction plan

[0337] The server then uses the final design and data from the emotion engine to create a detailed construction plan, including the order of steps, deadlines, and considerations related to the user's emotional state.

[0338] The server generates the material list

[0339] The server may generate a list of materials required for construction and select materials according to the user's preferences based on data from the emotion engine.

[0340] Sending to partner factories

[0341] The generated construction plan and materials list are sent from the server to a partner factory, where production can proceed taking into account the emotion engine data.

[0342] 4. 3D printed parts production and assembly

[0343] In-factory production

[0344] The partner factory uses 3D printers to produce each part of the house based on a materials list. The parts are inspected under strict quality control, and the emotion engine data is also used as a reference for production.

[0345] Parts transportation and on-site assembly

[0346] The manufactured parts are transported to the construction site. The construction team quickly assembles the parts to complete the house according to a construction plan that includes feedback from the emotion engine. For example, based on user emotion data, the system can incorporate ideas to minimize stress on-site.

[0347] Specific examples

[0348] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[0349] 1. User inputs request

[0350] A newlywed couple inputs their requirements for a one-bedroom apartment with a budget of 20 million yen and a steel-reinforced concrete structure into a terminal. The emotion engine recognizes their emotions as they type.

[0351] 2. The server creates the blueprint

[0352] The server receives the request data and emotion data, and uses generative AI to create the optimal design.

[0353] 3. User makes corrections

[0354] Check the blueprint and input modifications such as "change the window position" or "make the living room larger." The emotion engine simultaneously monitors the response.

[0355] 4. The server regenerates

[0356] Generate a new blueprint that reflects the modifications and confirm it.

[0357] 5. Generate construction plans and material lists

[0358] Based on the finalized drawings and emotion data, a construction plan and materials list are generated and sent to the factory.

[0359] 6. Manufacturing parts in factories

[0360] Parts are manufactured using 3D printers, and quality and emotional data are managed.

[0361] 7. On-site assembly

[0362] The parts are transported to the site, and the construction team quickly assembles them while taking into account the emotional data to complete the home.

[0363] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to provide a home that is more user-friendly and provides a higher level of satisfaction.

[0364] The processing flow will be explained below.

[0365] Specific processing steps of the program

[0366] Step 1: User input

[0367] 1.1 User starts terminal

[0368] The user turns on a device such as a smartphone or PC and opens a dedicated application or web browser.

[0369] 1.2 User fills out request form

[0370] Users enter basic information about their housing needs (e.g., floor plan, budget, materials to be used, etc.) into an input form, and emotion-recognition cameras and sensors detect their reactions.

[0371] 1.3 Emotion engine analyzes user emotions

[0372] The emotion engine analyzes the user's input emotional data (happiness, anxiety, excitement, etc.) in real time, allowing for a more detailed understanding of the user's wishes.

[0373] Step 2: Receiving and analyzing the requested data on the server

[0374] 2.1 The device sends the request data and emotion data to the server

[0375] The terminal transmits the request data input by the user and the emotion data analyzed by the emotion engine to the server.

[0376] 2.2 The server receives the request data and emotion data

[0377] The server receives the transmitted desire data and emotion data and begins analysis.

[0378] Step 3: Generate blueprints on the server

[0379] 3.1 The server starts the generated AI

[0380] The server activates a generation AI based on the analyzed request data and emotion data to generate a blueprint.

[0381] 3.2 Server generates blueprint

[0382] The generative AI generates home blueprints that are in compliance with building standards laws and best suit the user's needs and emotions.

[0383] Step 4: Check and modify the blueprint

[0384] 4.1 The server sends the blueprint to the device

[0385] The server sends the generated design drawings to the user's terminal.

[0386] 4.2 User checks the design drawing

[0387] The user checks the blueprint on the device, and the emotion engine monitors the user's reactions using the device's camera and microphone to collect emotional data.

[0388] 4.3 User enters corrections

[0389] When a user inputs modifications to the blueprint (e.g., changing the position of a window, adding a room, etc.) into the device, the emotion engine works and makes automatic suggestions based on the user's emotional state. The modifications are then sent to the server.

[0390] Step 5: Regenerate the blueprint on the server

[0391] 5.1 The server receives the correction data and emotion data

[0392] The server receives the correction data sent by the user and the emotion data analyzed by the emotion engine.

[0393] 5.2 Server restarts generated AI

[0394] The server restarts the generation AI and regenerates the blueprint based on the correction data and emotion data.

[0395] 5.3 The server confirms the final design

[0396] The server checks whether the new design meets the user's needs and feelings, and then finalizes the design.

[0397] Step 6: Generate construction plan and materials list

[0398] 6.1 Server creates construction plan

[0399] The server then uses the final design and data from the emotion engine to create a detailed construction plan, including process sequences, deadlines, and considerations related to the user's emotional state.

[0400] 6.2 Server generates ingredients list

[0401] The server generates a list of materials required for construction and selects materials according to the user's preferences based on data from the emotion engine.

[0402] 6.3 Server sends data to factory

[0403] The server sends the construction plan and materials list to the partner factory, which can then proceed with production while taking into account the emotion engine data.

[0404] Step 7: Factory parts production

[0405] 7.1 Factory receives data

[0406] The subcontract factory receives the construction plan and material list sent from the server.

[0407] 7.2 Factories prepare for 3D printers

[0408] The factory sets up the 3D printer and begins producing parts based on the materials list.

[0409] 7.3 3D printers produce parts

[0410] A 3D printer creates the house components according to the design, incorporating data from the emotion engine.

[0411] Step 8: Transport and assemble the parts

[0412] 8.1 Factory packs and transports parts

[0413] The factory packs the completed parts and transports them to the construction site.

[0414] 8.2 Installation team receives parts

[0415] The construction team receives the parts on-site and performs the necessary checks. Data from the emotion engine is also reflected in the construction plan.

[0416] 8.3 The construction team assembles the house

[0417] The construction team follows the construction plan provided by the server and quickly assembles the parts to complete the house. Based on feedback from the emotion engine, the construction is carried out with consideration for the user's emotions.

[0418] The above is a specific embodiment of the present invention that combines an emotion engine. This system takes into consideration the emotions of the user and provides a home that offers a higher level of satisfaction.

[0419] Example 2

[0420] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0421] With conventional home design systems, it was difficult to adjust the design content while taking the user's emotions into consideration, and as a result, it was not possible to maximize user satisfaction. Furthermore, there was no system in the design process that could make quick corrections based on the user's reactions. As a result, it was not possible to reduce the anxiety and stress felt by the user, and the efficiency of the entire design and construction process was reduced.

[0422] 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.

[0423] In this invention, the server includes: an input means for inputting the user's basic housing requirements; a transmission means for transmitting the user's requirement data and emotion data to the server; a generation means for receiving the requirement data and emotion data and generating a housing blueprint based on the user's emotional state using a generation AI; a transmission means for transmitting the generated housing blueprint and emotion data to the user's terminal and monitoring the user's reaction; a regeneration means for receiving correction data and emotion data from the user and readjusting the blueprint using the generation AI; a plan generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a factory; a production means for fabricating housing components using a 3D printer based on the generated materials list at the factory; and an assembly means for transporting the fabricated components to a site and having a construction team assemble the house based on the emotion data. This allows the system to reflect the user's emotions in real time, enabling the design and construction of homes that provide greater satisfaction.

[0424] 1. "Input means" refers to devices or software that provide an interface for users to input their basic housing requirements.

[0425] 2. "Transmission means" refers to a device or software with a communication function for transmitting user request data and emotion data to the server.

[0426] 3. "Generation means" refers to a system that uses generation AI to generate a house blueprint based on the received request data and emotional data, in accordance with the user's emotional state.

[0427] 4. The "regeneration means" is a system that receives correction data and emotional data from the user and readjusts the blueprint using a generation AI.

[0428] 5. "Plan generation means" is a system that generates a construction plan and material list based on the final design drawings and sends them to the factory.

[0429] 6. "Means of production" refers to the equipment or system that produces the housing components using a 3D printer based on a materials list generated in the factory.

[0430] 7. "Assembly means" refers to a system in which manufactured parts are transported to the site and the construction team assembles the house based on the emotional data.

[0431] 8. "Emotional data" refers to data used to read a user's emotional state in real time, and is information obtained from the user's facial expressions and voice.

[0432] 9. "Generative AI" is a system that uses artificial intelligence technology to analyze request data and emotional data and generate housing blueprints and construction plans.

[0433] 10. "Communication functions" refers to the technology that includes the network infrastructure and protocols for transmitting and receiving data.

[0434] These are the definitions of the important terms included in this system, which will clarify the technical scope and meaning of each term.

[0435] The present invention is a system that allows users to input basic housing requirements and emotional data, generates blueprints using a generative AI model, and then quickly and efficiently carries out construction based on these blueprints. Detailed embodiments of this system are described below.

[0436] User enters request information

[0437] Users use a device (e.g., smartphone, tablet, or PC) to input their basic housing requirements, including the floor plan, budget, and materials to be used. The device also has a built-in emotion engine (e.g., Affectiva or FaceReader) that reads the user's emotions in real time during the input process.

[0438] Examples:

[0439] The user inputs "1LDK, budget 20 million yen, steel-framed concrete construction" into the device's dedicated interface. At the same time, the emotion engine analyzes the user's facial expressions and voice and generates emotion parameters.

[0440] Sending request data and emotion data

[0441] The terminal packages the input desire data and emotion data and transmits the data to a server via the Internet, for example in text or digital format.

[0442] Receiving and analyzing data

[0443] The server receives the request data and emotion data sent from the device. The received data is analyzed on the server. The server analyzes the request data to understand the basic specifications of the home the user desires. At the same time, it analyzes the emotion data to understand the user's emotional state.

[0444] Examples:

[0445] The server receives and analyzes the request data, such as "1LDK, budget 20 million yen, steel-reinforced concrete construction," and emotional data, such as "joy (80%)" and "anxiety (20%)."

[0446] Blueprint generation

[0447] Based on the analysis results, the server generates a house blueprint using a generative AI model (e.g., OpenAI GPT-4). The generated blueprint is flexibly adjusted according to the user's emotional state.

[0448] Examples:

[0449] A "1LDK blueprint" is generated, and a spacious, relaxing living room is suggested based on the user's emotional data.

[0450] Sending blueprints and emotion data

[0451] The server sends the generated blueprint and emotion data to the user's device. As the user checks the blueprint, the emotion engine continues to monitor the user's reaction.

[0452] Examples:

[0453] The server sends the "proposed 1LDK blueprint" to the terminal, allowing the user to view it in real time.

[0454] Enter and submit correction data

[0455] When a user inputs corrections to the blueprint into the device, the emotion engine monitors the user's reaction in real time and generates emotion data. The input correction data and emotion data are then sent back to the server.

[0456] Examples:

[0457] The user inputs modifications such as "change the window position" or "make the living room bigger," and the emotion engine records emotional data such as "excitement (70%)" and "concern (30%)."

[0458] Regenerating blueprints

[0459] The server restarts the generative AI model based on the correction data and emotion data, and generates a new blueprint, which optimally reflects the user's desires and emotional state.

[0460] Generate construction plans and material lists

[0461] The server generates a detailed construction plan and materials list based on the final design and emotion data. The construction plan includes process sequence, deadlines, and emotion-related considerations. The generated data is sent to a partner factory.

[0462] Examples:

[0463] The server generates a "construction plan including the start date and time of construction, the order, and noise control measures" and a "list of materials with excellent durability and design" and sends them to the factory.

[0464] Parts production using a 3D printer

[0465] The factory will use 3D printers (e.g., Stratasys, Formlabs) to produce the house components based on a materials list, and the emotional data will also be taken into account during the production process.

[0466] Examples:

[0467] The factory will produce "housing components" and will also consider "designs that reflect emotional data."

[0468] Parts transportation and assembly

[0469] The construction team transports the manufactured parts to the site and assembles them according to the construction plan. Based on the emotional data, they make efforts to minimize user stress.

[0470] Examples:

[0471] The construction team "assembles the parts in a stress-free way for the user" to complete the home.

[0472] Prompt Sentence Examples

[0473] Here is an example where a newlywed couple wants a one-bedroom, one-room apartment.

[0474] 1. User enters request:

[0475] The newlyweds entered their requirements into the terminal: "1LDK, budget 20 million yen, steel-reinforced concrete construction."

[0476] 2. The server creates the blueprint:

[0477] The server receives the request data and emotion data, and creates the optimal design using a generative AI model.

[0478] 3. User makes corrections:

[0479] Check the blueprint and enter any modifications you would like to make, such as "changing the window position" or "making the living room larger."

[0480] 4. Server regenerates:

[0481] Regenerate a new blueprint reflecting the modifications and confirm.

[0482] 5. Generate construction plans and material lists:

[0483] Based on the finalized drawings and emotion data, a construction plan and materials list are generated and sent to the factory to begin production.

[0484] 6. Factory parts manufacturing:

[0485] 3D printers are used to create housing components and manage emotional data.

[0486] 7. On-site assembly:

[0487] The manufactured parts are transported to the site, and the construction team quickly assembles them while taking into account the emotional data.

[0488] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to provide a home that is user-friendly and highly satisfying.

[0489] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0490] Step 1:

[0491] The user inputs basic housing requirements

[0492] Users use a device (e.g., smartphone, tablet, or PC) to input their basic housing requirements, including the floor plan, budget, and materials to be used. An emotion engine (e.g., Affectiva, FaceReader) analyzes the user's facial expressions and tone of voice in real time to generate emotion parameters.

[0493] Input: Request information such as "1LDK, budget 20 million yen, steel-framed concrete construction," as well as the user's facial expression and voice

[0494] Output: Desire data and emotion data (e.g., "Happy (80%), Anxiety (20%)")

[0495] Specific operation: When a user enters their request into a form on the device, the emotion engine simultaneously analyzes the user's emotions.

[0496] Step 2:

[0497] The device sends the request data and emotion data to the server.

[0498] The terminal packages the request information entered by the user and the generated emotion data, and transmits the packaged data to a server via the Internet.

[0499] Input: User-entered desire and emotion data

[0500] Output: Data sent to the server

[0501] Specific operation: The device sends the request data "1LDK, budget 20 million yen, steel-reinforced concrete construction" and the emotion data "joy (80%), anxiety (20%)" to the server.

[0502] Step 3:

[0503] The server receives and analyzes the request data and emotion data.

[0504] The server receives and analyzes the request data and emotion data sent from the terminal. It analyzes the request data to understand the user's desired specifications, and analyzes the emotion data to grasp the user's emotional state.

[0505] Input: Desire data and emotion data sent from the device

[0506] Output: Analysis of the desires and emotional state

[0507] Specific operation: The server analyzes the request data for "1LDK, budget 20 million yen, steel-reinforced concrete construction," identifies the necessary specifications, and understands the user's emotional state from the emotional data.

[0508] Step 4:

[0509] The server generates the blueprint

[0510] The server uses a generative AI model (e.g., OpenAI GPT-4) based on the analysis results to generate a house blueprint, which is flexibly adjusted according to the user's emotional state.

[0511] Input: Analysis results of desires and emotional state

[0512] Output: Emotionally adjusted house blueprints

[0513] Specific operation: The server generates a "1LDK blueprint" and includes suggestions such as a spacious, relaxing living room, taking into account the user's emotional data.

[0514] Step 5:

[0515] The server sends the generated blueprint and emotion data to the user's device.

[0516] The server sends the generated blueprint and emotion data to the user's device. While the user is checking the blueprint, the emotion engine monitors the user's reaction.

[0517] Input: Generated blueprints and emotion data

[0518] Output: Blueprints sent to the user's device and monitoring data of user reactions

[0519] Specific operation: The server sends the "proposed 1LDK blueprint" to the terminal, and the emotion engine analyzes the user's real-time reaction.

[0520] Step 6:

[0521] The user checks the design and inputs corrections

[0522] The user checks the design on the device and inputs any necessary corrections. The emotion engine analyzes the user's reaction in real time and generates emotion data.

[0523] Input: Generated design, user's correction instructions, and user's emotional response

[0524] Output: Corrected data and new emotion data

[0525] Specific operation: The user inputs modifications such as "change the window position" or "make the living room bigger," and the emotion engine generates new emotion data such as "anxiety (40%)."

[0526] Step 7:

[0527] The device sends correction data and emotion data.

[0528] The terminal transmits the modified data from the user and the newly generated emotion data to the server.

[0529] Input: User correction data and emotion data

[0530] Output: Correction data and emotion data sent to the server

[0531] Specific operation: The device sends the correction data for "changing the window position" and "making the living room larger" and the emotion data for "anxiety (40%)" to the server.

[0532] Step 8:

[0533] The server launches the regenerative AI model

[0534] The server restarts the generative AI model based on the corrected data and new emotion data, and generates a new blueprint.

[0535] Input: Corrected data and new emotion data

[0536] Output: New modified blueprint

[0537] Specific operation: The server generates a new design plan that includes window placement that allows in more natural light to reduce the user's anxiety, and sends it to the device again.

[0538] Step 9:

[0539] The server generates the construction plan and material list

[0540] The server generates a construction plan and materials list based on the final design drawings and emotion data and sends them to the partner factory.

[0541] Input: Final blueprint and emotion data

[0542] Output: Detailed construction plan and materials list

[0543] Specific operation: The server generates a "construction plan including the start date and time of construction, the order, and noise control measures" and a "list of materials with excellent durability and design" and sends them to the factory.

[0544] Step 10:

[0545] Parts are manufactured by partner factories

[0546] The partner factory will use a 3D printer (e.g., Stratasys, Formlabs) to produce the housing components based on the materials list.

[0547] Input: Materials list

[0548] Output: Produced housing components

[0549] Specific operation: Factories will produce "housing components" using 3D printers, and will also take into consideration "designs that reflect emotional data."

[0550] Step 11:

[0551] Parts transportation and on-site assembly

[0552] The construction team transports the manufactured parts to the site and assembles them according to the construction plan. Based on the emotional data, they make efforts to minimize user stress.

[0553] Input: Manufactured parts and construction plans

[0554] Output: Completed house

[0555] What it does: The construction team "assembles the parts in a stress-free way, based on the user's emotional data," completing the home.

[0556] (Application example 2)

[0557] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0558] Current home design systems have difficulty considering users' requests and emotions, resulting in low user satisfaction. Furthermore, in the case of in-store shopping experiences, there is no system that can analyze customers' real-time emotions and provide appropriate product suggestions and guidance, making it difficult to improve customer satisfaction.

[0559] 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.

[0560] In this invention, the server includes an input means for a user to input basic housing requirements, a transmission means for transmitting the user's requirement data to the server, a generation means for receiving the requirement data and generating a housing blueprint that complies with the Building Standards Act using a generation AI, a transmission means for transmitting the generated housing blueprint to the user's terminal, a regeneration means for receiving correction data from the user and readjusting the blueprint using the generation AI, a generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a factory, a fabrication means for fabricating housing components using a 3D printer based on the generated materials list at the factory, an assembly means for transporting the fabricated components to a site and having a construction team assemble the housing, an emotion recognition means for recognizing and analyzing the user's emotions in real time, and a presentation means for suggesting and providing optimal products based on the emotion data. This enables high-satisfaction housing designs that take user emotions into consideration and an improved shopping experience in physical stores.

[0561] "User" means an individual or organization wishing to design a home or shop in a physical store.

[0562] "Basic requirements" are the initial conditions and requirements such as the layout of the house, budget, materials to be used, etc.

[0563] "Input means" refers to devices or software that allow users to input their basic housing requirements.

[0564] "Transmission means" refers to the communication means and device for transmitting the user's requested data to the server.

[0565] "Server" means a computer system that receives, analyzes, and processes user-requested data.

[0566] "Generative AI" is artificial intelligence for generating house blueprints.

[0567] "Generation means" refers to the process or device that uses generative AI to generate residential blueprints that comply with the Building Standards Act.

[0568] "Terminal" refers to a computer terminal or smart device operated by a user.

[0569] "Regeneration means" refers to the process or device that receives correction data from the user and readjusts the design using the generation AI.

[0570] - "Construction plan" is a construction plan based on the final design drawings.

[0571] - "Materials List" is a list of materials required for construction.

[0572] "Means of production" refers to the process or equipment used to 3D print the housing components based on a materials list generated in the factory.

[0573] · "Means of assembly" refers to the process or equipment by which the fabricated components are transported to the site and assembled into the home by the construction team.

[0574] "Emotion recognition means" refers to technology or systems that recognize and analyze users' emotions in real time.

[0575] "Presentation means" refers to a method or device for optimally proposing and providing product information based on emotional data.

[0576] The present invention combines an emotion engine with a system in which a user inputs basic housing requirements, uses AI to generate blueprints, and then quickly constructs the house. Specific embodiments of this system are described below.

[0577] 1. Inputting user requirements and generating design drawings

[0578] First, the user inputs their basic housing requirements using a terminal. The terminal is a device such as a smartphone or tablet, and is equipped with a dedicated interface. Input information includes the floor plan, budget, materials to be used, etc. The system also has a built-in emotion engine that recognizes the user's emotions in real time.

[0579] The user's request data is sent to the server using the transmission means. The server analyzes the received request data and uses an emotion engine to determine the user's emotional state. Based on this information, the generation AI generates a house blueprint. The generated blueprint is then sent from the server to the user's device, where the user can review it.

[0580] 2. Check and correct the design drawings

[0581] As the user reviews the blueprint, the smart glasses analyze the user's emotions and provide real-time feedback. For example, if the user feels joy or anxiety, the glasses will automatically suggest adjustments to the design based on that emotion data. The user inputs the corrections, which are then sent back to the server, where the AI ​​regenerates the design.

[0582] 3. Generate construction plans and material lists

[0583] Once the final design drawings are finalized, the server generates a construction plan and materials list, which are tailored to the user's preferences based on data from the emotion engine. The resulting construction plan and materials list are then sent to the partner factory.

[0584] 4. 3D printed parts production and assembly

[0585] In the factory, each component of the house is produced using a 3D printer based on a materials list. The produced components are then transported to the site, where the construction team quickly assembles them according to a construction plan that includes feedback from the emotion engine. This allows the delivery of homes that take user emotions into consideration and provide a high level of satisfaction.

[0586] 5. Physical store applications

[0587] The emotion engine and generative AI of this invention can also be applied to improving the shopping experience in brick-and-mortar stores. As customers wearing smart glasses walk through a store, their emotions are analyzed in real time via the smart glasses' camera and microphone. Based on the analysis results, the generative AI displays optimal product suggestions, in-store navigation, and custom messages on the smart glasses.

[0588] Prompt Sentence Examples

[0589] For example, if the emotion engine recognizes the user's "joy," it will input the following into the generative AI model:

[0590] Users are "delighted" - suggest the most popular products and those currently on sale.

[0591] The hardware used includes smart glasses, tablets, smartphones, NVIDIA Jetson, and Raspberry Pi, while the software used includes TensorFlow / Keras (for emotion recognition models), OpenCV (image processing), Flask, and FastAPI (for product suggestion APIs).

[0592] The above is a specific embodiment of the present invention, which realizes highly satisfying home design that takes into account the user's emotions and improves the shopping experience in physical stores.

[0593] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0594] Step 1:

[0595] The user uses a terminal to input basic housing requirements.

[0596] Input: Required data such as house layout, budget, materials to be used, etc.

[0597] Output: A data packet that sends the requested data to the server.

[0598] How it works: The user enters various information into a form on the device's dedicated interface and presses the send button. The emotion engine analyzes the user's emotions in real time and sends them along with the data packet.

[0599] Step 2:

[0600] The server receives the requested data and performs the analysis.

[0601] Input: Desire data and emotion data sent by the user.

[0602] Output: Parsed data to feed into the generative AI.

[0603] Specific operation: The server saves the request data in a database and uses the emotion engine to analyze the user's emotional state. Based on the analysis results, the data is converted into a format that can be input into the generation AI.

[0604] Step 3:

[0605] Generate house blueprints using generative AI.

[0606] Input: Parsed desire data and emotion data.

[0607] Output: The generated house plan.

[0608] Specific operation: The generation AI reads the request data and emotional data as prompts and generates appropriate house blueprints. The prompt uses the following sentence: "The user wants a 1LDK, budget of 20 million yen, and steel-reinforced concrete structure. The emotional state is inclined towards happiness."

[0609] Step 4:

[0610] The server sends the generated house design plan to the user's terminal.

[0611] Input: Generated house blueprint data.

[0612] Output: The blueprint displayed on the user's device.

[0613] Specific operation: The generated design drawing data is sent to the user's device and displayed using a dedicated application on the device.

[0614] Step 5:

[0615] The user checks the design drawings and inputs correction data.

[0616] Input: Correction data entered by the user after viewing the design drawings.

[0617] Output: A data packet that sends the modified data to the server.

[0618] How it works: The user checks the blueprint on the device and inputs the desired corrections. The emotion engine analyzes the user's emotional state and sends it along with the data packet.

[0619] Step 6:

[0620] The server receives the correction data and regenerates it using the generation AI.

[0621] Input: Correction data and emotion data.

[0622] Output: A regenerated house blueprint.

[0623] Specific operation: The server requests the AI ​​to regenerate the user's character based on the correction data and emotion data. The AI ​​then updates the prompt as follows: "The user wants to change the window position and make the living room larger. The user's emotional state is anxious."

[0624] Step 7:

[0625] The server generates a construction plan and material list based on the final design drawings and sends them to the factory.

[0626] Input: Final blueprint and emotion data.

[0627] Output: Construction plan and materials list.

[0628] Specific operation: Based on the generated final design drawings and emotion data, the server creates the order of construction processes, deadlines, and a list of materials to be used, and sends this to the factory.

[0629] Step 8:

[0630] The factory uses 3D printers to produce housing components.

[0631] Input: Construction plan and materials list.

[0632] Output: Produced housing components.

[0633] What it does: The factory uses a 3D printer to produce housing components based on the materials list it receives.

[0634] Step 9:

[0635] The manufactured parts are transported to the site, and the construction team assembles the house.

[0636] Input: Manufactured housing components and construction plans.

[0637] Output: A completed house.

[0638] Specific operation: The robot receives the transported parts at the construction site and begins assembling them according to the construction plan. The robot proceeds with the construction while taking into account feedback from the emotion engine.

[0639] Step 10:

[0640] In brick-and-mortar stores, smart glasses can analyze customer emotions in real time and make product suggestions.

[0641] Input: Video and audio data from smart glasses.

[0642] Output: Customer sentiment data and optimal product recommendations.

[0643] How it works: The smart glasses' camera and microphone capture the customer's facial expressions and voice, which are then analyzed by the emotion engine. Based on the analysis results, the generative AI creates a prompt and suggests the most suitable product. For example, "The user is feeling happy. Please suggest the most popular products that are currently on sale."

[0644] 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.

[0645] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0646] 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.

[0647] [Second embodiment]

[0648] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0649] 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.

[0650] 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).

[0651] 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.

[0652] 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.

[0653] 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).

[0654] 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.

[0655] 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.

[0656] 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.

[0657] 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.

[0658] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0659] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0660] The present invention relates to a system in which a user inputs basic requirements for a house, a server generates blueprints based on the requirements using AI, and the server then promptly carries out construction. A specific embodiment of this system will be described below.

[0661] 1. Inputting user requirements and generating design drawings

[0662] User inputs request

[0663] The user starts up a terminal (such as a PC or smartphone) and inputs basic housing requirements, including the floor plan, budget, and types of materials, into an input form interactively.

[0664] Server receives requested data

[0665] The device sends the desired data entered by the user to the server. The server analyzes the received data and activates the generation AI to generate blueprints that comply with the Building Standards Act. The generation AI uses pre-trained data to create blueprints that best meet the user's needs.

[0666] 2. Check and fine-tune the design

[0667] The server sends the blueprint

[0668] The generated blueprint is sent from the server to the user's device, where the user can view the blueprint on their device screen. For example, detailed layouts such as the layout of the living room and the location of windows are displayed.

[0669] User enters corrections

[0670] The user can check the blueprint and send any necessary corrections to the server from their device. For example, they can make specific changes such as "move the window a little further to the left" or "add a balcony."

[0671] Server Regeneration

[0672] The server restarts the generation AI based on the correction information received from the user and regenerates the blueprint, thus completing the final blueprint that meets the user's wishes.

[0673] 3. Generate construction plans and material lists

[0674] The server generates the construction plan and material list

[0675] The server creates a construction plan based on the final design drawings and generates a list of required materials. The construction plan includes the order of work and deadlines, while the material list lists the specific types and quantities of materials.

[0676] Sending to partner factories

[0677] The generated construction plan and materials list are sent from the server to a partner factory, which prepares a 3D printer and produces the house components based on the information sent.

[0678] 4. 3D printed parts production and assembly

[0679] In-factory production

[0680] The partner factory uses 3D printers to produce each part of the house based on the materials list, and the parts are checked under strict quality control.

[0681] Parts transportation and on-site assembly

[0682] The manufactured parts are transported to the construction site, where the construction team quickly assembles the parts to complete the house according to the construction plan provided by the server, which details, for example, the order in which wall panels should be assembled and the steps for laying the foundation.

[0683] Specific examples

[0684] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[0685] 1. User inputs request

[0686] A newlywed couple enters their requirements for a one-bedroom, one-room kitchen, a budget of 20 million yen, and a steel-reinforced concrete structure into a terminal.

[0687] 2. The server creates the blueprint

[0688] The server receives the requested data and creates the optimal design using a generation AI.

[0689] 3. User makes corrections

[0690] Check the blueprint and enter any modifications you would like to make, such as "change the window position" or "make the living room larger."

[0691] 4. The server regenerates

[0692] Generate a new blueprint that reflects the modifications and confirm it.

[0693] 5. Generate construction plans and material lists

[0694] A construction plan and material list are generated based on the finalized drawings and sent to the factory.

[0695] 6. Manufacturing parts in factories

[0696] Parts are manufactured using 3D printers and quality controlled.

[0697] 7. On-site assembly

[0698] The parts are transported to the site and assembled by the construction team to complete the home.

[0699] The above is an embodiment of the present invention. This system makes it possible to provide high-quality housing at low cost in a short period of time.

[0700] The processing flow will be explained below.

[0701] Specific processing steps of the program

[0702] Step 1: User input

[0703] 1.1 User starts terminal

[0704] The user turns on a device such as a smartphone or PC and opens a dedicated application or web browser.

[0705] 1.2 User fills out request form

[0706] The user enters basic information about the home they are looking for (e.g., layout, budget, materials to be used, etc.) into the input form and presses the submit button.

[0707] Step 2: Receiving and analyzing the requested data on the server

[0708] 2.1 The device sends the requested data to the server

[0709] The terminal transmits the request data input by the user to the server.

[0710] 2.2 The server receives the requested data

[0711] The server receives the transmitted request data and begins analyzing it.

[0712] Step 3: Generate blueprints on the server

[0713] 3.1 The server starts the generated AI

[0714] The server activates a generation AI based on the analyzed request data and generates a blueprint.

[0715] 3.2 Server generates blueprint

[0716] The generation AI generates house blueprints that best meet the user's needs while complying with the Building Standards Act.

[0717] Step 4: Check and modify the blueprint

[0718] 4.1 The server sends the blueprint to the device

[0719] The server sends the generated design drawings to the user's terminal.

[0720] 4.2 User checks the design drawing

[0721] The user checks the blueprint on the terminal and considers whether there are any problems with the contents.

[0722] 4.3 User enters corrections

[0723] The user inputs modifications to the blueprint (e.g., changing the position of a window, adding a room, etc.) into the terminal and sends them to the server.

[0724] Step 5: Regenerate the blueprint on the server

[0725] 5.1 Server receives modified data

[0726] The server receives the correction data sent by the user.

[0727] 5.2 Server restarts generated AI

[0728] The server will restart the generation AI and regenerate the blueprint based on the modified data.

[0729] 5.3 The server confirms the final design

[0730] The server checks whether the new design meets the user's requirements and confirms the final design.

[0731] Step 6: Generate construction plan and materials list

[0732] 6.1 Server creates construction plan

[0733] The server will create a detailed construction plan based on the final design drawings.

[0734] 6.2 Server generates ingredients list

[0735] The server generates a list of materials required for construction.

[0736] 6.3 Server sends data to factory

[0737] The server transmits the construction plan and material list to the subcontract factory.

[0738] Step 7: Factory parts production

[0739] 7.1 Factory receives data

[0740] The subcontract factory receives the construction plan and material list sent from the server.

[0741] 7.2 Factories prepare for 3D printers

[0742] The factory sets up the 3D printer and begins producing parts based on the materials list.

[0743] 7.3 3D printers produce parts

[0744] A 3D printer will create the components of the house according to the specified design.

[0745] Step 8: Transport and assemble the parts

[0746] 8.1 Factory packs and transports parts

[0747] The factory packs the completed parts and transports them to the construction site.

[0748] 8.2 Installation team receives parts

[0749] The construction team receives the parts on site and performs the necessary checks.

[0750] 8.3 The construction team assembles the house

[0751] The construction team quickly assembles the house based on the construction plan provided by the server, resulting in the completion of a high-quality home in a short period of time.

[0752] The above is the specific flow of program processing. This system allows users to obtain low-cost housing efficiently and quickly.

[0753] Example 1

[0754] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0755] The conventional housing design and construction process is time-consuming and costly, and it is difficult to accurately reflect the user's needs. Furthermore, there are many uncertainties in the design changes and material procurement processes, which frequently result in project delays and budget overruns. The purpose of this invention is to solve these problems and enable housing design and construction that quickly and accurately meets the user's needs.

[0756] 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.

[0757] In this invention, the server includes an input means for a user to input basic requirements for a home, a transmission means for transmitting the user's requirement data to the server, a generation means for receiving the requirement data and generating a home blueprint using a generative AI model, a transmission means for transmitting the generated home blueprint to the user's terminal, a regeneration means for receiving correction data from the user and readjusting the blueprint using the generative AI model, a generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a manufacturing facility, a manufacturing means for manufacturing home components using a 3D printer based on the generated materials list at the manufacturing facility, and an assembly means for transporting the manufactured components to a site and having a construction team assemble the home. This makes it possible to quickly and accurately reflect user requirements and provide high-quality homes in a short period of time.

[0758] "Basic housing requirements" refer to the user's desired housing conditions, such as layout, budget, and materials to be used.

[0759] "Input means" refers to a device or software interface that allows a user to input basic housing requirements.

[0760] The "transmission means" refers to a device or software that has the function of transmitting the user's requested data to the server.

[0761] "Server" refers to the machine and software that processes data received from users, generates house blueprints, and draws up construction plans.

[0762] A "generative AI model" is an artificial intelligence program that uses machine learning technology to automatically generate house blueprints from training data.

[0763] "Generation means" refers to devices or software that have the function of using generative AI models to create house blueprints, construction plans, and material lists.

[0764] A "terminal" is a device such as a personal computer or smartphone operated by a user.

[0765] A "regeneration means" is a device or software that has the function of readjusting a design using a generative AI model based on correction data from the user.

[0766] A "construction plan" refers to a plan that shows the series of work processes and schedule required to build a house.

[0767] A "materials list" is a list that lists the types and quantities of materials needed to build a house.

[0768] A "manufacturing facility" is a place where housing components are produced using 3D printers and high-precision machine tools.

[0769] A "production tool" is any equipment or software used to produce parts based on a materials list at a manufacturing facility.

[0770] "Assembly means" refers to the equipment and methods for transporting fabricated components to the site and assembling the home.

[0771] MODE FOR CARRYING OUT THE INVENTION

[0772] The present invention relates to a system in which a user inputs basic requirements for a house, a server generates blueprints based on those requirements using AI, and the server then promptly carries out construction. A specific method for implementing this system is described below.

[0773] Hardware and Software Configuration

[0774] 1. Terminal

[0775] Hardware: PC, smartphone

[0776] Software: Web browser

[0777] 2. Server

[0778] Hardware: High-performance servers (e.g. cloud servers in a data center)

[0779] Software: drafting software (e.g., AutoCAD, Revit), generative AI (e.g., GPT-4)

[0780] 3. Manufacturing Facilities

[0781] Hardware: 3D printers, high-precision machine tools

[0782] Software: Parts production management software (e.g., Siemens NX)

[0783] Specific operation of the system

[0784] 1. User request input

[0785] Users use a device (PC or smartphone) to input their basic housing requirements on a web browser. Specific requirements such as floor plan, budget, and types of materials are entered interactively in the input form.

[0786] 2. Receipt and analysis of requested data by the server

[0787] The device sends the input request data to the server, which then uses a data analysis module to extract elements such as floor plan, budget, and type of materials, and formats them as input data for the generative AI model.

[0788] 3. Server-based blueprint generation

[0789] The server inputs the formatted request data into a generative AI model (e.g., GPT-4). The prompt text used is something like, "Please generate a blueprint for a 1LDK house with a budget of 20 million yen and steel-framed concrete construction." The generative AI generates the blueprint, and the server receives the results.

[0790] 4. Submit your blueprints

[0791] The generated blueprint is sent from the server to the user's device, where the user can view it in a web browser. This blueprint includes detailed information such as the floor plan, interior, and window placement.

[0792] 5. Check and correct the design drawings

[0793] The user checks the blueprint and inputs any modifications they wish to make, such as "move the window a little further to the left" or "add a balcony." The modification data is then sent from the terminal to the server.

[0794] 6. Server Regeneration

[0795] The server re-runs the generative AI model based on the corrections received from the user and regenerates the blueprint. This process can be repeated until a new blueprint is generated.

[0796] 7. Generate construction plans and material lists

[0797] Once the final design drawings are finalized, the server automatically generates a construction plan and materials list based on them. The construction plan includes the order of work and deadlines, while the materials list includes the specific types and quantities of materials.

[0798] 8. Transmission of Information to Manufacturing Facilities

[0799] The server sends the construction plan and materials list to a manufacturing facility, which uses the information to create the home's components using 3D printers and high-precision machine tools.

[0800] 9. Parts production, transportation and assembly

[0801] The parts manufactured at the manufacturing facility are transported to the construction site under quality control, and the construction team quickly assembles the parts according to the construction plan provided by the server to complete the home.

[0802] Specific examples

[0803] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[0804] 1. User inputs request

[0805] The newlyweds input their requirements into the terminal: "1LDK," "budget of 20 million yen," and "steel-reinforced concrete construction."

[0806] 2. The server creates the blueprint

[0807] The server receives the requested data and uses the generation AI to input a prompt such as, "Please generate a blueprint for a 1LDK house with a budget of 20 million yen and steel-reinforced concrete construction," and creates the optimal blueprint.

[0808] 3. User makes corrections

[0809] Check the blueprint and enter corrections such as "change the window position" or "make the living room larger."

[0810] 4. The server regenerates

[0811] Regenerate a new blueprint that reflects the modifications and confirm.

[0812] 5. Generate construction plans and material lists

[0813] Based on the finalized drawings, a construction plan and material list are generated and sent to the manufacturing facility.

[0814] 6. Parts are made in a manufacturing facility

[0815] Parts are produced using 3D printers and quality control is performed.

[0816] 7. On-site assembly

[0817] The parts are transported to the site and assembled by the construction team to complete the home.

[0818] This system makes it possible to quickly reflect user requests and provide high-quality housing in a short period of time.

[0819] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0820] Step 1:

[0821] The user inputs the basic requirements for the home from the evaluation device (PC, smartphone, etc.). The user inputs the floor plan, budget, type of materials, etc. into a dedicated form in a web browser. The input data is sent from the evaluation device to the server.

[0822] Step 2:

[0823] The server receives the request data sent from the device and stores it in a database. The server then launches a data analysis module, analyzes the request data, extracts information such as floor plan, budget, and type of materials, and formats it as input data for the generative AI model. This formatted data becomes the output of the analysis.

[0824] Step 3:

[0825] The server launches a generative AI model based on the formatted request data. A prompt sentence is used as input for the generative AI model. For example, the input text is "Please generate blueprints for a 1LDK house with a budget of 20 million yen and steel-framed concrete construction." The generative AI model generates the blueprint data, which is received by the server. The generated blueprint data is the output.

[0826] Step 4:

[0827] The server sends the generated blueprint data to the user's device, which then displays the received blueprint data in a web browser. The user can then check the blueprint, including the floor plan, interior, and window placement.

[0828] Step 5:

[0829] The user checks the blueprint and inputs any modifications they would like to make into the terminal, for example, by inputting specific requests such as "move the window a little further to the left" or "add a balcony." The inputted modifications are then sent back to the server.

[0830] Step 6:

[0831] The server receives the modified data sent by the user and again analyzes the modifications using the data analysis module. Based on the modified information obtained through the analysis, the generative AI model is launched again. An updated prompt such as "Please regenerate the blueprint for a 1LDK house with windows repositioned and a balcony added, with a budget of 20 million yen and steel-concrete construction" is used. The generative AI model generates new blueprint data, which is received by the server. The new blueprint data becomes the output.

[0832] Step 7:

[0833] The server automatically generates a construction plan and materials list based on the final design drawing data. The construction plan includes the order of processes and deadlines, while the materials list includes the specific types and quantities of materials. The generated construction plan and materials list are output.

[0834] Step 8:

[0835] The server then sends the generated construction plan and materials list to the manufacturing facility, which uses the received information to produce the home's components using 3D printers and high-precision machine tools. The manufactured components are the output.

[0836] Step 9:

[0837] The parts manufactured at the manufacturing facility undergo quality control before being transported to the construction site. The construction team quickly assembles the parts according to the construction plan provided by the server to complete the house. The completed house is the final output.

[0838] (Application example 1)

[0839] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0840] The present invention relates to a system that allows a user to input basic housing requirements, quickly and accurately generates house blueprints based on those requirements, and automates the entire process from manufacturing parts in a factory to assembling them on-site. However, in conventional systems, the generation of blueprints that reflect the user's requirements and the quality control of manufactured parts are often performed manually, resulting in efficiency issues. Furthermore, insufficient quality control can lead to problems after construction, resulting in additional costs and time.

[0841] 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.

[0842] In this invention, the server includes: an input means for a user to input basic housing requirements; a transmission means for transmitting the user's requirement data to the server; a generation means for receiving the requirement data and generating a housing blueprint that complies with the Building Standards Act using a generation AI; a transmission means for transmitting the generated housing blueprint to the user's terminal; a regeneration means for receiving correction data from the user and readjusting the blueprint using the generation AI; a generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a manufacturing facility; a manufacturing means for manufacturing housing components using a 3D printer based on the generated materials list at the manufacturing facility; an AI-controlled quality control means for quality control of the manufactured components; and an assembly means for transporting the manufactured components to a site and assembling the housing by a construction team. This enables the system to quickly and accurately generate blueprints that reflect the user's requirements, accurately manage the quality of the manufactured components, and realize efficient, high-quality housing construction.

[0843] A "user" is an individual or group that inputs basic housing requirements and uses the system to participate in the process from creating blueprints to construction.

[0844] "Input means" refers to an interface device that allows users to input basic housing requirements, and refers to a terminal such as a computer or smartphone.

[0845] The "transmission means" is a communication means for transmitting the request data entered by the user to the server, and is a technology for connecting to the Internet and performing data communication.

[0846] "Request data" refers to specific desired information such as the layout of the house, budget, materials to be used, etc., entered by the user.

[0847] "Generative AI" is an artificial intelligence model that automatically generates residential blueprints based on user request data, and is a technology for outputting blueprints that comply with the Building Standards Act.

[0848] "Generation means" refers to the process and function for receiving the requested data and generating a house blueprint using generation AI.

[0849] "Regeneration means" refers to the process and functionality for receiving correction data from the user and re-adjusting the design using the generation AI.

[0850] The "server" is a computer system that receives requested data, launches the generation AI, generates and transmits blueprints, and generates a construction plan and material list based on the final blueprints.

[0851] A "construction plan" is a detailed plan that describes the order, schedule, and specific steps required to build a house.

[0852] A "materials list" is a list that lists the types and quantities of materials required to build a house.

[0853] "Manufacturing facility" refers to a factory or manufacturing base where housing components are produced using 3D printers based on construction plans and material lists.

[0854] A "3D printer" is a device that produces three-dimensional parts based on blueprint data, and is a production device used in manufacturing facilities.

[0855] "Means of production" refers to the technology and process used to produce housing components using a 3D printer.

[0856] "Quality control measures" are artificial intelligence-controlled technologies that automatically check the quality of manufactured parts and correct or remanufacture them as necessary.

[0857] "Means of assembly" refers to the processes and techniques used to transport the fabricated components to the site and assemble the home by the construction team.

[0858] 1. Inputting user requirements and generating design drawings

[0859] User inputs request

[0860] The user turns on a device (e.g., a PC or smartphone) and inputs their basic housing requirements. Specifically, they input the house's layout, budget, materials to be used, etc. into a dedicated interface. This interface is designed using prompts from the generative AI model, allowing the user to input information intuitively.

[0861] Server receives requested data

[0862] The device sends the user's requested data to the server. The server analyzes the received data and activates a generative AI model to generate a home design plan that complies with the Building Standards Act. The generative AI model uses pre-trained data to create a design plan that best suits the user's needs.

[0863] 2. Check and fine-tune the design

[0864] The server sends the blueprint

[0865] The generated design drawing is sent from the server to the user's device, where the user can view the drawing on the device screen and check the detailed layout, such as the layout of the living room and the location of windows.

[0866] User enters corrections

[0867] The user can check the blueprint and, if necessary, send any modifications they wish to make to the server from their device. For example, they can input specific modifications such as "move the window a little further to the left" or "add a balcony." This allows the user to obtain the final blueprint they desire.

[0868] Server Regeneration

[0869] The server restarts the generation AI based on the correction information received from the user and regenerates the blueprint, thus completing the final blueprint that meets the user's wishes.

[0870] 3. Generate construction plans and material lists

[0871] The server generates the construction plan and material list

[0872] The server creates a construction plan based on the final design drawings and generates a list of required materials. The construction plan includes the order of work and deadlines, while the material list lists the specific types and quantities of materials.

[0873] 4. Factory production and quality control

[0874] Parts production at manufacturing facilities

[0875] Based on the construction plan and materials list sent from the server, the manufacturing facility uses 3D printers to produce the house components. The produced components are automatically checked by quality control measures controlled by artificial intelligence. Any parts that fail are remanufactured.

[0876] 5. On-site assembly

[0877] Parts transportation and on-site assembly

[0878] Once quality control is complete, the parts are transported to the site, where the construction team quickly assembles them according to the construction plan provided by the server to complete the home.

[0879] Examples and prompts

[0880] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[0881] 1. Inputting requirements: A newlywed couple inputs their requirements for a 1LDK apartment with a budget of 20 million yen and a steel-reinforced concrete structure into the terminal.

[0882] 2. Blueprint generation: The server receives the requested data and creates the optimal blueprint using the generation AI.

[0883] 3. Entering modifications: The user checks the blueprint and enters modifications such as "changing the window position" or "making the living room larger."

[0884] 4. Regenerate: The server generates a new blueprint that reflects the modifications.

[0885] Example prompt sentence:

[0886] "Control the 3D printer based on this blueprint and create the required parts."

[0887] "The basic requirements are 'a 2LDK with a spacious living room, a budget of 30 million yen, and a wooden building.' Please generate the optimal design based on this and go through the process of manufacturing the parts."

[0888] In this way, the present invention makes it possible to realize a house design that quickly and accurately reflects the user's requests, and to efficiently build a high-quality house.

[0889] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0890] Step 1:

[0891] The user inputs basic housing requirements.

[0892] Specifically, users use a device such as a computer or smartphone to input information such as the house's layout, budget, and materials used into a dedicated interface. This interface is designed based on prompts from the generative AI model, allowing for intuitive input.

[0893] Input: Basic housing requirements (floor plan, budget, materials used, etc.)

[0894] Output: Request data

[0895] Step 2:

[0896] The terminal transmits the requested data to the server.

[0897] The input request data is transmitted from the terminal to the server, which then receives the user's request.

[0898] Input: Request data

[0899] Output: Sends the requested data to the server

[0900] Step 3:

[0901] The server receives the requested data and generates a house blueprint using generation AI.

[0902] The server analyzes the received request data and activates a generative AI model to generate blueprints that comply with the Building Standards Act. The generative AI model uses pre-trained data to create optimal blueprints.

[0903] Input: Request data

[0904] Output: Generated house plan

[0905] Step 4:

[0906] The server sends the generated design drawings to the user's device.

[0907] The generated blueprints are sent from the server to the user's device, where the user can view them on the device screen.

[0908] Input: Generated house plan

[0909] Output: Sending the blueprint to the user's device

[0910] Step 5:

[0911] The user checks the design drawings and inputs requests for corrections as necessary.

[0912] The user checks the blueprint and enters any requested modifications, such as "changing the position of a window" or "adding a balcony," into a dedicated interface.

[0913] Input: Initial blueprint

[0914] Output: Corrected data

[0915] Step 6:

[0916] The server receives the modified data from the user and regenerates the blueprint using the generation AI.

[0917] The server restarts the generative AI model based on the correction data received from the user and regenerates the blueprint, resulting in a final blueprint that meets the user's wishes.

[0918] Input: Correction data

[0919] Output: Regenerated blueprint

[0920] Step 7:

[0921] The server generates a construction plan and materials list based on the final design drawings and sends them to the manufacturing facility.

[0922] The server then creates a construction plan based on the final design drawings, generating a materials list, which includes the order of steps and deadlines, and the materials list includes the specific types and quantities of materials required. This data is then sent to the manufacturing facility.

[0923] Input: Regenerated blueprint

[0924] Output: Creation and transmission of construction plans and material lists

[0925] Step 8:

[0926] A manufacturing facility will use 3D printers to create the components for the home.

[0927] The manufacturing facility uses 3D printers to create the components of the home based on the construction plans and materials list submitted.

[0928] Input: Construction plan and materials list

[0929] Output: Produced parts

[0930] Step 9:

[0931] Control the quality of manufactured parts.

[0932] The manufacturing facility's artificial intelligence-controlled quality control measures are used to automatically check the quality of the parts produced, and any parts that fail are remanufactured.

[0933] Input: Produced parts

[0934] Output: Quality controlled parts

[0935] Step 10:

[0936] The manufactured parts are transported to the site, and the construction team assembles the house.

[0937] Once quality control is complete, the parts are transported to the site, where the construction team quickly assembles the house according to the construction plan provided by the server, resulting in a high-quality home.

[0938] Input: Quality-controlled parts, construction plans

[0939] Output: Completed house

[0940] 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.

[0941] The present invention combines an emotion engine with a system in which a user inputs basic housing requirements, uses AI to generate blueprints, and then quickly carries out construction. A specific embodiment of this system is described below.

[0942] 1. Inputting user requirements and generating design drawings

[0943] User inputs request

[0944] Users use the device to input their basic housing requirements, including the layout, budget, materials to be used, etc. The system also has a built-in emotion engine that recognizes the user's emotions in real time.

[0945] Receipt and analysis of requested data by the server

[0946] The request data sent from the device is sent to the server. The server analyzes the received request data and uses an emotion engine to determine the user's emotional state. Based on this information, the generation AI generates a blueprint, but the design content is adjusted according to the user's emotional response.

[0947] 2. Check and correct the design drawings

[0948] The server sends the blueprint

[0949] The generated blueprint is sent from the server to the user's device. When the user checks the blueprint on their device, the emotion engine monitors the user's reaction. For example, the user's emotional state (joy, anxiety, etc.) is analyzed in real time.

[0950] User enters corrections

[0951] When the user checks the blueprint and inputs corrections, the emotion engine is also running, and suggestions based on the user's emotional state (e.g., automatic corrections for stressful parts) can be made. The corrections are then sent to the server.

[0952] Server Regeneration

[0953] The server restarts the generation AI based on the correction data and information from the emotion engine, and regenerates the blueprint, resulting in a blueprint that optimally reflects the user's wishes and emotional state.

[0954] 3. Generate construction plans and material lists

[0955] The server creates a construction plan

[0956] The server then uses the final design and data from the emotion engine to create a detailed construction plan, including the order of steps, deadlines, and considerations related to the user's emotional state.

[0957] The server generates the material list

[0958] The server may generate a list of materials required for construction and select materials according to the user's preferences based on data from the emotion engine.

[0959] Sending to partner factories

[0960] The generated construction plan and materials list are sent from the server to a partner factory, where production can proceed taking into account the emotion engine data.

[0961] 4. 3D printed parts production and assembly

[0962] In-factory production

[0963] The partner factory uses 3D printers to produce each part of the house based on a materials list. The parts are inspected under strict quality control, and the emotion engine data is also used as a reference for production.

[0964] Parts transportation and on-site assembly

[0965] The manufactured parts are transported to the construction site. The construction team quickly assembles the parts to complete the house according to a construction plan that includes feedback from the emotion engine. For example, based on user emotion data, the system can incorporate ideas to minimize stress on-site.

[0966] Specific examples

[0967] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[0968] 1. User inputs request

[0969] A newlywed couple inputs their requirements for a one-bedroom apartment with a budget of 20 million yen and a steel-reinforced concrete structure into a terminal. The emotion engine recognizes their emotions as they type.

[0970] 2. The server creates the blueprint

[0971] The server receives the request data and emotion data, and uses generative AI to create the optimal design.

[0972] 3. User makes corrections

[0973] Check the blueprint and input modifications such as "change the window position" or "make the living room larger." The emotion engine simultaneously monitors the response.

[0974] 4. The server regenerates

[0975] Generate a new blueprint that reflects the modifications and confirm it.

[0976] 5. Generate construction plans and material lists

[0977] Based on the finalized drawings and emotion data, a construction plan and materials list are generated and sent to the factory.

[0978] 6. Manufacturing parts in factories

[0979] Parts are manufactured using 3D printers, and quality and emotional data are managed.

[0980] 7. On-site assembly

[0981] The parts are transported to the site, and the construction team quickly assembles them while taking into account the emotional data to complete the home.

[0982] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to provide a home that is more user-friendly and provides a higher level of satisfaction.

[0983] The processing flow will be explained below.

[0984] Specific processing steps of the program

[0985] Step 1: User input

[0986] 1.1 User starts terminal

[0987] The user turns on a device such as a smartphone or PC and opens a dedicated application or web browser.

[0988] 1.2 User fills out request form

[0989] Users enter basic information about their housing needs (e.g., floor plan, budget, materials to be used, etc.) into an input form, and emotion-recognition cameras and sensors detect their reactions.

[0990] 1.3 Emotion engine analyzes user emotions

[0991] The emotion engine analyzes the user's input emotional data (happiness, anxiety, excitement, etc.) in real time, allowing for a more detailed understanding of the user's wishes.

[0992] Step 2: Receiving and analyzing the requested data on the server

[0993] 2.1 The device sends the request data and emotion data to the server

[0994] The terminal transmits the request data input by the user and the emotion data analyzed by the emotion engine to the server.

[0995] 2.2 The server receives the request data and emotion data

[0996] The server receives the transmitted desire data and emotion data and begins analysis.

[0997] Step 3: Generate blueprints on the server

[0998] 3.1 The server starts the generated AI

[0999] The server activates a generation AI based on the analyzed request data and emotion data to generate a blueprint.

[1000] 3.2 Server generates blueprint

[1001] The generative AI generates home blueprints that are in compliance with building standards laws and best suit the user's needs and emotions.

[1002] Step 4: Check and modify the blueprint

[1003] 4.1 The server sends the blueprint to the device

[1004] The server sends the generated design drawings to the user's terminal.

[1005] 4.2 User checks the design drawing

[1006] The user checks the blueprint on the device, and the emotion engine monitors the user's reactions using the device's camera and microphone to collect emotional data.

[1007] 4.3 User enters corrections

[1008] When a user inputs modifications to the blueprint (e.g., changing the position of a window, adding a room, etc.) into the device, the emotion engine works and makes automatic suggestions based on the user's emotional state. The modifications are then sent to the server.

[1009] Step 5: Regenerate the blueprint on the server

[1010] 5.1 The server receives the correction data and emotion data

[1011] The server receives the correction data sent by the user and the emotion data analyzed by the emotion engine.

[1012] 5.2 Server restarts generated AI

[1013] The server restarts the generation AI and regenerates the blueprint based on the correction data and emotion data.

[1014] 5.3 The server confirms the final design

[1015] The server checks whether the new design meets the user's needs and feelings, and then finalizes the design.

[1016] Step 6: Generate construction plan and materials list

[1017] 6.1 Server creates construction plan

[1018] The server then uses the final design and data from the emotion engine to create a detailed construction plan, including the order of steps, deadlines, and considerations related to the user's emotional state.

[1019] 6.2 Server generates ingredients list

[1020] The server generates a list of materials required for construction and selects materials according to the user's preferences based on data from the emotion engine.

[1021] 6.3 Server sends data to factory

[1022] The server sends the construction plan and materials list to the partner factory, which can then proceed with production while taking into account the emotion engine data.

[1023] Step 7: Factory parts production

[1024] 7.1 Factory receives data

[1025] The subcontract factory receives the construction plan and material list sent from the server.

[1026] 7.2 Factories prepare for 3D printers

[1027] The factory sets up the 3D printer and begins producing parts based on the materials list.

[1028] 7.3 3D printers produce parts

[1029] A 3D printer creates the house components according to the design, incorporating data from the emotion engine.

[1030] Step 8: Transport and assemble the parts

[1031] 8.1 Factory packs and transports parts

[1032] The factory packs the completed parts and transports them to the construction site.

[1033] 8.2 Installation team receives parts

[1034] The construction team receives the parts on-site and performs the necessary checks. Data from the emotion engine is also reflected in the construction plan.

[1035] 8.3 The construction team assembles the house

[1036] The construction team follows the construction plan provided by the server and quickly assembles the parts to complete the house. Based on feedback from the emotion engine, the construction is carried out with consideration for the user's emotions.

[1037] The above is a specific embodiment of the present invention that combines an emotion engine. This system takes into consideration the emotions of the user and provides a home that offers a higher level of satisfaction.

[1038] Example 2

[1039] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1040] With conventional home design systems, it was difficult to adjust the design content while taking the user's emotions into consideration, and as a result, it was not possible to maximize user satisfaction. Furthermore, there was no system in the design process that could make quick corrections based on the user's reactions. As a result, it was not possible to reduce the anxiety and stress felt by the user, and the efficiency of the entire design and construction process was reduced.

[1041] 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.

[1042] In this invention, the server includes: an input means for inputting the user's basic housing requirements; a transmission means for transmitting the user's requirement data and emotion data to the server; a generation means for receiving the requirement data and emotion data and generating a housing blueprint based on the user's emotional state using a generation AI; a transmission means for transmitting the generated housing blueprint and emotion data to the user's terminal and monitoring the user's reaction; a regeneration means for receiving correction data and emotion data from the user and readjusting the blueprint using the generation AI; a plan generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a factory; a production means for fabricating housing components using a 3D printer based on the generated materials list at the factory; and an assembly means for transporting the fabricated components to a site and having a construction team assemble the house based on the emotion data. This allows the system to reflect the user's emotions in real time, enabling the design and construction of homes that provide greater satisfaction.

[1043] 1. "Input means" refers to devices or software that provide an interface for users to input their basic housing requirements.

[1044] 2. "Transmission means" refers to a device or software with a communication function for transmitting user request data and emotion data to the server.

[1045] 3. "Generation means" refers to a system that uses generation AI to generate a house blueprint that corresponds to the user's emotional state based on the received request data and emotional data.

[1046] 4. The "regeneration means" is a system that receives correction data and emotional data from the user and readjusts the blueprint using a generation AI.

[1047] 5. "Plan generation means" is a system that generates a construction plan and material list based on the final design drawings and sends them to the factory.

[1048] 6. "Means of production" refers to the equipment or system that produces the housing components using a 3D printer based on a materials list generated in the factory.

[1049] 7. "Assembly means" refers to a system in which manufactured parts are transported to the site and the construction team assembles the house based on the emotional data.

[1050] 8. "Emotional data" refers to data used to read a user's emotional state in real time, and is information obtained from the user's facial expressions and voice.

[1051] 9. "Generative AI" is a system that uses artificial intelligence technology to analyze request data and emotional data and generate housing blueprints and construction plans.

[1052] 10. "Communication functions" refers to the technology that includes the network infrastructure and protocols for transmitting and receiving data.

[1053] These are the definitions of the important terms included in this system, which will clarify the technical scope and meaning of each term.

[1054] The present invention is a system that allows users to input basic housing requirements and emotional data, generates blueprints using a generative AI model, and then quickly and efficiently carries out construction based on these blueprints. Detailed embodiments of this system are described below.

[1055] User enters request information

[1056] Users use a device (e.g., smartphone, tablet, or PC) to input their basic housing requirements, including the floor plan, budget, and materials to be used. The device also has a built-in emotion engine (e.g., Affectiva or FaceReader) that reads the user's emotions in real time during the input process.

[1057] Examples:

[1058] The user inputs "1LDK, budget 20 million yen, steel-framed concrete construction" into the device's dedicated interface. At the same time, the emotion engine analyzes the user's facial expressions and voice and generates emotion parameters.

[1059] Sending request data and emotion data

[1060] The terminal packages the input desire data and emotion data and transmits the data via the Internet to a server, for example in text or digital format.

[1061] Receiving and analyzing data

[1062] The server receives the request data and emotion data sent from the device. The received data is analyzed on the server. The server analyzes the request data to understand the basic specifications of the home the user desires. At the same time, it analyzes the emotion data to understand the user's emotional state.

[1063] Examples:

[1064] The server receives and analyzes the request data, such as "1LDK, budget 20 million yen, steel-reinforced concrete construction," and emotional data, such as "joy (80%)" and "anxiety (20%)."

[1065] Blueprint generation

[1066] Based on the analysis results, the server generates a house blueprint using a generative AI model (e.g., OpenAI GPT-4). The generated blueprint is flexibly adjusted according to the user's emotional state.

[1067] Examples:

[1068] A "1LDK blueprint" is generated, and a spacious, relaxing living room is suggested based on the user's emotional data.

[1069] Sending blueprints and emotion data

[1070] The server sends the generated blueprint and emotion data to the user's device. As the user checks the blueprint, the emotion engine continues to monitor the user's reaction.

[1071] Examples:

[1072] The server sends the "proposed 1LDK blueprint" to the terminal, allowing the user to view it in real time.

[1073] Enter and submit correction data

[1074] When a user inputs changes to the blueprint into the device, the emotion engine monitors the user's reaction in real time and generates emotion data. The inputted correction data and emotion data are then sent back to the server.

[1075] Examples:

[1076] The user inputs modifications such as "change the window position" or "make the living room bigger," and the emotion engine records emotional data such as "excitement (70%)" and "concern (30%)."

[1077] Regenerating blueprints

[1078] The server restarts the generative AI model based on the correction data and emotion data, and generates a new blueprint, which optimally reflects the user's desires and emotional state.

[1079] Generate construction plans and material lists

[1080] The server generates a detailed construction plan and materials list based on the final design and emotion data. The construction plan includes process sequence, deadlines, and emotion-related considerations. The generated data is sent to a partner factory.

[1081] Examples:

[1082] The server generates a "construction plan including the start date and time of construction, the order, and noise control measures" and a "list of materials with excellent durability and design" and sends them to the factory.

[1083] Parts production using a 3D printer

[1084] The factory will use 3D printers (e.g., Stratasys, Formlabs) to produce the house components based on a materials list, and the emotional data will also be taken into account during the production process.

[1085] Examples:

[1086] The factory will produce "housing components" and will also consider "designs that reflect emotional data."

[1087] Parts transportation and assembly

[1088] The construction team transports the manufactured parts to the site and assembles them according to the construction plan. Based on the emotional data, they make efforts to minimize user stress.

[1089] Examples:

[1090] The construction team "assembles the parts in a stress-free way for the user" to complete the home.

[1091] Prompt Sentence Examples

[1092] Here is an example where a newlywed couple wants a one-bedroom, one-bedroom, one-kitchen home.

[1093] 1. User enters request:

[1094] The newlyweds entered their requirements into the terminal: "1LDK, budget 20 million yen, steel-reinforced concrete construction."

[1095] 2. The server creates the blueprint:

[1096] The server receives the request data and emotion data, and creates the optimal design using a generative AI model.

[1097] 3. User makes corrections:

[1098] Check the blueprint and enter any modifications you would like to make, such as "changing the window position" or "making the living room larger."

[1099] 4. Server regenerates:

[1100] Regenerate a new blueprint reflecting the modifications and confirm.

[1101] 5. Generate construction plans and material lists:

[1102] Based on the finalized drawings and emotion data, a construction plan and materials list are generated and sent to the factory to begin production.

[1103] 6. Factory parts manufacturing:

[1104] 3D printers are used to create housing components and manage emotional data.

[1105] 7. On-site assembly:

[1106] The manufactured parts are transported to the site, and the construction team quickly assembles them while taking into account the emotional data.

[1107] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it is possible to provide a home that is user-friendly and highly satisfying.

[1108] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1109] Step 1:

[1110] The user inputs basic housing requirements

[1111] Users use a device (e.g., smartphone, tablet, or PC) to input their basic housing requirements, including the floor plan, budget, and materials to be used. An emotion engine (e.g., Affectiva, FaceReader) analyzes the user's facial expressions and tone of voice in real time to generate emotion parameters.

[1112] Input: Request information such as "1LDK, budget 20 million yen, steel-framed concrete construction," as well as the user's facial expression and voice

[1113] Output: Desire data and emotion data (e.g., "Happy (80%), Anxiety (20%)")

[1114] Specific operation: When a user enters their request into a form on the device, the emotion engine simultaneously analyzes the user's emotions.

[1115] Step 2:

[1116] The device sends the request data and emotion data to the server.

[1117] The terminal packages the request information entered by the user and the generated emotion data, and transmits the packaged data to a server via the Internet.

[1118] Input: User-entered desire and emotion data

[1119] Output: Data sent to the server

[1120] Specific operation: The device sends the request data "1LDK, budget 20 million yen, steel-reinforced concrete construction" and the emotion data "joy (80%), anxiety (20%)" to the server.

[1121] Step 3:

[1122] The server receives and analyzes the request data and emotion data.

[1123] The server receives and analyzes the request data and emotion data sent from the terminal. It analyzes the request data to understand the user's desired specifications, and analyzes the emotion data to grasp the user's emotional state.

[1124] Input: Desire data and emotion data sent from the device

[1125] Output: Analysis of the desires and emotional state

[1126] Specific operation: The server analyzes the request data for "1LDK, budget 20 million yen, steel-reinforced concrete construction," identifies the necessary specifications, and understands the user's emotional state from the emotional data.

[1127] Step 4:

[1128] The server generates the blueprint

[1129] The server uses a generative AI model (e.g., OpenAI GPT-4) based on the analysis results to generate a house blueprint, which is flexibly adjusted according to the user's emotional state.

[1130] Input: Analysis results of desires and emotional state

[1131] Output: Emotionally adjusted house blueprints

[1132] Specific operation: The server generates a "1LDK blueprint" and includes suggestions such as a spacious, relaxing living room, taking into account the user's emotional data.

[1133] Step 5:

[1134] The server sends the generated blueprint and emotion data to the user's device.

[1135] The server sends the generated blueprint and emotion data to the user's device. While the user is checking the blueprint, the emotion engine monitors the user's reaction.

[1136] Input: Generated blueprints and emotion data

[1137] Output: Blueprints sent to the user's device and monitoring data of user reactions

[1138] Specific operation: The server sends the "proposed 1LDK blueprint" to the terminal, and the emotion engine analyzes the user's real-time reaction.

[1139] Step 6:

[1140] The user checks the design and inputs corrections

[1141] The user checks the design on the device and inputs any necessary corrections. The emotion engine analyzes the user's reaction in real time and generates emotion data.

[1142] Input: Generated design, user's correction instructions, and user's emotional response

[1143] Output: Corrected data and new emotion data

[1144] Specific operation: The user inputs modifications such as "change the window position" or "make the living room bigger," and the emotion engine generates new emotion data such as "anxiety (40%)."

[1145] Step 7:

[1146] The device sends correction data and emotion data.

[1147] The terminal transmits the modified data from the user and the newly generated emotion data to the server.

[1148] Input: User correction data and emotion data

[1149] Output: Correction data and emotion data sent to the server

[1150] Specific operation: The device sends the correction data for "changing the window position" and "making the living room larger" and the emotion data for "anxiety (40%)" to the server.

[1151] Step 8:

[1152] The server launches the regenerative AI model

[1153] The server restarts the generative AI model based on the corrected data and new emotion data, and generates a new blueprint.

[1154] Input: Corrected data and new emotion data

[1155] Output: New modified blueprint

[1156] Specific operation: The server generates a new design plan that includes window placement that allows in more natural light to reduce the user's anxiety, and sends it to the device again.

[1157] Step 9:

[1158] The server generates the construction plan and material list

[1159] The server generates a construction plan and materials list based on the final design drawings and emotion data and sends them to the partner factory.

[1160] Input: Final blueprint and emotion data

[1161] Output: Detailed construction plan and materials list

[1162] Specific operation: The server generates a "construction plan including the start date and time of construction, the order, and noise control measures" and a "list of materials with excellent durability and design" and sends them to the factory.

[1163] Step 10:

[1164] Parts are manufactured by partner factories

[1165] The partner factory will use a 3D printer (e.g., Stratasys, Formlabs) to produce the housing components based on the materials list.

[1166] Input: Materials list

[1167] Output: Produced housing components

[1168] Specific operation: Factories will produce "housing components" using 3D printers, and will also take into consideration "designs that reflect emotional data."

[1169] Step 11:

[1170] Parts transportation and on-site assembly

[1171] The construction team transports the manufactured parts to the site and assembles them according to the construction plan. Based on the emotional data, they make efforts to minimize user stress.

[1172] Input: Manufactured parts and construction plans

[1173] Output: Completed house

[1174] What it does: The construction team "assembles the parts in a stress-free way, based on the user's emotional data," completing the home.

[1175] (Application example 2)

[1176] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1177] Current home design systems have difficulty considering users' requests and emotions, resulting in low user satisfaction. Furthermore, in the case of in-store shopping experiences, there is no system that can analyze customers' real-time emotions and provide appropriate product suggestions and guidance, making it difficult to improve customer satisfaction.

[1178] 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.

[1179] In this invention, the server includes an input means for a user to input basic housing requirements, a transmission means for transmitting the user's requirement data to the server, a generation means for receiving the requirement data and generating a housing blueprint that complies with the Building Standards Act using a generation AI, a transmission means for transmitting the generated housing blueprint to the user's terminal, a regeneration means for receiving correction data from the user and readjusting the blueprint using the generation AI, a generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a factory, a fabrication means for fabricating housing components using a 3D printer based on the generated materials list at the factory, an assembly means for transporting the fabricated components to a site and having a construction team assemble the housing, an emotion recognition means for recognizing and analyzing the user's emotions in real time, and a presentation means for suggesting and providing optimal products based on the emotion data. This enables high-satisfaction housing designs that take user emotions into consideration and an improved shopping experience in physical stores.

[1180] "User" means an individual or organization wishing to design a home or shop in a physical store.

[1181] "Basic requirements" are the initial conditions and requirements such as the layout of the house, budget, materials to be used, etc.

[1182] "Input means" refers to devices or software that allow users to input their basic housing requirements.

[1183] "Transmission means" refers to the communication means and device for transmitting the user's requested data to the server.

[1184] "Server" means a computer system that receives, analyzes, and processes user-requested data.

[1185] "Generative AI" is artificial intelligence for generating house blueprints.

[1186] "Generation means" refers to the process or device that uses generative AI to generate residential blueprints that comply with the Building Standards Act.

[1187] "Terminal" refers to a computer terminal or smart device operated by a user.

[1188] "Regeneration means" refers to the process or device that receives correction data from the user and readjusts the design using the generation AI.

[1189] - "Construction plan" is a construction plan based on the final design drawings.

[1190] - "Materials List" is a list of materials required for construction.

[1191] "Means of production" refers to the process or equipment used to 3D print the housing components based on a materials list generated in the factory.

[1192] · "Means of assembly" refers to the process or equipment by which the fabricated components are transported to the site and assembled into the home by the construction team.

[1193] "Emotion recognition means" refers to technologies and systems that recognize and analyze users' emotions in real time.

[1194] "Presentation means" refers to a method or device for optimally proposing and providing product information based on emotional data.

[1195] The present invention combines an emotion engine with a system in which a user inputs basic housing requirements, uses AI to generate blueprints, and then quickly constructs the house. Specific embodiments of this system are described below.

[1196] 1. Inputting user requirements and generating design drawings

[1197] First, the user inputs their basic housing requirements using a terminal. The terminal is a device such as a smartphone or tablet, and is equipped with a dedicated interface. Input information includes the floor plan, budget, materials to be used, etc. The system also has a built-in emotion engine that recognizes the user's emotions in real time.

[1198] The user's request data is sent to the server using the transmission means. The server analyzes the received request data and uses an emotion engine to determine the user's emotional state. Based on this information, the generation AI generates a house blueprint. The generated blueprint is then sent from the server to the user's device, where the user can review it.

[1199] 2. Check and correct the design drawings

[1200] As the user reviews the blueprint, the smart glasses analyze the user's emotions and provide real-time feedback. For example, if the user feels joy or anxiety, the glasses will automatically suggest adjustments to the design based on that emotion data. The user inputs the corrections, which are then sent back to the server, where the AI ​​regenerates the design.

[1201] 3. Generate construction plans and material lists

[1202] Once the final design drawings are finalized, the server generates a construction plan and materials list, which are tailored to the user's preferences based on data from the emotion engine. The resulting construction plan and materials list are then sent to the partner factory.

[1203] 4. 3D printed parts production and assembly

[1204] In the factory, each component of the house is produced using a 3D printer based on a materials list. The produced components are then transported to the site, where the construction team quickly assembles them according to a construction plan that includes feedback from the emotion engine. This allows the delivery of homes that take user emotions into consideration and provide a high level of satisfaction.

[1205] 5. Physical store applications

[1206] The emotion engine and generative AI of this invention can also be applied to improving the shopping experience in brick-and-mortar stores. As customers wearing smart glasses walk through a store, their emotions are analyzed in real time via the smart glasses' camera and microphone. Based on the analysis results, the generative AI displays optimal product suggestions, in-store navigation, and custom messages on the smart glasses.

[1207] Prompt Sentence Examples

[1208] For example, if the emotion engine recognizes the user's "joy," it will input the following into the generative AI model:

[1209] Users are "delighted" - suggest the most popular products and those currently on sale.

[1210] The hardware used includes smart glasses, tablets, smartphones, NVIDIA Jetson, and Raspberry Pi, while the software used includes TensorFlow / Keras (for emotion recognition models), OpenCV (image processing), Flask, and FastAPI (for product suggestion APIs).

[1211] The above is a specific embodiment of the present invention, which realizes highly satisfying home design that takes into account the user's emotions and improves the shopping experience in physical stores.

[1212] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1213] Step 1:

[1214] The user uses a terminal to input basic housing requirements.

[1215] Input: Required data such as house layout, budget, materials to be used, etc.

[1216] Output: A data packet that sends the requested data to the server.

[1217] How it works: The user enters various information into a form on the device's dedicated interface and presses the send button. The emotion engine analyzes the user's emotions in real time and sends them along with the data packet.

[1218] Step 2:

[1219] The server receives the requested data and performs the analysis.

[1220] Input: Desire data and emotion data sent by the user.

[1221] Output: Parsed data to feed into the generative AI.

[1222] Specific operation: The server saves the request data in a database and uses the emotion engine to analyze the user's emotional state. Based on the analysis results, the data is converted into a format that can be input into the generation AI.

[1223] Step 3:

[1224] Generate house blueprints using generative AI.

[1225] Input: Parsed desire data and emotion data.

[1226] Output: The generated house plan.

[1227] Specific operation: The generation AI reads the request data and emotional data as prompts and generates appropriate house blueprints. The prompt uses the following sentence: "The user wants a 1LDK, budget of 20 million yen, and steel-reinforced concrete structure. The emotional state is inclined towards happiness."

[1228] Step 4:

[1229] The server sends the generated house design plan to the user's terminal.

[1230] Input: Generated house blueprint data.

[1231] Output: The blueprint displayed on the user's device.

[1232] Specific operation: The generated design drawing data is sent to the user's device and displayed using a dedicated application on the device.

[1233] Step 5:

[1234] The user checks the design drawings and inputs correction data.

[1235] Input: Correction data entered by the user after viewing the design drawings.

[1236] Output: A data packet that sends the modified data to the server.

[1237] How it works: The user checks the blueprint on the device and inputs the desired corrections. The emotion engine analyzes the user's emotional state and sends it along with the data packet.

[1238] Step 6:

[1239] The server receives the correction data and regenerates it using the generation AI.

[1240] Input: Correction data and emotion data.

[1241] Output: A regenerated house blueprint.

[1242] Specific operation: The server requests the AI ​​to regenerate the user's voice based on the correction data and emotion data. The AI ​​then updates the prompt as follows: "The user wants to change the window position and make the living room larger. The user's emotional state is anxious."

[1243] Step 7:

[1244] The server generates a construction plan and material list based on the final design drawings and sends them to the factory.

[1245] Input: Final blueprint and emotion data.

[1246] Output: Construction plan and materials list.

[1247] Specific operation: Based on the generated final design drawings and emotion data, the server creates the order of construction processes, deadlines, and a list of materials to be used, and sends this to the factory.

[1248] Step 8:

[1249] The factory uses 3D printers to produce housing components.

[1250] Input: Construction plan and materials list.

[1251] Output: Produced housing components.

[1252] What it does: The factory uses a 3D printer to produce housing components based on the materials list it receives.

[1253] Step 9:

[1254] The manufactured parts are transported to the site, and the construction team assembles the house.

[1255] Input: Manufactured housing components and construction plans.

[1256] Output: A completed house.

[1257] Specific operation: The robot receives the transported parts at the construction site and begins assembling them according to the construction plan. The robot proceeds with the construction while taking into account feedback from the emotion engine.

[1258] Step 10:

[1259] In brick-and-mortar stores, smart glasses can analyze customer emotions in real time and make product suggestions.

[1260] Input: Video and audio data from smart glasses.

[1261] Output: Customer sentiment data and optimal product recommendations.

[1262] How it works: The smart glasses' camera and microphone capture the customer's facial expressions and voice, which are then analyzed by the emotion engine. Based on the analysis results, the generative AI creates a prompt and suggests the most suitable products. For example, "The user is feeling happy. Please suggest the most popular products that are currently on sale."

[1263] 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.

[1264] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1265] 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.

[1266] [Third embodiment]

[1267] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1268] 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.

[1269] 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).

[1270] 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.

[1271] 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.

[1272] 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).

[1273] 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.

[1274] 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.

[1275] 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.

[1276] 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.

[1277] 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.

[1278] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1279] The present invention relates to a system in which a user inputs basic requirements for a house, a server generates blueprints based on the requirements using AI, and the server then promptly carries out construction. A specific embodiment of this system will be described below.

[1280] 1. Inputting user requirements and generating design drawings

[1281] User inputs request

[1282] The user starts up a terminal (such as a PC or smartphone) and inputs basic housing requirements, including the floor plan, budget, and types of materials, into an input form interactively.

[1283] Server receives requested data

[1284] The device sends the desired data entered by the user to the server. The server analyzes the received data and activates the generation AI to generate blueprints that comply with the Building Standards Act. The generation AI uses pre-trained data to create blueprints that best meet the user's needs.

[1285] 2. Check and fine-tune the design

[1286] The server sends the blueprint

[1287] The generated blueprint is sent from the server to the user's device, where the user can view the blueprint on their device screen. For example, detailed layouts such as the layout of the living room and the location of windows are displayed.

[1288] User enters corrections

[1289] The user can check the blueprint and send any necessary corrections to the server from their device. For example, they can make specific changes such as "move the window a little further to the left" or "add a balcony."

[1290] Server Regeneration

[1291] The server restarts the generation AI based on the correction information received from the user and regenerates the blueprint, thus completing the final blueprint that meets the user's wishes.

[1292] 3. Generate construction plans and material lists

[1293] The server generates the construction plan and material list

[1294] The server creates a construction plan based on the final design drawings and generates a list of required materials. The construction plan includes the order of work and deadlines, while the material list lists the specific types and quantities of materials.

[1295] Sending to partner factories

[1296] The generated construction plan and materials list are sent from the server to a partner factory, which prepares a 3D printer and produces the house components based on the information sent.

[1297] 4. 3D printed parts production and assembly

[1298] In-factory production

[1299] The partner factory uses 3D printers to produce each part of the house based on the materials list, and the parts are checked under strict quality control.

[1300] Parts transportation and on-site assembly

[1301] The manufactured parts are transported to the construction site, where the construction team quickly assembles the parts to complete the house according to the construction plan provided by the server, which details, for example, the order in which wall panels should be assembled and the steps for laying the foundation.

[1302] Specific examples

[1303] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[1304] 1. User inputs request

[1305] A newlywed couple enters their requirements for a one-bedroom, one-room kitchen, a budget of 20 million yen, and a steel-reinforced concrete structure into a terminal.

[1306] 2. The server creates the blueprint

[1307] The server receives the requested data and creates the optimal design using a generation AI.

[1308] 3. User makes corrections

[1309] Check the blueprint and enter any modifications you would like to make, such as "change the window position" or "make the living room larger."

[1310] 4. The server regenerates

[1311] Generate a new blueprint that reflects the modifications and confirm it.

[1312] 5. Generate construction plans and material lists

[1313] A construction plan and material list are generated based on the finalized drawings and sent to the factory.

[1314] 6. Manufacturing parts in factories

[1315] Parts are manufactured using 3D printers and quality controlled.

[1316] 7. On-site assembly

[1317] The parts are transported to the site and assembled by the construction team to complete the home.

[1318] The above is an embodiment of the present invention. This system makes it possible to provide high-quality housing at low cost in a short period of time.

[1319] The processing flow will be explained below.

[1320] Specific processing steps of the program

[1321] Step 1: User input

[1322] 1.1 User starts terminal

[1323] The user turns on a device such as a smartphone or PC and opens a dedicated application or web browser.

[1324] 1.2 User fills out request form

[1325] The user enters basic information about the home they are looking for (e.g., layout, budget, materials to be used, etc.) into the input form and presses the submit button.

[1326] Step 2: Receiving and analyzing the requested data on the server

[1327] 2.1 The device sends the requested data to the server

[1328] The terminal transmits the request data input by the user to the server.

[1329] 2.2 The server receives the requested data

[1330] The server receives the transmitted request data and begins analyzing it.

[1331] Step 3: Generate blueprints on the server

[1332] 3.1 The server starts the generated AI

[1333] The server activates a generation AI based on the analyzed request data and generates a blueprint.

[1334] 3.2 Server generates blueprint

[1335] The generation AI generates house blueprints that best meet the user's needs while complying with the Building Standards Act.

[1336] Step 4: Check and modify the blueprint

[1337] 4.1 The server sends the blueprint to the device

[1338] The server sends the generated design drawings to the user's terminal.

[1339] 4.2 User checks the design drawing

[1340] The user checks the blueprint on the terminal and considers whether there are any problems with the contents.

[1341] 4.3 User enters corrections

[1342] The user inputs modifications to the blueprint (e.g., changing the position of a window, adding a room, etc.) into the terminal and sends them to the server.

[1343] Step 5: Regenerate the blueprint on the server

[1344] 5.1 Server receives modified data

[1345] The server receives the correction data sent by the user.

[1346] 5.2 Server restarts generated AI

[1347] The server will restart the generation AI and regenerate the blueprint based on the modified data.

[1348] 5.3 The server confirms the final design

[1349] The server checks whether the new design meets the user's requirements and confirms the final design.

[1350] Step 6: Generate construction plan and materials list

[1351] 6.1 Server creates construction plan

[1352] The server will create a detailed construction plan based on the final design drawings.

[1353] 6.2 Server generates ingredients list

[1354] The server generates a list of materials required for construction.

[1355] 6.3 Server sends data to factory

[1356] The server transmits the construction plan and material list to the subcontract factory.

[1357] Step 7: Factory parts production

[1358] 7.1 Factory receives data

[1359] The subcontract factory receives the construction plan and material list sent from the server.

[1360] 7.2 Factories prepare for 3D printers

[1361] The factory sets up the 3D printer and begins producing parts based on the materials list.

[1362] 7.3 3D printers produce parts

[1363] A 3D printer will create the components of the house according to the specified design.

[1364] Step 8: Transport and assemble the parts

[1365] 8.1 Factory packs and transports parts

[1366] The factory packs the completed parts and transports them to the construction site.

[1367] 8.2 Installation team receives parts

[1368] The construction team receives the parts on site and performs the necessary checks.

[1369] 8.3 The construction team assembles the house

[1370] The construction team quickly assembles the house based on the construction plan provided by the server, resulting in the completion of a high-quality home in a short period of time.

[1371] The above is the specific flow of program processing. This system allows users to obtain low-cost housing efficiently and quickly.

[1372] Example 1

[1373] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1374] The conventional housing design and construction process is time-consuming and costly, and it is difficult to accurately reflect the user's needs. Furthermore, there are many uncertainties in the design changes and material procurement processes, which frequently result in project delays and budget overruns. The purpose of this invention is to solve these problems and enable housing design and construction that quickly and accurately meets the user's needs.

[1375] 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.

[1376] In this invention, the server includes an input means for a user to input basic requirements for a home, a transmission means for transmitting the user's requirement data to the server, a generation means for receiving the requirement data and generating a home blueprint using a generative AI model, a transmission means for transmitting the generated home blueprint to the user's terminal, a regeneration means for receiving correction data from the user and readjusting the blueprint using the generative AI model, a generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a manufacturing facility, a manufacturing means for manufacturing home components using a 3D printer based on the generated materials list at the manufacturing facility, and an assembly means for transporting the manufactured components to a site and having a construction team assemble the home. This makes it possible to quickly and accurately reflect user requirements and provide high-quality homes in a short period of time.

[1377] "Basic housing requirements" refer to the user's desired housing conditions, such as layout, budget, and materials to be used.

[1378] "Input means" refers to a device or software interface that allows a user to input basic housing requirements.

[1379] The "transmission means" refers to a device or software that has the function of transmitting the user's requested data to the server.

[1380] "Server" refers to the machine and software that processes data received from users, generates house blueprints, and draws up construction plans.

[1381] A "generative AI model" is an artificial intelligence program that uses machine learning technology to automatically generate house blueprints from training data.

[1382] "Generation means" refers to devices or software that have the function of using generative AI models to create house blueprints, construction plans, and material lists.

[1383] A "terminal" is a device such as a personal computer or smartphone operated by a user.

[1384] A "regeneration means" is a device or software that has the function of readjusting a design using a generative AI model based on correction data from the user.

[1385] A "construction plan" refers to a plan that shows the series of work processes and schedule required to build a house.

[1386] A "materials list" is a list that lists the types and quantities of materials needed to build a house.

[1387] A "manufacturing facility" is a place where housing components are produced using 3D printers and high-precision machine tools.

[1388] A "production tool" is any equipment or software used to produce parts based on a materials list at a manufacturing facility.

[1389] "Assembly means" refers to the equipment and methods for transporting fabricated components to the site and assembling the home.

[1390] MODE FOR CARRYING OUT THE INVENTION

[1391] The present invention relates to a system in which a user inputs basic requirements for a house, a server generates blueprints based on those requirements using AI, and the server then promptly carries out construction. A specific method for implementing this system is described below.

[1392] Hardware and Software Configuration

[1393] 1. Terminal

[1394] Hardware: PC, smartphone

[1395] Software: Web browser

[1396] 2. Server

[1397] Hardware: High-performance servers (e.g. cloud servers in a data center)

[1398] Software: drafting software (e.g., AutoCAD, Revit), generative AI (e.g., GPT-4)

[1399] 3. Manufacturing Facilities

[1400] Hardware: 3D printers, high-precision machine tools

[1401] Software: Parts production management software (e.g., Siemens NX)

[1402] Specific operation of the system

[1403] 1. User request input

[1404] Users use a device (PC or smartphone) to input their basic housing requirements on a web browser. Specific requirements such as floor plan, budget, and types of materials are entered interactively in the input form.

[1405] 2. Receipt and analysis of requested data by the server

[1406] The device sends the input request data to the server, which then uses a data analysis module to extract elements such as floor plan, budget, and type of materials, and formats them as input data for the generative AI model.

[1407] 3. Server-based blueprint generation

[1408] The server inputs the formatted request data into a generative AI model (e.g., GPT-4). The prompt text used is something like, "Please generate a blueprint for a 1LDK house with a budget of 20 million yen and steel-framed concrete construction." The generative AI generates the blueprint, and the server receives the results.

[1409] 4. Submit your blueprints

[1410] The generated blueprint is sent from the server to the user's device, where the user can view it in a web browser. This blueprint includes detailed information such as the floor plan, interior, and window placement.

[1411] 5. Check and correct the design drawings

[1412] The user checks the blueprint and inputs any modifications they wish to make, such as "move the window a little further to the left" or "add a balcony." The modification data is then sent from the terminal to the server.

[1413] 6. Server Regeneration

[1414] The server re-runs the generative AI model based on the corrections received from the user and regenerates the blueprint. This process can be repeated until a new blueprint is generated.

[1415] 7. Generate construction plans and material lists

[1416] Once the final design drawings are finalized, the server automatically generates a construction plan and materials list based on them. The construction plan includes the order of work and deadlines, while the materials list includes the specific types and quantities of materials.

[1417] 8. Transmission of Information to Manufacturing Facilities

[1418] The server sends the construction plan and materials list to a manufacturing facility, which uses the information to create the home's components using 3D printers and high-precision machine tools.

[1419] 9. Parts production, transportation and assembly

[1420] The parts manufactured at the manufacturing facility are transported to the construction site under quality control, and the construction team quickly assembles the parts according to the construction plan provided by the server to complete the home.

[1421] Specific examples

[1422] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[1423] 1. User inputs request

[1424] The newlyweds input their requirements into the terminal: "1LDK," "budget of 20 million yen," and "steel-reinforced concrete construction."

[1425] 2. The server creates the blueprint

[1426] The server receives the requested data and uses the generation AI to input a prompt such as, "Please generate a blueprint for a 1LDK house with a budget of 20 million yen and steel-reinforced concrete construction," and creates the optimal blueprint.

[1427] 3. User makes corrections

[1428] Check the blueprint and enter corrections such as "change the window position" or "make the living room larger."

[1429] 4. The server regenerates

[1430] Regenerate a new blueprint that reflects the modifications and confirm.

[1431] 5. Generate construction plans and material lists

[1432] Based on the finalized drawings, a construction plan and material list are generated and sent to the manufacturing facility.

[1433] 6. Parts are made in a manufacturing facility

[1434] Parts are produced using 3D printers and quality control is performed.

[1435] 7. On-site assembly

[1436] The parts are transported to the site and assembled by the construction team to complete the home.

[1437] This system makes it possible to quickly reflect user requests and provide high-quality housing in a short period of time.

[1438] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1439] Step 1:

[1440] The user inputs the basic requirements for the home from the evaluation device (PC, smartphone, etc.). The user inputs the floor plan, budget, type of materials, etc. into a dedicated form in a web browser. The input data is sent from the evaluation device to the server.

[1441] Step 2:

[1442] The server receives the request data sent from the device and stores it in a database. The server then launches a data analysis module, analyzes the request data, extracts information such as floor plan, budget, and type of materials, and formats it as input data for the generative AI model. This formatted data becomes the output of the analysis.

[1443] Step 3:

[1444] The server launches a generative AI model based on the formatted request data. A prompt sentence is used as input for the generative AI model. For example, the input text is "Please generate blueprints for a 1LDK house with a budget of 20 million yen and steel-framed concrete construction." The generative AI model generates the blueprint data, which is received by the server. The generated blueprint data is the output.

[1445] Step 4:

[1446] The server sends the generated blueprint data to the user's device, which then displays the received blueprint data in a web browser. The user can then check the blueprint, including the floor plan, interior, and window placement.

[1447] Step 5:

[1448] The user checks the blueprint and inputs any modifications they would like to make into the terminal, for example, by inputting specific requests such as "move the window a little further to the left" or "add a balcony." The inputted modifications are then sent back to the server.

[1449] Step 6:

[1450] The server receives the modified data sent by the user and again analyzes the modifications using the data analysis module. Based on the modified information obtained through the analysis, the generative AI model is launched again. An updated prompt such as "Please regenerate the blueprint for a 1LDK house with windows repositioned and a balcony added, with a budget of 20 million yen and steel-concrete construction" is used. The generative AI model generates new blueprint data, which is received by the server. The new blueprint data becomes the output.

[1451] Step 7:

[1452] The server automatically generates a construction plan and materials list based on the final design drawing data. The construction plan includes the order of processes and deadlines, while the materials list includes the specific types and quantities of materials. The generated construction plan and materials list are output.

[1453] Step 8:

[1454] The server then sends the generated construction plan and materials list to the manufacturing facility, which uses the received information to produce the home's components using 3D printers and high-precision machine tools. The manufactured components are the output.

[1455] Step 9:

[1456] The parts manufactured at the manufacturing facility undergo quality control before being transported to the construction site. The construction team quickly assembles the parts according to the construction plan provided by the server to complete the house. The completed house is the final output.

[1457] (Application example 1)

[1458] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1459] The present invention relates to a system that allows a user to input basic housing requirements, quickly and accurately generates house blueprints based on those requirements, and automates the entire process from manufacturing parts in a factory to assembling them on-site. However, in conventional systems, the generation of blueprints that reflect the user's requirements and the quality control of manufactured parts are often performed manually, resulting in efficiency issues. Furthermore, insufficient quality control can lead to problems after construction, resulting in additional costs and time.

[1460] 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.

[1461] In this invention, the server includes: an input means for a user to input basic housing requirements; a transmission means for transmitting the user's requirement data to the server; a generation means for receiving the requirement data and generating a housing blueprint that complies with the Building Standards Act using a generation AI; a transmission means for transmitting the generated housing blueprint to the user's terminal; a regeneration means for receiving correction data from the user and readjusting the blueprint using the generation AI; a generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a manufacturing facility; a manufacturing means for manufacturing housing components using a 3D printer based on the generated materials list at the manufacturing facility; an AI-controlled quality control means for quality control of the manufactured components; and an assembly means for transporting the manufactured components to a site and assembling the housing by a construction team. This enables the system to quickly and accurately generate blueprints that reflect the user's requirements, accurately manage the quality of the manufactured components, and realize efficient, high-quality housing construction.

[1462] A "user" is an individual or group that inputs basic housing requirements and uses the system to participate in the process from creating blueprints to construction.

[1463] "Input means" refers to an interface device that allows users to input basic housing requirements, and refers to a terminal such as a computer or smartphone.

[1464] The "transmission means" is a communication means for transmitting the request data entered by the user to the server, and is a technology for connecting to the Internet and performing data communication.

[1465] "Request data" refers to specific desired information such as the layout of the house, budget, materials to be used, etc., entered by the user.

[1466] "Generative AI" is an artificial intelligence model that automatically generates residential blueprints based on user request data, and is a technology for outputting blueprints that comply with the Building Standards Act.

[1467] "Generation means" refers to the process and function for receiving the requested data and generating a house blueprint using generation AI.

[1468] "Regeneration means" refers to the process and functionality for receiving correction data from the user and re-adjusting the design using the generation AI.

[1469] The "server" is a computer system that receives requested data, launches the generation AI, generates and transmits blueprints, and generates a construction plan and material list based on the final blueprints.

[1470] A "construction plan" is a detailed plan that describes the order, schedule, and specific steps required to build a house.

[1471] A "materials list" is a list that lists the types and quantities of materials required to build a house.

[1472] "Manufacturing facility" refers to a factory or manufacturing base where housing components are produced using 3D printers based on construction plans and material lists.

[1473] A "3D printer" is a device that produces three-dimensional parts based on blueprint data, and is a production device used in manufacturing facilities.

[1474] "Means of production" refers to the technology and process used to produce housing components using a 3D printer.

[1475] "Quality control measures" are artificial intelligence-controlled technologies that automatically check the quality of manufactured parts and correct or remanufacture them as necessary.

[1476] "Means of assembly" refers to the processes and techniques used to transport the fabricated components to the site and assemble the home by the construction team.

[1477] 1. Inputting user requirements and generating design drawings

[1478] User inputs request

[1479] The user turns on a device (e.g., a PC or smartphone) and inputs their basic housing requirements. Specifically, they input the house's layout, budget, materials to be used, etc. into a dedicated interface. This interface is designed using prompts from the generative AI model, allowing the user to input information intuitively.

[1480] Server receives requested data

[1481] The device sends the user's requested data to the server. The server analyzes the received data and activates a generative AI model to generate a home design plan that complies with the Building Standards Act. The generative AI model uses pre-trained data to create a design plan that best suits the user's needs.

[1482] 2. Check and fine-tune the design

[1483] The server sends the blueprint

[1484] The generated design drawing is sent from the server to the user's device, where the user can view the drawing on the device screen and check the detailed layout, such as the layout of the living room and the location of windows.

[1485] User enters corrections

[1486] The user can check the blueprint and, if necessary, send any modifications they wish to make to the server from their device. For example, they can input specific modifications such as "move the window a little further to the left" or "add a balcony." This allows the user to obtain the final blueprint they desire.

[1487] Server Regeneration

[1488] The server restarts the generation AI based on the correction information received from the user and regenerates the blueprint, thus completing the final blueprint that meets the user's wishes.

[1489] 3. Generate construction plans and material lists

[1490] The server generates the construction plan and material list

[1491] The server creates a construction plan based on the final design drawings and generates a list of required materials. The construction plan includes the order of work and deadlines, while the material list lists the specific types and quantities of materials.

[1492] 4. Factory production and quality control

[1493] Parts production at manufacturing facilities

[1494] Based on the construction plan and materials list sent from the server, the manufacturing facility uses 3D printers to produce the house components. The produced components are automatically checked by quality control measures controlled by artificial intelligence. Any parts that fail are remanufactured.

[1495] 5. On-site assembly

[1496] Parts transportation and on-site assembly

[1497] Once quality control is complete, the parts are transported to the site, where the construction team quickly assembles them according to the construction plan provided by the server to complete the home.

[1498] Examples and prompts

[1499] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[1500] 1. Inputting requirements: A newlywed couple inputs their requirements for a 1LDK apartment with a budget of 20 million yen and a steel-reinforced concrete structure into the terminal.

[1501] 2. Blueprint generation: The server receives the requested data and creates the optimal blueprint using the generation AI.

[1502] 3. Entering modifications: The user checks the blueprint and enters modifications such as "changing the window position" or "making the living room larger."

[1503] 4. Regenerate: The server generates a new blueprint that reflects the modifications.

[1504] Example prompt sentence:

[1505] "Control the 3D printer based on this blueprint and create the required parts."

[1506] "The basic requirements are 'a 2LDK with a spacious living room, a budget of 30 million yen, and a wooden building.' Please generate the optimal design based on this and go through the process of manufacturing the parts."

[1507] In this way, the present invention makes it possible to realize a house design that quickly and accurately reflects the user's requests, and to efficiently build a high-quality house.

[1508] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1509] Step 1:

[1510] The user inputs basic housing requirements.

[1511] Specifically, users use a device such as a computer or smartphone to input information such as the house's layout, budget, and materials used into a dedicated interface. This interface is designed based on prompts from the generative AI model, allowing for intuitive input.

[1512] Input: Basic housing requirements (floor plan, budget, materials used, etc.)

[1513] Output: Request data

[1514] Step 2:

[1515] The terminal transmits the requested data to the server.

[1516] The input request data is transmitted from the terminal to the server, which then receives the user's request.

[1517] Input: Request data

[1518] Output: Sends the requested data to the server

[1519] Step 3:

[1520] The server receives the requested data and generates a house blueprint using generation AI.

[1521] The server analyzes the received request data and activates a generative AI model to generate blueprints that comply with the Building Standards Act. The generative AI model uses pre-trained data to create optimal blueprints.

[1522] Input: Request data

[1523] Output: Generated house plan

[1524] Step 4:

[1525] The server sends the generated design drawings to the user's device.

[1526] The generated blueprints are sent from the server to the user's device, where the user can view them on the device screen.

[1527] Input: Generated house plan

[1528] Output: Sending the blueprint to the user's device

[1529] Step 5:

[1530] The user checks the design drawings and inputs requests for corrections as necessary.

[1531] The user checks the blueprint and enters any requested modifications, such as "changing the position of a window" or "adding a balcony," into a dedicated interface.

[1532] Input: Initial blueprint

[1533] Output: Corrected data

[1534] Step 6:

[1535] The server receives the modified data from the user and regenerates the blueprint using the generation AI.

[1536] The server restarts the generative AI model based on the correction data received from the user and regenerates the blueprint, resulting in a final blueprint that meets the user's wishes.

[1537] Input: Correction data

[1538] Output: Regenerated blueprint

[1539] Step 7:

[1540] The server generates a construction plan and materials list based on the final design drawings and sends them to the manufacturing facility.

[1541] The server then creates a construction plan based on the final design drawings, generating a materials list, which includes the order of steps and deadlines, and the materials list includes the specific types and quantities of materials required. This data is then sent to the manufacturing facility.

[1542] Input: Regenerated blueprint

[1543] Output: Creation and transmission of construction plans and material lists

[1544] Step 8:

[1545] A manufacturing facility will use 3D printers to create the components for the home.

[1546] The manufacturing facility uses 3D printers to create the components of the home based on the construction plans and materials list submitted.

[1547] Input: Construction plan and materials list

[1548] Output: Produced parts

[1549] Step 9:

[1550] Control the quality of manufactured parts.

[1551] The manufacturing facility's artificial intelligence-controlled quality control measures are used to automatically check the quality of the parts produced, and any parts that fail are remanufactured.

[1552] Input: Produced parts

[1553] Output: Quality controlled parts

[1554] Step 10:

[1555] The manufactured parts are transported to the site, and the construction team assembles the house.

[1556] Once quality control is complete, the parts are transported to the site, where the construction team quickly assembles the house according to the construction plan provided by the server, resulting in a high-quality home.

[1557] Input: Quality-controlled parts, construction plans

[1558] Output: Completed house

[1559] 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.

[1560] The present invention combines an emotion engine with a system in which a user inputs basic housing requirements, uses AI to generate blueprints, and then quickly carries out construction. A specific embodiment of this system is described below.

[1561] 1. Inputting user requirements and generating design drawings

[1562] User inputs request

[1563] Users use the device to input their basic housing requirements, including the layout, budget, materials to be used, etc. The system also has a built-in emotion engine that recognizes the user's emotions in real time.

[1564] Receipt and analysis of requested data by the server

[1565] The request data sent from the device is sent to the server. The server analyzes the received request data and uses an emotion engine to determine the user's emotional state. Based on this information, the generation AI generates a blueprint, but the design content is adjusted according to the user's emotional response.

[1566] 2. Check and correct the design drawings

[1567] The server sends the blueprint

[1568] The generated blueprint is sent from the server to the user's device. When the user checks the blueprint on their device, the emotion engine monitors the user's reaction. For example, the user's emotional state (joy, anxiety, etc.) is analyzed in real time.

[1569] User enters corrections

[1570] When the user checks the blueprint and inputs corrections, the emotion engine is also running, and suggestions based on the user's emotional state (e.g., automatic corrections for stressful parts) can be made. The corrections are then sent to the server.

[1571] Server Regeneration

[1572] The server restarts the generation AI based on the correction data and information from the emotion engine, and regenerates the blueprint, resulting in a blueprint that optimally reflects the user's wishes and emotional state.

[1573] 3. Generate construction plans and material lists

[1574] The server creates a construction plan

[1575] The server then uses the final design and data from the emotion engine to create a detailed construction plan, including the order of steps, deadlines, and considerations related to the user's emotional state.

[1576] The server generates the material list

[1577] The server may generate a list of materials required for construction and select materials according to the user's preferences based on data from the emotion engine.

[1578] Sending to partner factories

[1579] The generated construction plan and materials list are sent from the server to a partner factory, where production can proceed taking into account the emotion engine data.

[1580] 4. 3D printed parts production and assembly

[1581] In-factory production

[1582] The partner factory uses 3D printers to produce each part of the house based on a materials list. The parts are inspected under strict quality control, and the emotion engine data is also used as a reference for production.

[1583] Parts transportation and on-site assembly

[1584] The manufactured parts are transported to the construction site. The construction team quickly assembles the parts to complete the house according to a construction plan that includes feedback from the emotion engine. For example, based on user emotion data, the system can incorporate ideas to minimize stress on-site.

[1585] Specific examples

[1586] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[1587] 1. User inputs request

[1588] A newlywed couple inputs their requirements for a one-bedroom apartment with a budget of 20 million yen and a steel-reinforced concrete structure into a terminal. The emotion engine recognizes their emotions as they type.

[1589] 2. The server creates the blueprint

[1590] The server receives the request data and emotion data, and uses generative AI to create the optimal design.

[1591] 3. User makes corrections

[1592] Check the blueprint and input modifications such as "change the window position" or "make the living room larger." The emotion engine simultaneously monitors the response.

[1593] 4. The server regenerates

[1594] Generate a new blueprint that reflects the modifications and confirm it.

[1595] 5. Generate construction plans and material lists

[1596] Based on the finalized drawings and emotion data, a construction plan and materials list are generated and sent to the factory.

[1597] 6. Manufacturing parts in factories

[1598] Parts are manufactured using 3D printers, and quality and emotional data are managed.

[1599] 7. On-site assembly

[1600] The parts are transported to the site, and the construction team quickly assembles them while taking into account the emotional data to complete the home.

[1601] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to provide a home that is more user-friendly and provides a higher level of satisfaction.

[1602] The processing flow will be explained below.

[1603] Specific processing steps of the program

[1604] Step 1: User input

[1605] 1.1 User starts terminal

[1606] The user turns on a device such as a smartphone or PC and opens a dedicated application or web browser.

[1607] 1.2 User fills out request form

[1608] Users enter basic information about their housing needs (e.g., floor plan, budget, materials to be used, etc.) into an input form, and emotion-recognition cameras and sensors detect their reactions.

[1609] 1.3 Emotion engine analyzes user emotions

[1610] The emotion engine analyzes the user's input emotional data (happiness, anxiety, excitement, etc.) in real time, allowing for a more detailed understanding of the user's wishes.

[1611] Step 2: Receiving and analyzing the requested data on the server

[1612] 2.1 The device sends the request data and emotion data to the server

[1613] The terminal transmits the request data input by the user and the emotion data analyzed by the emotion engine to the server.

[1614] 2.2 The server receives the request data and emotion data

[1615] The server receives the transmitted desire data and emotion data and begins analysis.

[1616] Step 3: Generate blueprints on the server

[1617] 3.1 The server starts the generated AI

[1618] The server activates a generation AI based on the analyzed request data and emotion data to generate a blueprint.

[1619] 3.2 Server generates blueprint

[1620] The generative AI generates home blueprints that are in compliance with building standards laws and best suit the user's needs and emotions.

[1621] Step 4: Check and modify the blueprint

[1622] 4.1 The server sends the blueprint to the device

[1623] The server sends the generated design drawings to the user's terminal.

[1624] 4.2 User checks the design drawing

[1625] The user checks the blueprint on the device, and the emotion engine monitors the user's reactions using the device's camera and microphone to collect emotional data.

[1626] 4.3 User enters corrections

[1627] When a user inputs modifications to the blueprint (e.g., changing the position of a window, adding a room, etc.) into the device, the emotion engine works and makes automatic suggestions based on the user's emotional state. The modifications are then sent to the server.

[1628] Step 5: Regenerate the blueprint on the server

[1629] 5.1 The server receives the correction data and emotion data

[1630] The server receives the correction data sent by the user and the emotion data analyzed by the emotion engine.

[1631] 5.2 Server restarts generated AI

[1632] The server restarts the generation AI and regenerates the blueprint based on the correction data and emotion data.

[1633] 5.3 The server confirms the final design

[1634] The server checks whether the new design meets the user's needs and feelings, and then finalizes the design.

[1635] Step 6: Generate construction plan and materials list

[1636] 6.1 Server creates construction plan

[1637] The server then uses the final design and data from the emotion engine to create a detailed construction plan, including the order of steps, deadlines, and considerations related to the user's emotional state.

[1638] 6.2 Server generates ingredients list

[1639] The server generates a list of materials required for construction and selects materials according to the user's preferences based on data from the emotion engine.

[1640] 6.3 Server sends data to factory

[1641] The server sends the construction plan and materials list to the partner factory, which can then proceed with production while taking into account the emotion engine data.

[1642] Step 7: Factory parts production

[1643] 7.1 Factory receives data

[1644] The subcontract factory receives the construction plan and material list sent from the server.

[1645] 7.2 Factories prepare for 3D printers

[1646] The factory sets up the 3D printer and begins producing parts based on the materials list.

[1647] 7.3 3D printers produce parts

[1648] A 3D printer creates the house components according to the design, incorporating data from the emotion engine.

[1649] Step 8: Transport and assemble the parts

[1650] 8.1 Factory packs and transports parts

[1651] The factory packs the completed parts and transports them to the construction site.

[1652] 8.2 Installation team receives parts

[1653] The construction team receives the parts on-site and performs the necessary checks. Data from the emotion engine is also reflected in the construction plan.

[1654] 8.3 The construction team assembles the house

[1655] The construction team follows the construction plan provided by the server and quickly assembles the parts to complete the house. Based on feedback from the emotion engine, the construction is carried out with consideration for the user's emotions.

[1656] The above is a specific embodiment of the present invention that combines an emotion engine. This system takes into consideration the emotions of the user and provides a home that offers a higher level of satisfaction.

[1657] Example 2

[1658] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1659] With conventional home design systems, it was difficult to adjust the design content while taking the user's emotions into consideration, and as a result, it was not possible to maximize user satisfaction. Furthermore, there was no system in the design process that could make quick corrections based on the user's reactions. As a result, it was not possible to reduce the anxiety and stress felt by the user, and the efficiency of the entire design and construction process was reduced.

[1660] 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.

[1661] In this invention, the server includes: an input means for inputting the user's basic housing requirements; a transmission means for transmitting the user's requirement data and emotion data to the server; a generation means for receiving the requirement data and emotion data and generating a housing blueprint based on the user's emotional state using a generation AI; a transmission means for transmitting the generated housing blueprint and emotion data to the user's terminal and monitoring the user's reaction; a regeneration means for receiving correction data and emotion data from the user and readjusting the blueprint using the generation AI; a plan generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a factory; a production means for fabricating housing components using a 3D printer based on the generated materials list at the factory; and an assembly means for transporting the fabricated components to a site and having a construction team assemble the house based on the emotion data. This allows the system to reflect the user's emotions in real time, enabling the design and construction of homes that provide greater satisfaction.

[1662] 1. "Input means" refers to devices or software that provide an interface for users to input their basic housing requirements.

[1663] 2. "Transmission means" refers to a device or software with a communication function for transmitting user request data and emotion data to the server.

[1664] 3. "Generation means" refers to a system that uses generation AI to generate a house blueprint that corresponds to the user's emotional state based on the received request data and emotional data.

[1665] 4. The "regeneration means" is a system that receives correction data and emotional data from the user and readjusts the blueprint using a generation AI.

[1666] 5. "Plan generation means" is a system that generates a construction plan and material list based on the final design drawings and sends them to the factory.

[1667] 6. "Means of production" refers to the equipment or system that produces the housing components using a 3D printer based on a materials list generated in the factory.

[1668] 7. "Assembly means" refers to a system in which manufactured parts are transported to the site and the construction team assembles the house based on the emotional data.

[1669] 8. "Emotional data" refers to data used to read a user's emotional state in real time, and is information obtained from the user's facial expressions and voice.

[1670] 9. "Generative AI" is a system that uses artificial intelligence technology to analyze request data and emotional data and generate housing blueprints and construction plans.

[1671] 10. "Communication functions" refers to the technology that includes the network infrastructure and protocols for transmitting and receiving data.

[1672] These are the definitions of the important terms included in this system, which will clarify the technical scope and meaning of each term.

[1673] The present invention is a system that allows users to input basic housing requirements and emotional data, generates blueprints using a generative AI model, and then quickly and efficiently carries out construction based on these blueprints. Detailed embodiments of this system are described below.

[1674] User enters request information

[1675] Users use a device (e.g., smartphone, tablet, or PC) to input their basic housing requirements, including the floor plan, budget, and materials to be used. The device also has a built-in emotion engine (e.g., Affectiva or FaceReader) that reads the user's emotions in real time during the input process.

[1676] Examples:

[1677] The user inputs "1LDK, budget 20 million yen, steel-framed concrete construction" into the device's dedicated interface. At the same time, the emotion engine analyzes the user's facial expressions and voice and generates emotion parameters.

[1678] Sending request data and emotion data

[1679] The terminal packages the input desire data and emotion data and transmits the data via the Internet to a server, for example in text or digital format.

[1680] Receiving and analyzing data

[1681] The server receives the request data and emotion data sent from the device. The received data is analyzed on the server. The server analyzes the request data to understand the basic specifications of the home the user desires. At the same time, it analyzes the emotion data to understand the user's emotional state.

[1682] Examples:

[1683] The server receives and analyzes the request data, such as "1LDK, budget 20 million yen, steel-reinforced concrete construction," and emotional data, such as "joy (80%)" and "anxiety (20%)."

[1684] Blueprint generation

[1685] Based on the analysis results, the server generates a house blueprint using a generative AI model (e.g., OpenAI GPT-4). The generated blueprint is flexibly adjusted according to the user's emotional state.

[1686] Examples:

[1687] A "1LDK blueprint" is generated, and a spacious, relaxing living room is suggested based on the user's emotional data.

[1688] Sending blueprints and emotion data

[1689] The server sends the generated blueprint and emotion data to the user's device. As the user checks the blueprint, the emotion engine continues to monitor the user's reaction.

[1690] Examples:

[1691] The server sends the "proposed 1LDK blueprint" to the terminal, allowing the user to view it in real time.

[1692] Enter and submit correction data

[1693] When a user inputs changes to the blueprint into the device, the emotion engine monitors the user's reaction in real time and generates emotion data. The inputted correction data and emotion data are then sent back to the server.

[1694] Examples:

[1695] The user inputs modifications such as "change the window position" or "make the living room bigger," and the emotion engine records emotional data such as "excitement (70%)" and "concern (30%)."

[1696] Regenerating blueprints

[1697] The server restarts the generative AI model based on the correction data and emotion data, and generates a new blueprint, which optimally reflects the user's desires and emotional state.

[1698] Generate construction plans and material lists

[1699] The server generates a detailed construction plan and materials list based on the final design and emotion data. The construction plan includes process sequence, deadlines, and emotion-related considerations. The generated data is sent to a partner factory.

[1700] Examples:

[1701] The server generates a "construction plan including the start date and time of construction, the order, and noise control measures" and a "list of materials with excellent durability and design" and sends them to the factory.

[1702] Parts production using a 3D printer

[1703] The factory will use 3D printers (e.g., Stratasys, Formlabs) to produce the house components based on a materials list, and the emotional data will also be taken into account during the production process.

[1704] Examples:

[1705] The factory will produce "housing components" and will also consider "designs that reflect emotional data."

[1706] Parts transportation and assembly

[1707] The construction team transports the manufactured parts to the site and assembles them according to the construction plan. Based on the emotional data, they make efforts to minimize user stress.

[1708] Examples:

[1709] The construction team "assembles the parts in a stress-free way for the user" to complete the home.

[1710] Prompt Sentence Examples

[1711] Here is an example where a newlywed couple wants a one-bedroom, one-bedroom, one-kitchen home.

[1712] 1. User enters request:

[1713] The newlyweds entered their requirements into the terminal: "1LDK, budget 20 million yen, steel-reinforced concrete construction."

[1714] 2. The server creates the blueprint:

[1715] The server receives the request data and emotion data, and creates the optimal design using a generative AI model.

[1716] 3. User makes corrections:

[1717] Check the blueprint and enter any modifications you would like to make, such as "changing the window position" or "making the living room larger."

[1718] 4. Server regenerates:

[1719] Regenerate a new blueprint reflecting the modifications and confirm.

[1720] 5. Generate construction plans and material lists:

[1721] Based on the finalized drawings and emotion data, a construction plan and materials list are generated and sent to the factory to begin production.

[1722] 6. Factory parts manufacturing:

[1723] 3D printers are used to create housing components and manage emotional data.

[1724] 7. On-site assembly:

[1725] The manufactured parts are transported to the site, and the construction team quickly assembles them while taking into account the emotional data.

[1726] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it is possible to provide a home that is user-friendly and highly satisfying.

[1727] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1728] Step 1:

[1729] The user inputs basic housing requirements

[1730] Users use a device (e.g., smartphone, tablet, or PC) to input their basic housing requirements, including the floor plan, budget, and materials to be used. An emotion engine (e.g., Affectiva, FaceReader) analyzes the user's facial expressions and tone of voice in real time to generate emotion parameters.

[1731] Input: Request information such as "1LDK, budget 20 million yen, steel-framed concrete construction," as well as the user's facial expression and voice

[1732] Output: Desire data and emotion data (e.g., "Happy (80%), Anxiety (20%)")

[1733] Specific operation: When a user enters their request into a form on the device, the emotion engine simultaneously analyzes the user's emotions.

[1734] Step 2:

[1735] The device sends the request data and emotion data to the server.

[1736] The terminal packages the request information entered by the user and the generated emotion data, and transmits the packaged data to a server via the Internet.

[1737] Input: User-entered desire and emotion data

[1738] Output: Data sent to the server

[1739] Specific operation: The device sends the request data "1LDK, budget 20 million yen, steel-reinforced concrete construction" and the emotion data "joy (80%), anxiety (20%)" to the server.

[1740] Step 3:

[1741] The server receives and analyzes the request data and emotion data.

[1742] The server receives and analyzes the request data and emotion data sent from the terminal. It analyzes the request data to understand the user's desired specifications, and analyzes the emotion data to grasp the user's emotional state.

[1743] Input: Desire data and emotion data sent from the device

[1744] Output: Analysis of the desires and emotional state

[1745] Specific operation: The server analyzes the request data for "1LDK, budget 20 million yen, steel-reinforced concrete construction," identifies the necessary specifications, and understands the user's emotional state from the emotional data.

[1746] Step 4:

[1747] The server generates the blueprint

[1748] The server uses a generative AI model (e.g., OpenAI GPT-4) based on the analysis results to generate a house blueprint, which is flexibly adjusted according to the user's emotional state.

[1749] Input: Analysis results of desires and emotional state

[1750] Output: Emotionally adjusted house blueprints

[1751] Specific operation: The server generates a "1LDK blueprint" and includes suggestions such as a spacious, relaxing living room, taking into account the user's emotional data.

[1752] Step 5:

[1753] The server sends the generated blueprint and emotion data to the user's device.

[1754] The server sends the generated blueprint and emotion data to the user's device. While the user is checking the blueprint, the emotion engine monitors the user's reaction.

[1755] Input: Generated blueprints and emotion data

[1756] Output: Blueprints sent to the user's device and monitoring data of user reactions

[1757] Specific operation: The server sends the "proposed 1LDK blueprint" to the terminal, and the emotion engine analyzes the user's real-time reaction.

[1758] Step 6:

[1759] The user checks the design and inputs corrections

[1760] The user checks the design on the device and inputs any necessary corrections. The emotion engine analyzes the user's reaction in real time and generates emotion data.

[1761] Input: Generated design, user's correction instructions, and user's emotional response

[1762] Output: Corrected data and new emotion data

[1763] Specific operation: The user inputs modifications such as "change the window position" or "make the living room bigger," and the emotion engine generates new emotion data such as "anxiety (40%)."

[1764] Step 7:

[1765] The device sends correction data and emotion data.

[1766] The terminal transmits the modified data from the user and the newly generated emotion data to the server.

[1767] Input: User correction data and emotion data

[1768] Output: Correction data and emotion data sent to the server

[1769] Specific operation: The device sends the correction data for "changing the window position" and "making the living room larger" and the emotion data for "anxiety (40%)" to the server.

[1770] Step 8:

[1771] The server launches the regenerative AI model

[1772] The server restarts the generative AI model based on the corrected data and new emotion data, and generates a new blueprint.

[1773] Input: Corrected data and new emotion data

[1774] Output: New modified blueprint

[1775] Specific operation: The server generates a new design plan that includes window placement that allows in more natural light to reduce the user's anxiety, and sends it to the device again.

[1776] Step 9:

[1777] The server generates the construction plan and material list

[1778] The server generates a construction plan and materials list based on the final design drawings and emotion data and sends them to the partner factory.

[1779] Input: Final blueprint and emotion data

[1780] Output: Detailed construction plan and materials list

[1781] Specific operation: The server generates a "construction plan including the start date and time of construction, the order, and noise control measures" and a "list of materials with excellent durability and design" and sends them to the factory.

[1782] Step 10:

[1783] Parts are manufactured by partner factories

[1784] The partner factory will use a 3D printer (e.g., Stratasys, Formlabs) to produce the housing components based on the materials list.

[1785] Input: Materials list

[1786] Output: Produced housing components

[1787] Specific operation: Factories will produce "housing components" using 3D printers, and will also take into consideration "designs that reflect emotional data."

[1788] Step 11:

[1789] Parts transportation and on-site assembly

[1790] The construction team transports the manufactured parts to the site and assembles them according to the construction plan. Based on the emotional data, they make efforts to minimize user stress.

[1791] Input: Manufactured parts and construction plans

[1792] Output: Completed house

[1793] What it does: The construction team "assembles the parts in a stress-free way, based on the user's emotional data," completing the home.

[1794] (Application example 2)

[1795] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1796] Current home design systems have difficulty considering users' requests and emotions, resulting in low user satisfaction. Furthermore, in the case of in-store shopping experiences, there is no system that can analyze customers' real-time emotions and provide appropriate product suggestions and guidance, making it difficult to improve customer satisfaction.

[1797] 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.

[1798] In this invention, the server includes an input means for a user to input basic housing requirements, a transmission means for transmitting the user's requirement data to the server, a generation means for receiving the requirement data and generating a housing blueprint that complies with the Building Standards Act using a generation AI, a transmission means for transmitting the generated housing blueprint to the user's terminal, a regeneration means for receiving correction data from the user and readjusting the blueprint using the generation AI, a generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a factory, a fabrication means for fabricating housing components using a 3D printer based on the generated materials list at the factory, an assembly means for transporting the fabricated components to a site and having a construction team assemble the housing, an emotion recognition means for recognizing and analyzing the user's emotions in real time, and a presentation means for suggesting and providing optimal products based on the emotion data. This enables high-satisfaction housing designs that take user emotions into consideration and an improved shopping experience in physical stores.

[1799] "User" means an individual or organization wishing to design a home or shop in a physical store.

[1800] "Basic requirements" are the initial conditions and requirements such as the layout of the house, budget, materials to be used, etc.

[1801] "Input means" refers to devices or software that allow users to input their basic housing requirements.

[1802] "Transmission means" refers to the communication means and device for transmitting the user's requested data to the server.

[1803] "Server" means a computer system that receives, analyzes, and processes user-requested data.

[1804] "Generative AI" is artificial intelligence for generating house blueprints.

[1805] "Generation means" refers to the process or device that uses generative AI to generate residential blueprints that comply with the Building Standards Act.

[1806] "Terminal" refers to a computer terminal or smart device operated by a user.

[1807] "Regeneration means" refers to the process or device that receives correction data from the user and readjusts the design using the generation AI.

[1808] - "Construction plan" is a construction plan based on the final design drawings.

[1809] - "Materials List" is a list of materials required for construction.

[1810] "Means of production" refers to the process or equipment used to 3D print the housing components based on a materials list generated in the factory.

[1811] · "Means of assembly" refers to the process or equipment by which the fabricated components are transported to the site and assembled into the home by the construction team.

[1812] "Emotion recognition means" refers to technologies and systems that recognize and analyze users' emotions in real time.

[1813] "Presentation means" refers to a method or device for optimally proposing and providing product information based on emotional data.

[1814] The present invention combines an emotion engine with a system in which a user inputs basic housing requirements, uses AI to generate blueprints, and then quickly constructs the house. Specific embodiments of this system are described below.

[1815] 1. Inputting user requirements and generating design drawings

[1816] First, the user inputs their basic housing requirements using a terminal. The terminal is a device such as a smartphone or tablet, and is equipped with a dedicated interface. Input information includes the floor plan, budget, materials to be used, etc. The system also has a built-in emotion engine that recognizes the user's emotions in real time.

[1817] The user's request data is sent to the server using the transmission means. The server analyzes the received request data and uses an emotion engine to determine the user's emotional state. Based on this information, the generation AI generates a house blueprint. The generated blueprint is then sent from the server to the user's device, where the user can review it.

[1818] 2. Check and correct the design drawings

[1819] As the user reviews the blueprint, the smart glasses analyze the user's emotions and provide real-time feedback. For example, if the user feels joy or anxiety, the glasses will automatically suggest adjustments to the design based on that emotion data. The user inputs the corrections, which are then sent back to the server, where the AI ​​regenerates the design.

[1820] 3. Generate construction plans and material lists

[1821] Once the final design drawings are finalized, the server generates a construction plan and materials list, which are tailored to the user's preferences based on data from the emotion engine. The resulting construction plan and materials list are then sent to the partner factory.

[1822] 4. 3D printed parts production and assembly

[1823] In the factory, each component of the house is produced using a 3D printer based on a materials list. The produced components are then transported to the site, where the construction team quickly assembles them according to a construction plan that includes feedback from the emotion engine. This allows the delivery of homes that take user emotions into consideration and provide a high level of satisfaction.

[1824] 5. Physical store applications

[1825] The emotion engine and generative AI of this invention can also be applied to improving the shopping experience in brick-and-mortar stores. As customers wearing smart glasses walk through a store, their emotions are analyzed in real time via the smart glasses' camera and microphone. Based on the analysis results, the generative AI displays optimal product suggestions, in-store navigation, and custom messages on the smart glasses.

[1826] Prompt Sentence Examples

[1827] For example, if the emotion engine recognizes the user's "joy," it will input the following into the generative AI model:

[1828] Users are "delighted" - suggest the most popular products and those currently on sale.

[1829] The hardware used includes smart glasses, tablets, smartphones, NVIDIA Jetson, and Raspberry Pi, while the software used includes TensorFlow / Keras (for emotion recognition models), OpenCV (image processing), Flask, and FastAPI (for product suggestion APIs).

[1830] The above is a specific embodiment of the present invention, which realizes highly satisfying home design that takes into account the user's emotions and improves the shopping experience in physical stores.

[1831] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1832] Step 1:

[1833] The user uses a terminal to input basic housing requirements.

[1834] Input: Required data such as house layout, budget, materials to be used, etc.

[1835] Output: A data packet that sends the requested data to the server.

[1836] How it works: The user enters various information into a form on the device's dedicated interface and presses the send button. The emotion engine analyzes the user's emotions in real time and sends them along with the data packet.

[1837] Step 2:

[1838] The server receives the requested data and performs the analysis.

[1839] Input: Desire data and emotion data sent by the user.

[1840] Output: Parsed data to feed into the generative AI.

[1841] Specific operation: The server saves the request data in a database and uses the emotion engine to analyze the user's emotional state. Based on the analysis results, the data is converted into a format that can be input into the generation AI.

[1842] Step 3:

[1843] Generate house blueprints using generative AI.

[1844] Input: Parsed desire data and emotion data.

[1845] Output: The generated house plan.

[1846] Specific operation: The generation AI reads the request data and emotional data as prompts and generates appropriate house blueprints. The prompt uses the following sentence: "The user wants a 1LDK, budget of 20 million yen, and steel-reinforced concrete structure. The emotional state is inclined towards happiness."

[1847] Step 4:

[1848] The server sends the generated house design plan to the user's terminal.

[1849] Input: Generated house blueprint data.

[1850] Output: The blueprint displayed on the user's device.

[1851] Specific operation: The generated design drawing data is sent to the user's device and displayed using a dedicated application on the device.

[1852] Step 5:

[1853] The user checks the design drawings and inputs correction data.

[1854] Input: Correction data entered by the user after viewing the design drawings.

[1855] Output: A data packet that sends the modified data to the server.

[1856] How it works: The user checks the blueprint on the device and inputs the desired corrections. The emotion engine analyzes the user's emotional state and sends it along with the data packet.

[1857] Step 6:

[1858] The server receives the correction data and regenerates it using the generation AI.

[1859] Input: Correction data and emotion data.

[1860] Output: A regenerated house blueprint.

[1861] Specific operation: The server requests the AI ​​to regenerate the user's voice based on the correction data and emotion data. The AI ​​then updates the prompt as follows: "The user wants to change the window position and make the living room larger. The user's emotional state is anxious."

[1862] Step 7:

[1863] The server generates a construction plan and material list based on the final design drawings and sends them to the factory.

[1864] Input: Final blueprint and emotion data.

[1865] Output: Construction plan and materials list.

[1866] Specific operation: Based on the generated final design drawings and emotion data, the server creates the order of construction processes, deadlines, and a list of materials to be used, and sends this to the factory.

[1867] Step 8:

[1868] The factory uses 3D printers to produce housing components.

[1869] Input: Construction plan and materials list.

[1870] Output: Produced housing components.

[1871] What it does: The factory uses a 3D printer to produce housing components based on the materials list it receives.

[1872] Step 9:

[1873] The manufactured parts are transported to the site, and the construction team assembles the house.

[1874] Input: Manufactured housing components and construction plans.

[1875] Output: A completed house.

[1876] Specific operation: The robot receives the transported parts at the construction site and begins assembling them according to the construction plan. The robot proceeds with the construction while taking into account feedback from the emotion engine.

[1877] Step 10:

[1878] In brick-and-mortar stores, smart glasses can analyze customer emotions in real time and make product suggestions.

[1879] Input: Video and audio data from smart glasses.

[1880] Output: Customer sentiment data and optimal product recommendations.

[1881] How it works: The smart glasses' camera and microphone capture the customer's facial expressions and voice, which are then analyzed by the emotion engine. Based on the analysis results, the generative AI creates a prompt and suggests the most suitable products. For example, "The user is feeling happy. Please suggest the most popular products that are currently on sale."

[1882] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1883] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1884] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1885] [Fourth embodiment]

[1886] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1887] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1888] 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).

[1889] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1890] 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.

[1891] 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).

[1892] 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.

[1893] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1894] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1895] 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.

[1896] 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.

[1897] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1898] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1899] The present invention relates to a system in which a user inputs basic requirements for a house, a server generates blueprints based on those requirements using AI, and the server then promptly carries out construction. A specific embodiment of this system will be described below.

[1900] 1. Inputting user requirements and generating design drawings

[1901] User inputs request

[1902] The user starts up a terminal (such as a PC or smartphone) and inputs basic housing requirements, including the floor plan, budget, and types of materials, into an input form interactively.

[1903] Server receives requested data

[1904] The device sends the desired data entered by the user to the server. The server analyzes the received data and activates the generation AI to generate blueprints that comply with the Building Standards Act. The generation AI uses pre-trained data to create blueprints that best meet the user's needs.

[1905] 2. Check and fine-tune the design

[1906] The server sends the blueprint

[1907] The generated blueprint is sent from the server to the user's device, where the user can view the blueprint on their device screen. For example, detailed layouts such as the layout of the living room and the location of windows are displayed.

[1908] User enters corrections

[1909] The user can check the blueprint and send any necessary corrections to the server from their device. For example, they can make specific changes such as "move the window a little further to the left" or "add a balcony."

[1910] Server Regeneration

[1911] The server restarts the generation AI based on the correction information received from the user and regenerates the blueprint, thus completing the final blueprint that meets the user's wishes.

[1912] 3. Generate construction plans and material lists

[1913] The server generates the construction plan and material list

[1914] The server creates a construction plan based on the final design drawings and generates a list of required materials. The construction plan includes the order of work and deadlines, while the material list lists the specific types and quantities of materials.

[1915] Sending to partner factories

[1916] The generated construction plan and materials list are sent from the server to a partner factory, which prepares a 3D printer and produces the house components based on the information sent.

[1917] 4. 3D printed parts production and assembly

[1918] In-factory production

[1919] The partner factory uses 3D printers to produce each part of the house based on the materials list, and the parts are checked under strict quality control.

[1920] Parts transportation and on-site assembly

[1921] The manufactured parts are transported to the construction site, where the construction team quickly assembles the parts to complete the house according to the construction plan provided by the server, which details, for example, the order in which wall panels should be assembled and the steps for laying the foundation.

[1922] Specific examples

[1923] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[1924] 1. User inputs request

[1925] A newlywed couple enters their requirements for a one-bedroom, one-room kitchen, a budget of 20 million yen, and a steel-reinforced concrete structure into a terminal.

[1926] 2. The server creates the blueprint

[1927] The server receives the requested data and creates the optimal design using a generation AI.

[1928] 3. User makes corrections

[1929] Check the blueprint and enter any modifications you would like to make, such as "change the window position" or "make the living room larger."

[1930] 4. The server regenerates

[1931] Generate a new blueprint that reflects the modifications and confirm it.

[1932] 5. Generate construction plans and material lists

[1933] A construction plan and material list are generated based on the finalized drawings and sent to the factory.

[1934] 6. Manufacturing parts in factories

[1935] Parts are manufactured using 3D printers and quality controlled.

[1936] 7. On-site assembly

[1937] The parts are transported to the site and assembled by the construction team to complete the home.

[1938] The above is an embodiment of the present invention. This system makes it possible to provide high-quality housing at low cost in a short period of time.

[1939] The processing flow will be explained below.

[1940] Specific processing steps of the program

[1941] Step 1: User input

[1942] 1.1 User starts terminal

[1943] The user turns on a device such as a smartphone or PC and opens a dedicated application or web browser.

[1944] 1.2 User fills out request form

[1945] The user enters basic information about the home they are looking for (e.g., layout, budget, materials to be used, etc.) into the input form and presses the submit button.

[1946] Step 2: Receiving and analyzing the requested data on the server

[1947] 2.1 The device sends the requested data to the server

[1948] The terminal transmits the request data input by the user to the server.

[1949] 2.2 The server receives the requested data

[1950] The server receives the transmitted request data and begins analyzing it.

[1951] Step 3: Generate blueprints on the server

[1952] 3.1 The server starts the generated AI

[1953] The server activates a generation AI based on the analyzed request data and generates a blueprint.

[1954] 3.2 Server generates blueprint

[1955] The generation AI generates house blueprints that best meet the user's needs while complying with the Building Standards Act.

[1956] Step 4: Check and modify the blueprint

[1957] 4.1 The server sends the blueprint to the device

[1958] The server sends the generated design drawings to the user's terminal.

[1959] 4.2 User checks the design drawing

[1960] The user checks the blueprint on the terminal and considers whether there are any problems with the contents.

[1961] 4.3 User enters corrections

[1962] The user inputs modifications to the blueprint (e.g., changing the position of a window, adding a room, etc.) into the terminal and sends them to the server.

[1963] Step 5: Regenerate the blueprint on the server

[1964] 5.1 Server receives modified data

[1965] The server receives the correction data sent by the user.

[1966] 5.2 Server restarts generated AI

[1967] The server will restart the generation AI and regenerate the blueprint based on the modified data.

[1968] 5.3 The server confirms the final design

[1969] The server checks whether the new design meets the user's requirements and confirms the final design.

[1970] Step 6: Generate construction plan and materials list

[1971] 6.1 Server creates construction plan

[1972] The server will create a detailed construction plan based on the final design drawings.

[1973] 6.2 Server generates ingredients list

[1974] The server generates a list of materials required for construction.

[1975] 6.3 Server sends data to factory

[1976] The server transmits the construction plan and material list to the subcontract factory.

[1977] Step 7: Factory parts production

[1978] 7.1 Factory receives data

[1979] The subcontract factory receives the construction plan and material list sent from the server.

[1980] 7.2 Factories prepare for 3D printers

[1981] The factory sets up the 3D printer and begins producing parts based on the materials list.

[1982] 7.3 3D printers produce parts

[1983] A 3D printer will create the components of the house according to the specified design.

[1984] Step 8: Transport and assemble the parts

[1985] 8.1 Factory packs and transports parts

[1986] The factory packs the completed parts and transports them to the construction site.

[1987] 8.2 Installation team receives parts

[1988] The construction team receives the parts on site and performs the necessary checks.

[1989] 8.3 The construction team assembles the house

[1990] The construction team quickly assembles the house based on the construction plan provided by the server, resulting in the completion of a high-quality home in a short period of time.

[1991] The above is the specific flow of program processing. This system allows users to obtain low-cost housing efficiently and quickly.

[1992] Example 1

[1993] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1994] The conventional housing design and construction process is time-consuming and costly, and it is difficult to accurately reflect the user's needs. Furthermore, there are many uncertainties in the design changes and material procurement processes, which frequently result in project delays and budget overruns. The purpose of this invention is to solve these problems and enable housing design and construction that quickly and accurately meets the user's needs.

[1995] 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.

[1996] In this invention, the server includes an input means for a user to input basic requirements for a home, a transmission means for transmitting the user's requirement data to the server, a generation means for receiving the requirement data and generating a home blueprint using a generative AI model, a transmission means for transmitting the generated home blueprint to the user's terminal, a regeneration means for receiving correction data from the user and readjusting the blueprint using the generative AI model, a generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a manufacturing facility, a manufacturing means for manufacturing home components using a 3D printer based on the generated materials list at the manufacturing facility, and an assembly means for transporting the manufactured components to a site and having a construction team assemble the home. This makes it possible to quickly and accurately reflect user requirements and provide high-quality homes in a short period of time.

[1997] "Basic housing requirements" refer to the user's desired housing conditions, such as layout, budget, and materials to be used.

[1998] "Input means" refers to a device or software interface that allows a user to input basic housing requirements.

[1999] The "transmission means" refers to a device or software that has the function of transmitting the user's requested data to the server.

[2000] "Server" refers to the machine and software that processes data received from users, generates house blueprints, and draws up construction plans.

[2001] A "generative AI model" is an artificial intelligence program that uses machine learning technology to automatically generate house blueprints from training data.

[2002] "Generation means" refers to devices or software that have the function of using generative AI models to create house blueprints, construction plans, and material lists.

[2003] A "terminal" is a device such as a personal computer or smartphone operated by a user.

[2004] A "regeneration means" is a device or software that has the function of readjusting a design using a generative AI model based on correction data from the user.

[2005] A "construction plan" refers to a plan that shows the series of work processes and schedule required to build a house.

[2006] A "materials list" is a list that lists the types and quantities of materials needed to build a house.

[2007] A "manufacturing facility" is a place where housing components are produced using 3D printers and high-precision machine tools.

[2008] A "production tool" is any equipment or software used to produce parts based on a materials list at a manufacturing facility.

[2009] "Assembly means" refers to the equipment and methods for transporting fabricated components to the site and assembling the home.

[2010] MODE FOR CARRYING OUT THE INVENTION

[2011] The present invention relates to a system in which a user inputs basic requirements for a house, a server generates blueprints based on those requirements using AI, and the server then promptly carries out construction. A specific method for implementing this system is described below.

[2012] Hardware and Software Configuration

[2013] 1. Terminal

[2014] Hardware: PC, smartphone

[2015] Software: Web browser

[2016] 2. Server

[2017] Hardware: High-performance servers (e.g. cloud servers in a data center)

[2018] Software: drafting software (e.g., AutoCAD, Revit), generative AI (e.g., GPT-4)

[2019] 3. Manufacturing Facilities

[2020] Hardware: 3D printers, high-precision machine tools

[2021] Software: Parts production management software (e.g., Siemens NX)

[2022] Specific operation of the system

[2023] 1. User request input

[2024] Users use a device (PC or smartphone) to input their basic housing requirements on a web browser. Specific requirements such as floor plan, budget, and types of materials are entered interactively in the input form.

[2025] 2. Receipt and analysis of requested data by the server

[2026] The device sends the input request data to the server, which then uses a data analysis module to extract elements such as floor plan, budget, and type of materials, and formats them as input data for the generative AI model.

[2027] 3. Server-based blueprint generation

[2028] The server inputs the formatted request data into a generative AI model (e.g., GPT-4). The prompt text used is something like, "Please generate a blueprint for a 1LDK house with a budget of 20 million yen and steel-framed concrete construction." The generative AI generates the blueprint, and the server receives the results.

[2029] 4. Submit your blueprints

[2030] The generated blueprint is sent from the server to the user's device, where the user can view it in a web browser. This blueprint includes detailed information such as the floor plan, interior, and window placement.

[2031] 5. Check and correct the design drawings

[2032] The user checks the blueprint and inputs any modifications they wish to make, such as "move the window a little further to the left" or "add a balcony." The modification data is then sent from the terminal to the server.

[2033] 6. Server Regeneration

[2034] The server re-runs the generative AI model based on the corrections received from the user and regenerates the blueprint. This process can be repeated until a new blueprint is generated.

[2035] 7. Generate construction plans and material lists

[2036] Once the final design drawings are finalized, the server automatically generates a construction plan and materials list based on them. The construction plan includes the order of work and deadlines, while the materials list includes the specific types and quantities of materials.

[2037] 8. Transmission of Information to Manufacturing Facilities

[2038] The server sends the construction plan and materials list to a manufacturing facility, which uses the information to create the home's components using 3D printers and high-precision machine tools.

[2039] 9. Parts production, transportation and assembly

[2040] The parts manufactured at the manufacturing facility are transported to the construction site under quality control, and the construction team quickly assembles the parts according to the construction plan provided by the server to complete the home.

[2041] Specific examples

[2042] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[2043] 1. User inputs request

[2044] The newlyweds input their requirements into the terminal: "1LDK," "budget of 20 million yen," and "steel-reinforced concrete construction."

[2045] 2. The server creates the blueprint

[2046] The server receives the requested data and uses the generation AI to input a prompt such as, "Please generate a blueprint for a 1LDK house with a budget of 20 million yen and steel-reinforced concrete construction," and creates the optimal blueprint.

[2047] 3. User makes corrections

[2048] Check the blueprint and enter corrections such as "change the window position" or "make the living room larger."

[2049] 4. The server regenerates

[2050] Regenerate a new blueprint that reflects the modifications and confirm.

[2051] 5. Generate construction plans and material lists

[2052] Based on the finalized drawings, a construction plan and material list are generated and sent to the manufacturing facility.

[2053] 6. Parts are made in a manufacturing facility

[2054] Parts are produced using 3D printers and quality control is performed.

[2055] 7. On-site assembly

[2056] The parts are transported to the site and assembled by the construction team to complete the home.

[2057] This system makes it possible to quickly reflect user requests and provide high-quality housing in a short period of time.

[2058] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2059] Step 1:

[2060] The user inputs the basic requirements for the home from the evaluation device (PC, smartphone, etc.). The user inputs the floor plan, budget, type of materials, etc. into a dedicated form in a web browser. The input data is sent from the evaluation device to the server.

[2061] Step 2:

[2062] The server receives the request data sent from the device and stores it in a database. The server then launches a data analysis module, analyzes the request data, extracts information such as floor plan, budget, and type of materials, and formats it as input data for the generative AI model. This formatted data becomes the output of the analysis.

[2063] Step 3:

[2064] The server launches a generative AI model based on the formatted request data. A prompt sentence is used as input for the generative AI model. For example, the input text is "Please generate blueprints for a 1LDK house with a budget of 20 million yen and steel-framed concrete construction." The generative AI model generates the blueprint data, which is received by the server. The generated blueprint data is the output.

[2065] Step 4:

[2066] The server sends the generated blueprint data to the user's device, which then displays the received blueprint data in a web browser. The user can then check the blueprint, including the floor plan, interior, and window placement.

[2067] Step 5:

[2068] The user checks the blueprint and inputs any modifications they would like to make into the terminal, for example, by inputting specific requests such as "move the window a little further to the left" or "add a balcony." The inputted modifications are then sent back to the server.

[2069] Step 6:

[2070] The server receives the modified data sent by the user and again analyzes the modifications using the data analysis module. Based on the modified information obtained through the analysis, the generative AI model is launched again. An updated prompt such as "Please regenerate the blueprint for a 1LDK house with windows repositioned and a balcony added, with a budget of 20 million yen and steel-concrete construction" is used. The generative AI model generates new blueprint data, which is received by the server. The new blueprint data becomes the output.

[2071] Step 7:

[2072] The server automatically generates a construction plan and materials list based on the final design drawing data. The construction plan includes the order of processes and deadlines, while the materials list includes the specific types and quantities of materials. The generated construction plan and materials list are output.

[2073] Step 8:

[2074] The server then sends the generated construction plan and materials list to the manufacturing facility, which uses the received information to produce the home's components using 3D printers and high-precision machine tools. The manufactured components are the output.

[2075] Step 9:

[2076] The parts manufactured at the manufacturing facility undergo quality control before being transported to the construction site. The construction team quickly assembles the parts according to the construction plan provided by the server to complete the house. The completed house is the final output.

[2077] (Application example 1)

[2078] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2079] The present invention relates to a system that allows a user to input basic housing requirements, quickly and accurately generates house blueprints based on those requirements, and automates the entire process from manufacturing parts in a factory to assembling them on-site. However, in conventional systems, the generation of blueprints that reflect the user's requirements and the quality control of manufactured parts are often performed manually, resulting in efficiency issues. Furthermore, insufficient quality control can lead to problems after construction, resulting in additional costs and time.

[2080] 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.

[2081] In this invention, the server includes: an input means for a user to input basic housing requirements; a transmission means for transmitting the user's requirement data to the server; a generation means for receiving the requirement data and generating a housing blueprint that complies with the Building Standards Act using a generation AI; a transmission means for transmitting the generated housing blueprint to the user's terminal; a regeneration means for receiving correction data from the user and readjusting the blueprint using the generation AI; a generation means for generating a construction plan and materials list based on the final blueprint and transmitting them to a manufacturing facility; a manufacturing means for manufacturing housing components using a 3D printer based on the generated materials list at the manufacturing facility; an AI-controlled quality control means for quality control of the manufactured components; and an assembly means for transporting the manufactured components to a site and assembling the housing by a construction team. This enables the system to quickly and accurately generate blueprints that reflect the user's requirements, accurately manage the quality of the manufactured components, and realize efficient, high-quality housing construction.

[2082] A "user" is an individual or group that inputs basic housing requirements and uses the system to participate in the process from creating blueprints to construction.

[2083] "Input means" refers to an interface device that allows users to input basic housing requirements, and refers to a terminal such as a computer or smartphone.

[2084] The "transmission means" is a communication means for transmitting the request data entered by the user to the server, and is a technology for connecting to the Internet and performing data communication.

[2085] "Request data" refers to specific desired information such as the layout of the house, budget, materials to be used, etc., entered by the user.

[2086] "Generative AI" is an artificial intelligence model that automatically generates residential blueprints based on user request data, and is a technology for outputting blueprints that comply with the Building Standards Act.

[2087] "Generation means" refers to the process and function for receiving the requested data and generating a house blueprint using generation AI.

[2088] "Regeneration means" refers to the process and functionality for receiving correction data from the user and re-adjusting the design using the generation AI.

[2089] The "server" is a computer system that receives requested data, launches the generation AI, generates and transmits blueprints, and generates a construction plan and material list based on the final blueprints.

[2090] A "construction plan" is a detailed plan that describes the order, schedule, and specific steps required to build a house.

[2091] A "materials list" is a list that lists the types and quantities of materials required to build a house.

[2092] "Manufacturing facility" refers to a factory or manufacturing base where housing components are produced using 3D printers based on construction plans and material lists.

[2093] A "3D printer" is a device that produces three-dimensional parts based on blueprint data, and is a production device used in manufacturing facilities.

[2094] "Means of production" refers to the technology and process used to produce housing components using a 3D printer.

[2095] "Quality control measures" are artificial intelligence-controlled technologies that automatically check the quality of manufactured parts and correct or remanufacture them as necessary.

[2096] "Means of assembly" refers to the processes and techniques used to transport the fabricated components to the site and assemble the home by the construction team.

[2097] 1. Inputting user requirements and generating design drawings

[2098] User inputs request

[2099] The user turns on a device (e.g., a PC or smartphone) and inputs their basic housing requirements. Specifically, they input the house's layout, budget, materials to be used, etc. into a dedicated interface. This interface is designed using prompts from the generative AI model, allowing the user to input information intuitively.

[2100] Server receives requested data

[2101] The device sends the user's requested data to the server. The server analyzes the received data and activates a generative AI model to generate a home design plan that complies with the Building Standards Act. The generative AI model uses pre-trained data to create a design plan that best suits the user's needs.

[2102] 2. Check and fine-tune the design

[2103] The server sends the blueprint

[2104] The generated design drawing is sent from the server to the user's device, where the user can view the drawing on the device screen and check the detailed layout, such as the layout of the living room and the location of windows.

[2105] User enters corrections

[2106] The user can check the blueprint and, if necessary, send any modifications they wish to make to the server from their device. For example, they can input specific modifications such as "move the window a little further to the left" or "add a balcony." This allows the user to obtain the final blueprint they desire.

[2107] Server Regeneration

[2108] The server restarts the generation AI based on the correction information received from the user and regenerates the blueprint, thus completing the final blueprint that meets the user's wishes.

[2109] 3. Generate construction plans and material lists

[2110] The server generates the construction plan and material list

[2111] The server creates a construction plan based on the final design drawings and generates a list of required materials. The construction plan includes the order of work and deadlines, while the material list lists the specific types and quantities of materials.

[2112] 4. Factory production and quality control

[2113] Parts production at manufacturing facilities

[2114] Based on the construction plan and materials list sent from the server, the manufacturing facility uses 3D printers to produce the house components. The produced components are automatically checked by quality control measures controlled by artificial intelligence. Any parts that fail are remanufactured.

[2115] 5. On-site assembly

[2116] Parts transportation and on-site assembly

[2117] Once quality control is complete, the parts are transported to the site, where the construction team quickly assembles them according to the construction plan provided by the server to complete the home.

[2118] Examples and prompts

[2119] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[2120] 1. Inputting requirements: A newlywed couple inputs their requirements for a 1LDK apartment with a budget of 20 million yen and a steel-reinforced concrete structure into the terminal.

[2121] 2. Blueprint generation: The server receives the requested data and creates the optimal blueprint using the generation AI.

[2122] 3. Entering modifications: The user checks the blueprint and enters modifications such as "changing the window position" or "making the living room larger."

[2123] 4. Regenerate: The server generates a new blueprint that reflects the modifications.

[2124] Example prompt sentence:

[2125] "Control the 3D printer based on this blueprint and create the required parts."

[2126] "The basic requirements are 'a 2LDK with a spacious living room, a budget of 30 million yen, and a wooden building.' Please generate the optimal design based on this and go through the process of manufacturing the parts."

[2127] In this way, the present invention makes it possible to realize a house design that quickly and accurately reflects the user's requests, and to efficiently build a high-quality house.

[2128] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2129] Step 1:

[2130] The user inputs basic housing requirements.

[2131] Specifically, users use a device such as a computer or smartphone to input information such as the house's layout, budget, and materials used into a dedicated interface. This interface is designed based on prompts from the generative AI model, allowing for intuitive input.

[2132] Input: Basic housing requirements (floor plan, budget, materials used, etc.)

[2133] Output: Request data

[2134] Step 2:

[2135] The terminal transmits the requested data to the server.

[2136] The input request data is transmitted from the terminal to the server, which then receives the user's request.

[2137] Input: Request data

[2138] Output: Sends the requested data to the server

[2139] Step 3:

[2140] The server receives the requested data and generates a house blueprint using generation AI.

[2141] The server analyzes the received request data and activates a generative AI model to generate blueprints that comply with the Building Standards Act. The generative AI model uses pre-trained data to create optimal blueprints.

[2142] Input: Request data

[2143] Output: Generated house plan

[2144] Step 4:

[2145] The server sends the generated design drawings to the user's device.

[2146] The generated blueprints are sent from the server to the user's device, where the user can view them on the device screen.

[2147] Input: Generated house plan

[2148] Output: Sending the blueprint to the user's device

[2149] Step 5:

[2150] The user checks the design drawings and inputs requests for corrections as necessary.

[2151] The user checks the blueprint and enters any requested modifications, such as "changing the position of a window" or "adding a balcony," into a dedicated interface.

[2152] Input: Initial blueprint

[2153] Output: Corrected data

[2154] Step 6:

[2155] The server receives the modified data from the user and regenerates the blueprint using the generation AI.

[2156] The server restarts the generative AI model based on the correction data received from the user and regenerates the blueprint, resulting in a final blueprint that meets the user's wishes.

[2157] Input: Correction data

[2158] Output: Regenerated blueprint

[2159] Step 7:

[2160] The server generates a construction plan and materials list based on the final design drawings and sends them to the manufacturing facility.

[2161] The server then creates a construction plan based on the final design drawings, generating a materials list, which includes the order of steps and deadlines, and the materials list includes the specific types and quantities of materials required. This data is then sent to the manufacturing facility.

[2162] Input: Regenerated blueprint

[2163] Output: Creation and transmission of construction plans and material lists

[2164] Step 8:

[2165] A manufacturing facility will use 3D printers to create the components for the home.

[2166] The manufacturing facility uses 3D printers to create the components of the home based on the construction plans and materials list submitted.

[2167] Input: Construction plan and materials list

[2168] Output: Produced parts

[2169] Step 9:

[2170] Control the quality of manufactured parts.

[2171] The manufacturing facility's artificial intelligence-controlled quality control measures are used to automatically check the quality of the parts produced, and any parts that fail are remanufactured.

[2172] Input: Produced parts

[2173] Output: Quality controlled parts

[2174] Step 10:

[2175] The manufactured parts are transported to the site, and the construction team assembles the house.

[2176] Once quality control is complete, the parts are transported to the site, where the construction team quickly assembles the house according to the construction plan provided by the server, resulting in a high-quality home.

[2177] Input: Quality-controlled parts, construction plans

[2178] Output: Completed house

[2179] 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.

[2180] The present invention combines an emotion engine with a system in which a user inputs basic housing requirements, uses AI to generate blueprints, and then quickly carries out construction. A specific embodiment of this system is described below.

[2181] 1. Inputting user requirements and generating design drawings

[2182] User inputs request

[2183] Users use the device to input their basic housing requirements, including the layout, budget, materials to be used, etc. The system also has a built-in emotion engine that recognizes the user's emotions in real time.

[2184] Receipt and analysis of requested data by the server

[2185] The request data sent from the device is sent to the server. The server analyzes the received request data and uses an emotion engine to determine the user's emotional state. Based on this information, the generation AI generates a blueprint, but the design content is adjusted according to the user's emotional response.

[2186] 2. Check and correct the design drawings

[2187] The server sends the blueprint

[2188] The generated blueprint is sent from the server to the user's device. When the user checks the blueprint on their device, the emotion engine monitors the user's reaction. For example, the user's emotional state (joy, anxiety, etc.) is analyzed in real time.

[2189] User enters corrections

[2190] When the user checks the blueprint and inputs corrections, the emotion engine is also running, and suggestions based on the user's emotional state (e.g., automatic corrections for stressful parts) can be made. The corrections are then sent to the server.

[2191] Server Regeneration

[2192] The server restarts the generation AI based on the correction data and information from the emotion engine, and regenerates the blueprint, resulting in a blueprint that optimally reflects the user's wishes and emotional state.

[2193] 3. Generate construction plans and material lists

[2194] The server creates a construction plan

[2195] The server then uses the final design and data from the emotion engine to create a detailed construction plan, including the order of steps, deadlines, and considerations related to the user's emotional state.

[2196] The server generates the material list

[2197] The server may generate a list of materials required for construction and select materials according to the user's preferences based on data from the emotion engine.

[2198] Sending to partner factories

[2199] The generated construction plan and materials list are sent from the server to a partner factory, where production can proceed taking into account the emotion engine data.

[2200] 4. 3D printed parts production and assembly

[2201] In-factory production

[2202] The partner factory uses 3D printers to produce each part of the house based on a materials list. The parts are inspected under strict quality control, and the emotion engine data is also used as a reference for production.

[2203] Parts transportation and on-site assembly

[2204] The manufactured parts are transported to the construction site. The construction team quickly assembles the parts to complete the house according to a construction plan that includes feedback from the emotion engine. For example, based on user emotion data, the system can incorporate ideas to minimize stress on-site.

[2205] Specific examples

[2206] For example, if a newlywed couple wants a one-bedroom, one-room apartment, the process would proceed as follows:

[2207] 1. User inputs request

[2208] A newlywed couple inputs their requirements for a one-bedroom apartment with a budget of 20 million yen and a steel-reinforced concrete structure into a terminal. The emotion engine recognizes their emotions as they type.

[2209] 2. The server creates the blueprint

[2210] The server receives the request data and emotion data, and uses generative AI to create the optimal design.

[2211] 3. User makes corrections

[2212] Check the blueprint and input modifications such as "change the window position" or "make the living room larger." The emotion engine simultaneously monitors the response.

[2213] 4. The server regenerates

[2214] Generate a new blueprint that reflects the modifications and confirm it.

[2215] 5. Generate construction plans and material lists

[2216] Based on the finalized drawings and emotion data, a construction plan and materials list are generated and sent to the factory.

[2217] 6. Manufacturing parts in factories

[2218] Parts are manufactured using 3D printers, and quality and emotional data are managed.

[2219] 7. On-site assembly

[2220] The parts are transported to the site, and the construction team quickly assembles them while taking into account the emotional data to complete the home.

[2221] The above is a ...

Claims

1. an input means for a user to input basic housing requirements; a transmitting means for transmitting user request data to a server; A generation means for receiving the requested data and generating a house design drawing that complies with the Building Standards Act using a generation AI; a transmitting means for transmitting the generated house design plan to a user's terminal; A regeneration means for receiving correction data from a user and readjusting the design using a generation AI; A generating means for generating a construction plan and a material list based on the final design drawing and transmitting them to the factory; A production method for producing housing components using a 3D printer based on a materials list generated in a factory; an assembly means for transporting the manufactured components to the site and for the construction team to assemble the house; A system including:

2. The system of claim 1, wherein the generating AI takes into account regulations for compliance with building standards when generating a residential blueprint.

3. 2. The system according to claim 1, wherein the terminal for the user to input desired data has a dedicated interface for inputting the layout of the house, the budget, the materials to be used, etc.

4. 2. The system according to claim 1, wherein the server automatically performs a series of processes from generating a house design drawing to generating a construction plan and a material list.

5. The system according to claim 1, wherein the subcontract factory uses a 3D printer to manufacture parts based on the design drawings and material list received from the server.

6. The system of claim 1 further comprising a means for transporting the produced parts to a site and coordinating them to allow a construction team to quickly assemble the house.

7. The system according to claim 1, wherein an individually customized construction plan is generated based on input desired data.

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