System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining user information; means for using a generation AI to generate a planning plan based on the obtained user information; means for recommending a vendor based on the generated planning plan; means for providing a virtual reality experience using virtual reality technology; and means for transparently managing building progress and cost information.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] This invention provides a system that allows ordinary people with little knowledge of architecture to easily design and build the home that best suits them. In the traditional construction industry, information is often opaque, and costs are often high, making it difficult for ordinary people to build the home that best suits them. Therefore, a system that increases transparency and is easy for users to use is needed. [Means for solving the problem]

[0005] The present invention solves the above problems with a system including a means for acquiring user information, a means for using a generation AI to generate design plans based on the acquired user information, a means for recommending specialist contractors based on the generated design plans, a means for providing a virtual building experience using virtual reality technology, and a means for transparently managing information on the construction process and costs. Furthermore, the system includes a means for displaying the generated design plans and a means for displaying a list of recommended specialist contractors so that the user can select, allowing the user to easily design and build the home that best suits them.

[0006] "User Information" refers to personal information necessary for home design and construction, such as the user's family composition, budget, and preferences.

[0007] "Generative AI" refers to algorithms or programs that use artificial intelligence technology to generate home design plans based on user information.

[0008] "Professional contractors" are those who provide services such as home design, construction, renovation, cleaning, repairs, and electrical work.

[0009] "Virtual reality technology" is a technology that uses computer technology to generate a virtual 3D space, allowing users to experience it as if it were real.

[0010] "Virtual architectural experience" is a process that allows users to experience design plans generated using virtual reality technology.

[0011] The "construction process" refers to the entire process from creating a design plan to the actual construction work and completion.

[0012] "Transparent management tools" are systems and functions that provide users with real-time updates on construction process and costs.

[0013] "Display means" refers to a system or function that visually presents the generated design plans, lists of specialist contractors, etc. through a user interface. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] This is a system that allows users to easily design and build custom homes. The system starts by collecting user information, then generates design plans using generative AI, recommends professional contractors, provides a virtual building experience, and transparently manages the construction process and costs to provide users with the perfect home.

[0036] Retrieving User Information

[0037] The server authenticates users when they access the platform and provides them with a login form. After logging in, users are provided with a form to enter basic information such as family composition, budget, and housing preferences. Users enter the required information into the indicated form and submit it to the server, which then securely stores the submitted information in a database.

[0038] Design proposals using generative AI

[0039] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[0040] Professional recommendation

[0041] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[0042] Providing a virtual architectural experience

[0043] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides an access link to the VR environment to the user's device, allowing the user to experience the designed home in virtual space through the link.

[0044] Transparent Management

[0045] The server constantly updates the construction progress and cost details and displays them in real time through the user interface. Users can check the progress and costs through the interface provided, ensuring transparency of the construction process and costs.

[0046] summary

[0047] The system of the present invention allows users to easily design and build the home that best suits them by linking the processes of acquiring user information, providing design suggestions using generative AI, recommending professional contractors, providing a virtual building experience, and transparently managing the building process and costs. This system allows users to realize a home that meets their needs without experiencing the opacity of the building industry.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] The server authenticates the user when they access the platform and provides a login form. If the user successfully logs in, the server displays a form for entering user information.

[0051] Step 2:

[0052] The user fills in the form with basic information such as family composition, budget, housing preferences, etc. Once the information is complete, the user presses the "Submit" button to send the information to the server.

[0053] Step 3:

[0054] The server receives the information sent by the user, stores it in a database, and then sends a request to the generation AI to create a plan.

[0055] Step 4:

[0056] The generation AI analyzes the received user information, generates multiple home design plans based on the user's preferences and budget, and returns the generated design plans to the server.

[0057] Step 5:

[0058] The server presents the design plans returned by the generation AI to the user, who then selects one of the plans.

[0059] Step 6:

[0060] The server sends a request to the generation AI to recommend the most suitable specialist based on the design plan selected by the user.

[0061] Step 7:

[0062] The generation AI analyzes the area, budget, ratings, etc., and generates a list of the most suitable specialist contractors that correspond to the selected design plan. The generated contractor list is returned to the server.

[0063] Step 8:

[0064] The server presents the list of vendors returned by the generation AI to the user, who then selects a vendor from the list based on their preferences and reliability.

[0065] Step 9:

[0066] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space.

[0067] Step 10:

[0068] The VR module generates a 3D model based on the design plan, creates a virtual environment, and returns an access link to the virtual environment to the server.

[0069] Step 11:

[0070] The server provides users with an access link to the VR environment, through which they can experience the designed house in a virtual space.

[0071] Step 12:

[0072] The server constantly updates the construction progress and cost details and displays them on the user interface, allowing users to check the progress and costs in real time and maintaining transparency of the construction process and costs.

[0073] Example 1

[0074] 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."

[0075] In the traditional home design and construction process, users must go through complicated procedures, making it difficult to select the right design and contractor without specialized knowledge. Furthermore, the construction process and costs are not transparent, making it difficult for users to track the progress and manage costs of a construction project. For these reasons, there is a demand for a system that allows users to design and build custom homes easily and smoothly.

[0076] 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.

[0077] In this invention, the server includes means for acquiring user information, means for using a generation AI to generate a design plan based on the acquired user information, means for sending a design plan creation request to the generation AI, means for presenting the generated design plan to the user, means for recommending a professional contractor based on the generated design plan, means for presenting a list of recommended contractors to the user, means for providing a virtual construction experience using virtual reality technology, and means for transparently managing information on the construction process and costs. This allows users to obtain optimal design and construction plans even without specialized knowledge, and enables transparent and real-time management of the construction process and costs.

[0078] "Means for obtaining user information" refers to a function for collecting personal information, family composition, budget, housing preferences, etc. provided by the user.

[0079] "Means of using generation AI to generate design plans based on acquired user information" refers to a function that uses generation AI to automatically create optimal home design plans based on information obtained from the user.

[0080] The "means for sending a design plan creation request to the generation AI" is a function that generates a prompt message based on user information to request the generation AI to create a design plan, and sends this message.

[0081] "Means for presenting the generated design plan to the user" refers to a function that displays and proposes the design plan created by the generation AI to the user.

[0082] The "means for recommending specialist contractors based on the generated design plan" is a function that selects and recommends specialist contractors that are suitable for the user's area and budget in accordance with the optimal design plan.

[0083] "Means for presenting a list of recommended contractors to the user" refers to a function that displays a list of multiple specialist contractors selected by the generation AI to the user, allowing them to make a selection.

[0084] "Means for providing a virtual architectural experience using virtual reality technology" refers to a function that reproduces the generated design plan as a 3D model, allowing users to experience a home in a virtual reality environment.

[0085] "A means for transparently managing information on construction processes and costs" is a management function that updates the progress and cost details of construction projects in real time, allowing users to easily check this information.

[0086] This is a system that allows users to easily design and build custom homes. The system starts by collecting user information, then generates design plans using generative AI, recommends professional contractors, provides a virtual building experience, and transparently manages the construction process and costs to provide users with the perfect home.

[0087] Retrieving User Information

[0088] The server authenticates users when they access the platform and provides them with a login form. For authentication, Firebase Authentication, a common authentication system, is used. After logging in, users are given a form to enter basic information such as family composition, budget, and housing preferences, which they then enter and send to the server. After receiving the information, the server securely stores it in a database (e.g., Amazon RDS).

[0089] Examples:

[0090] The user enters "Family composition: 4 people, Budget: 30 million yen, Preferences: Modern" into the form and submits it.

[0091] Design proposals using generative AI

[0092] The server generates a prompt sentence based on the acquired user information to send to the generation AI a request to create a design plan. For example, the generated prompt sentence might be, "Please generate a modern house design plan for a family of four with a budget of 30 million yen." The server sends this to a generative AI model (e.g., OpenAI GPT-4). The generation AI generates the optimal house design plan based on the user's preferences and budget and returns it to the server. The server presents the generated design plan to the user, displaying it in a selectable format.

[0093] Example prompt sentence:

[0094] "Generate a modern home design plan for a family of four with a budget of 30 million yen."

[0095] Professional recommendation

[0096] The user selects their preferred plan from the presented design plans. Based on the selected design plan, the server sends a request to the generation AI to recommend the most suitable specialist contractor. The generation AI considers conditions such as budget, region, and reputation, generates a list of the most suitable contractors, and returns it to the server. The server presents the list of recommended contractors to the user, allowing the user to make a selection.

[0097] Examples:

[0098] After the user selects "4LDK with modern design," the generating AI creates a list of highly rated specialist contractors in Tokyo and returns this to the server.

[0099] Providing a virtual architectural experience

[0100] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan using software such as Unity and creates a virtual environment. The server provides the user's device with an access link to the VR environment, allowing the user to experience the designed home in virtual space through the link.

[0101] Examples:

[0102] The user accesses the link provided by the server on their Oculus Quest 2 and tours the designed home in a virtual environment.

[0103] Transparent Management

[0104] The server operates a system to constantly update the progress and cost details of the construction process. For this, a management system is built using Python and Django. The server displays this information to users in real time through a user interface. Users can check the progress and costs through the interface provided, maintaining transparency of the construction process and costs.

[0105] Examples:

[0106] The user checks details on the dashboard, such as "Current phase: foundation work, progress rate: 60%, cumulative cost: 18 million yen."

[0107] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0108] Step 1:

[0109] Retrieving User Information

[0110] The server authenticates users when they access the platform and provides them with a login form. The user enters their login information into the form and sends it to the server. The server receives it and authenticates them using Firebase Authentication. If authentication is successful, it displays a form for entering user information. The user enters information such as family composition, budget, and housing preferences and sends it to the server. The server stores the received information in an Amazon RDS database.

[0111] Input: User login information, personal information form (family composition, budget, preferences, etc.)

[0112] Output: Authentication result, message that saving to database is complete

[0113] Specific operation: The user enters "User name: user123, Password: pass123, Family composition: 4 people, Budget: 30 million yen, Preferences: Modern" into the form and submits it.

[0114] Step 2:

[0115] Design proposals using generative AI

[0116] The server generates a prompt based on the acquired user information to send a request to the generative AI to create a design plan. The server then sends this prompt to a generative AI model (e.g., OpenAI GPT-4). The generative AI generates an optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plan to the user.

[0117] Input: User information (family structure, budget, preferences, etc.), prompt text

[0118] Output: Generated design plan

[0119] Specific operation: The server generates a prompt sentence, "Please generate a modern house design plan for a family of four with a budget of 30 million yen," and sends it to the generation AI. The generation AI generates a plan proposing a modern design for a 4LDK and returns it to the server.

[0120] Step 3:

[0121] Professional recommendation

[0122] After the user selects their preferred plan from the presented design plans, the server sends a request to the generation AI to recommend the most suitable specialist contractors, including local information, based on the selected design plan. The generation AI considers conditions such as budget, area, and reputation, generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user.

[0123] Input: Selected design plan, local information

[0124] Output: A list of specialists

[0125] Specific operation: After the user selects "4LDK with modern design," the server uses that information to request highly rated specialist contractors in Tokyo with a budget of 30 million yen or less from the generation AI, and presents the generated contractor list to the user.

[0126] Step 4:

[0127] Providing a virtual architectural experience

[0128] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides an access link to the VR environment to the user's device, allowing the user to experience the designed home in virtual space through the link.

[0129] Input: Generated design plan

[0130] Output: VR environment link

[0131] Specific operation: The user accesses the link provided by the server on Oculus Quest 2 and tours the designed home in a virtual environment.

[0132] Step 5:

[0133] Transparent Management

[0134] The server operates a system to constantly update the construction progress and cost details. The management system is built using Python and Django. The server displays this information to users in real time through a user interface. Users can check the progress and costs through the interface provided, maintaining transparency of the construction process and costs.

[0135] Input: Construction progress information, cost information

[0136] Output: Real-time progress and cost information

[0137] Specific operation: The user checks details on the dashboard, such as "Current phase: foundation work, progress rate: 60%, cumulative cost: 18 million yen."

[0138] (Application example 1)

[0139] 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."

[0140] Conventional home design systems required extensive specialized knowledge for users to design their ideal home, and checking and correcting design plans required a lot of time and money. Furthermore, it was difficult to fully experience the real world, and virtual environments were limited in scope. Furthermore, transparency of the process and costs from design to construction was often lacking, reducing user satisfaction.

[0141] 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.

[0142] In this invention, the server includes a means for acquiring user information, a means for using a generation AI to generate a design plan based on the acquired user information, a VR module that is a means for displaying the generated design plan as a 3D model using virtual reality technology, a means for using a generation AI to recommend a professional contractor based on the generated design plan, a means for providing a virtual construction experience using virtual reality technology, a means for transparently managing information on the construction process and costs, a means for acquiring user location information using a location identification device, and a means for displaying information using smart glasses. This allows users without specialized knowledge to easily create an optimal home design and enjoy a detailed virtual experience in real time, ensuring transparency of the process and costs from design to construction.

[0143] "User information" refers to basic information such as the user's family structure, budget, and housing preferences.

[0144] "Design plans" refer to the blueprints and layouts of homes generated based on the user's preferences and budget.

[0145] "Generative AI" is an artificial intelligence system that generates optimal design plans based on user information.

[0146] The "VR Module" is a system that uses virtual reality technology to display design plans as 3D models, providing users with a virtual architectural experience.

[0147] "Recommending specialists" refers to the process by which the generative AI selects and recommends the most suitable specialists based on the user's design plan.

[0148] "Virtual architectural experience" refers to the process of allowing users to experience generated design plans in a virtual reality environment.

[0149] "Transparent management" means providing users with real-time updates on the construction process and costs.

[0150] "Location-determining device" refers to a device used to obtain a user's location information.

[0151] "Smart glasses" are wearable devices for displaying information and providing visual feedback to users.

[0152] This invention is a system that allows users to easily design and build custom homes, and includes the following processes:

[0153] Retrieving User Information

[0154] The server authenticates users when they access the platform and provides them with a login form. After logging in, users are provided with a form to enter basic information such as family composition, budget, and housing preferences. Users enter the required information into the indicated form and submit it to the server, which then securely stores the submitted information in a database.

[0155] Generate design plans

[0156] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[0157] Virtual reality experience

[0158] The server passes the design plan created by the generative AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides the user's device with an access link to the VR environment, allowing the user to experience the designed home in virtual space through the link.

[0159] Professional recommendation

[0160] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[0161] Transparent Management

[0162] The server constantly updates the progress and cost details of the construction process and displays them in real time through the user interface. Users can check the progress and costs through the interface provided, ensuring transparency of the construction process and costs.

[0163] Using smart glasses

[0164] Furthermore, smart glasses can be used to visually display information, allowing users to check design plans and experience them virtually on the spot by using the smart glasses installed in showrooms and stores.

[0165] Use of location-specific devices

[0166] By using location-specific devices to obtain user location information, the in-store experience can be improved in real time, and optimal information can be provided based on the user's movement.

[0167] Examples and prompts

[0168] For example, in a scenario where a user visiting a housing exhibition puts on smart glasses and designs a custom home on the spot, the following prompt is generated based on the information entered by the user:

[0169] Family composition: 4 people

[0170] Budget: 50,000,000 yen

[0171] Style: Modern

[0172] Number of rooms: 3

[0173] Use this information to generate the best home design plans.

[0174] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0175] Step 1:

[0176] When a user accesses the platform, the server sends an authentication request. The user enters information into the login form and completes authentication. The input data is a username and password, and the server compares this with the database as authentication information and returns the authentication result. The output is the authentication result (success / failure).

[0177] Step 2:

[0178] The server provides a form for users who have been successfully authenticated to enter basic information such as family composition, budget, and housing preferences. The user enters the information into this form and sends it to the server. The input data, such as family composition, budget, and preferred style, is securely stored in a database by the server. The output is a confirmation that the user information has been saved.

[0179] Step 3:

[0180] The server generates a prompt sentence based on the saved user information. Using the generated prompt sentence, it sends a design plan generation request to the generation AI. The input data is user information, which is converted into a prompt sentence generated by the server and sent to the generation AI. The output is a confirmation that the design plan generation request has been sent.

[0181] Step 4:

[0182] The generation AI generates a house design plan based on the received prompt and returns it to the server. The input data is the prompt, and the generation AI analyzes this prompt to generate a design plan. The output is the design plan, which is sent back to the server.

[0183] Step 5:

[0184] The server passes the generated design plan to the VR module and sends a request to display it as a 3D model. The input data is the design plan, which the server sends to the VR module. The output is a confirmation of the sending of the 3D model generation request.

[0185] Step 6:

[0186] The VR module creates a virtual environment based on the design plan and returns a link to the server that can be accessed on the user's device. The input data is the design plan, which the VR module converts into a 3D model. The output is a link to access the virtual environment.

[0187] Step 7:

[0188] The server provides the user with an access link to the virtual environment, through which the user experiences the designed house in the virtual space. The input data is the virtual environment access link, which the user uses to perform the virtual experience. The output is the user's experience information.

[0189] Step 8:

[0190] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable specialist. The input data is the design plan, which the server sends to the generation AI. The output is a confirmation of the submission of the specialist recommendation request.

[0191] Step 9:

[0192] The generation AI analyzes the region, budget, ratings, etc., and generates a list of the most suitable contractors, which it returns to the server. The input data is the design plan and contractor information, which the generation AI analyzes. The output is a list of recommended contractors.

[0193] Step 10:

[0194] The server provides the user with a list of recommended vendors, from which the user can select the vendor that best suits them. The input data is the list of recommended vendors, which the server displays to the user. The output is the user's selection of vendors.

[0195] Step 11:

[0196] The server updates the progress and cost details of the construction process and displays them in real time through the user interface. The input data is the progress and cost details of the construction process, which the server records in a database and provides to the user. The output is a display of the progress and cost information.

[0197] Step 12:

[0198] The user checks the progress and costs through the provided interface. The input data are the details of the progress and costs provided by the server, which the user can view. The output is the confirmation result.

[0199] 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.

[0200] This is a system that allows users to easily design and build custom homes, and in particular, incorporates an emotion engine to provide optimal design plans and services that take user emotions into consideration. This system includes the processes of acquiring user information, generating design plans using AI, recommending professional contractors, providing a virtual building experience, and transparently managing the construction process and costs.

[0201] Retrieving User Information

[0202] The server authenticates users when they access the platform and provides them with a login form. If the user successfully logs in, a form is displayed for them to enter basic information such as their family composition, budget, and housing preferences. The user enters the required information into the form and submits it to the server, which stores the submitted information in a database.

[0203] Design proposals using generative AI

[0204] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[0205] Professional recommendation

[0206] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[0207] Implementing the Emotion Engine

[0208] The server uses an emotion engine to recognize users' emotions in real time as they select design plans or engage in virtual building experiences. The emotion engine analyzes users' emotions using facial recognition, voice analysis, and other technologies, and feeds the results back to the generative AI and other system components.

[0209] Providing a virtual architectural experience

[0210] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in a virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides the user with an access link to the VR environment. The user experiences the designed house in a virtual space through the link.

[0211] Feedback combined with emotion engine

[0212] The emotion engine recognizes users' emotions in real time during the virtual building experience and provides that data to the generative AI. The generative AI can then use this feedback to adjust the design plan. For example, if a user expresses positive emotions about a design plan, the system will generate a plan that emphasizes those elements. If a user expresses negative emotions, the system will generate a plan to improve those elements.

[0213] Transparent management and support

[0214] The server constantly updates the progress and cost details of the construction process and displays them on the user interface. Users can check the progress and costs in real time and communicate with the builder if necessary. In addition, the emotion engine recognizes the user's emotions during this process and provides appropriate assistance and alerts.

[0215] summary

[0216] The system of this invention allows users to easily design and build their ideal home by combining user information acquisition, design suggestions using generative AI, recommendation of professional contractors, provision of a virtual building experience incorporating an emotion engine, and transparent management of the building process and costs. This system will eliminate opacity in the building industry and increase user satisfaction and peace of mind.

[0217] The processing flow will be explained below.

[0218] Step 1:

[0219] The server authenticates users when they access the platform and provides them with a login form. If the user successfully logs in, they are presented with a form to enter basic information such as family composition, budget, and housing preferences.

[0220] Step 2:

[0221] The user enters the necessary information into the displayed form and sends it to the server. For example, the user might enter "family of four" as the family composition, "50 million yen" as the budget, and "modern style" as the preference.

[0222] Step 3:

[0223] The server receives the information sent by the user, stores it in a database, and then sends a request to the generation AI to create a plan.

[0224] Step 4:

[0225] The generation AI analyzes the received user information and generates multiple home design plans based on the user's preferences and budget. The generated design plans are then returned to the server. For example, it generates three modern-style design plans and sends that information to the server.

[0226] Step 5:

[0227] The server presents the design plans returned by the generation AI to the user, who then selects one of the plans. At this time, details and images of the design plan are also displayed.

[0228] Step 6:

[0229] The server sends a request to the generation AI to recommend the most suitable specialist based on the design plan selected by the user.

[0230] Step 7:

[0231] The Generative AI analyzes the area, budget, and ratings to generate a list of the most suitable professional contractors for the selected design plan. For example, it selects three contractors based on the user's area, budget, and past ratings. The generated contractor list is then returned to the server.

[0232] Step 8:

[0233] The server presents the list of vendors returned by the AI ​​to the user, who then selects the vendor that best suits them. The list also includes detailed information and ratings for each vendor.

[0234] Step 9:

[0235] The server uses an emotion engine to recognize the user's emotions in real time based on the design plan and professional contractor information selected by the user, and this information is fed back to the generative AI.

[0236] Step 10:

[0237] The emotion engine analyzes emotions from facial expressions and voice when a user selects a design plan or browses a list of contractors, and sends the data to a server. For example, if a user smiles while looking at a plan, it determines that the emotion is positive.

[0238] Step 11:

[0239] Based on the feedback data from the emotion engine, the server asks the generative AI to adjust the design plan, for example, to generate a new plan that emphasizes elements that have been identified as generating positive emotions.

[0240] Step 12:

[0241] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space.

[0242] Step 13:

[0243] The VR module generates a 3D model based on the design plan, creates a virtual environment, and returns an access link to the virtual environment to the server.

[0244] Step 14:

[0245] The server provides users with an access link to the VR environment, through which they can experience the designed house in a virtual space.

[0246] Step 15:

[0247] The server constantly updates the progress and cost details of the construction process and displays them on the user interface. Users can check the progress and costs in real time and communicate with the builder if necessary. In addition, the emotion engine recognizes the user's emotions during this process and provides appropriate assistance and alerts.

[0248] Example 2

[0249] 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."

[0250] Conventional custom home design and construction systems have difficulty providing design plans that adequately reflect the complex needs and feelings of users. Furthermore, because individual processes such as proposing design plans, recommending specialist contractors, and providing virtual construction experiences are not integrated, the process is cumbersome and opaque for users. Furthermore, the lack of transparency in the management of the construction process and costs has led to a lack of security for users.

[0251] 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.

[0252] In this invention, the server includes means for acquiring user information, means for using artificial intelligence to generate a design plan based on the acquired user information, means for recommending a contractor based on the generated design plan, means for recognizing the user's emotions using an emotion engine and providing feedback based on the emotions, means for providing a virtual construction experience using virtual reality technology, and means for transparently managing information on the construction process and costs. This makes it possible to provide a design plan that reflects the user's emotions and needs, recommend the most suitable contractor, provide a virtual construction experience using real-time emotion feedback, and transparently manage the construction process and costs.

[0253] "User Information" refers to personal information about a User, such as family composition, budget, and housing preferences, that is necessary for the design and construction of a custom home.

[0254] "Artificial intelligence" refers to digital technology that uses machine learning and deep learning techniques to generate optimal home design plans based on user information.

[0255] "Specialist contractors" refer to the craftsmen and companies that actually carry out the construction and installation in the design and building of custom homes.

[0256] An "emotion engine" refers to technology that recognizes and analyzes the emotions of users in real time when using a system.

[0257] "Virtual reality technology" is a technology that provides an experience close to the real world in a digital space, and is used to allow users to experience a house before it is built in a virtual space.

[0258] "Virtual architectural experience" refers to the use of virtual reality technology to allow users to experience a home designed in a digital space in real time.

[0259] "Transparent information management" means providing users with real-time details about the construction process and costs, and sharing the latest information at all times, eliminating any opacity for users.

[0260] This is a system that allows users to easily design and build custom homes, and in particular, incorporates an emotion engine to provide optimal design plans and services that take user emotions into consideration. This system includes the processes of acquiring user information, generating design plans using AI, recommending professional contractors, providing a virtual building experience, and transparently managing the construction process and costs.

[0261] First, the server authenticates the user when they access the platform and provides them with a login form. If the user successfully logs in, a form is displayed for them to enter basic information such as their family composition, budget, and housing preferences. The user enters this information and sends it to the server. The server stores the submitted information in a database. This process uses a relational database management system such as the MySQL database.

[0262] Next, the server requests the generation AI to generate a design plan based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one. The generation AI uses models such as GPT-3 that use deep learning technology.

[0263] Once the user selects a design plan, the server sends a request to the generation AI to recommend the most suitable specialist contractor. The generation AI analyzes the area, budget, and evaluation data, generates a list of the most suitable contractors, and returns it to the server. The server then presents this list to the user, who can then select the contractor that best suits them.

[0264] When selecting a design plan or experiencing a virtual building, the server uses an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotions using facial recognition technology (e.g., OpenCV) and voice analysis technology. This emotion data is fed back to the generative AI and other system components.

[0265] To provide a virtual architectural experience, the server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in a virtual space. The VR module generates a 3D model based on the design plan using a 3D game engine such as Unity, creating a virtual environment. The server provides the user with an access link to the VR environment, allowing the user to experience the designed house in the virtual space through the link.

[0266] Furthermore, the server updates the progress and cost details of the construction process in real time and displays them on the user interface. Users can check this and communicate with the builder if necessary. The emotion engine recognizes the user's emotions during the construction process and provides appropriate assistance and alerts.

[0267] Prompt Sentence Examples

[0268] User information: Family composition (couple and two children), budget (50 million yen), housing preferences (modern, spacious kitchen)

[0269] Generate the best home design plan based on the user information above.

[0270] In this way, the system can provide design plans that reflect the user's emotions and needs, recommend professional contractors, provide a virtual building experience with real-time emotional feedback, and transparently manage the construction process and costs.

[0271] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0272] Step 1: Get user information

[0273] 1. The server initiates the authentication process when the user accesses the platform and displays a login form.

[0274] Input: User ID, Password

[0275] Output: Authentication result (success / failure), form display status

[0276] Specific behavior: Validates the authentication information and displays the next input form if the user successfully logs in.

[0277] 2. The user enters the required information into the login form and presses the submit button.

[0278] Input: User ID, Password

[0279] Output: User authentication request

[0280] Specific operation: Sends authentication information to the server.

[0281] 3. The server verifies the authentication information entered and, if successful, displays a form for entering basic information such as family composition, budget, and housing preferences.

[0282] Input: User authentication request

[0283] Output: User information input form

[0284] Specific operation: Check the database and dynamically generate the next form depending on the authentication result.

[0285] 4. The user enters basic information and presses the send button.

[0286] Inputs: Family composition, budget, housing preferences

[0287] Output: User information request

[0288] Specific operation: Send basic information to the server.

[0289] 5. The server stores the entered user information in a database.

[0290] Input: User Information Request

[0291] Output: Status of saving to database

[0292] What it does: Stores user information using a relational database management system such as a MySQL database.

[0293] Step 2: Generate a design plan

[0294] 1. The server requests the generation AI to generate a design plan based on the stored user information.

[0295] Input: User information

[0296] Output: Design plan generation request

[0297] Specific operation: A Python program is used to call the generative AI's API and send a prompt containing user information.

[0298] 2. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server.

[0299] Input: Design plan generation request

[0300] Output: Generated house design plan

[0301] Specific operation: Generate a design plan using deep learning technology (e.g., GPT-3).

[0302] 3. The server presents the generated design plans to the user for selection.

[0303] Input: Generated house design plan

[0304] Output: Present the design plan to the user

[0305] What it does: Display the design plan on a web page or application interface.

[0306] Step 3: Professional Recommendations

[0307] 1. The user selects one of the presented design plans.

[0308] Input: Multiple design plans

[0309] Output: Selected design plan

[0310] Specific behavior: Review the design plans and select the best one.

[0311] 2. The server sends a request to the generating AI to generate a list of the most suitable specialists based on the design plan information selected by the user.

[0312] Input: Selected design plan information

[0313] Output: Contractor selection request

[0314] Specific operation: Include vendor evaluation data in the prompt text sent to the generation AI.

[0315] 3. The generative AI analyzes the region, budget, and rating data to create a list of optimal contractors and return it to the server.

[0316] Input: Contractor selection request

[0317] Output: A list of the best specialists

[0318] Specific operation: Select the best vendor using a machine learning algorithm.

[0319] 4. The server presents this list of vendors to the user.

[0320] Input: List of best professional contractors

[0321] Output: Present a list of vendors to the user

[0322] What it does: Displays a list of vendors on a web page or application interface.

[0323] 5. The user selects the appropriate provider from the list.

[0324] Input: Professional Contractor List

[0325] Output: Selected vendor information

[0326] Specific actions: Check the vendor list and select the appropriate vendor.

[0327] Step 4: Implementing the Emotion Engine

[0328] 1. The server runs an emotion engine that recognizes the user's emotions in real time as they select design plans and engage in virtual architectural experiences.

[0329] Input: Real-time user data (face data, voice data)

[0330] Output: User emotion data

[0331] What it does: Captures real-time facial and audio data using a webcam and microphone.

[0332] 2. The emotion engine analyzes the user's facial recognition data and voice data to determine their emotional state.

[0333] Input: Real-time face data, voice data

[0334] Output: User emotion judgment result

[0335] Specific operation: Analyzes emotion data using OpenCV and speech analysis libraries.

[0336] 3. The server feeds this emotion data back to system components such as generative AI, triggering corresponding actions.

[0337] Input: User's emotion judgment result

[0338] Output: Feedback data, trigger actions

[0339] Specific behavior: Dynamically change the content of the user interface based on emotion data.

[0340] Step 5: Providing a virtual building experience

[0341] 1. The server passes the design plan created by the generation AI to the VR module and sends a request to reproduce it in virtual space.

[0342] Input: User design plan

[0343] Output: Virtual space generation request

[0344] Specific operation: Calls the API to send data to the VR module.

[0345] 2. The VR module generates a 3D model based on the design plan and creates a virtual environment.

[0346] Input: User design plan

[0347] Output: The generated virtual environment

[0348] Specific operation: Build a virtual environment using a 3D game engine such as Unity.

[0349] 3. The server provides the user with an access link to this VR environment.

[0350] Input: The generated virtual environment

[0351] Output: VR environment access link to user

[0352] What it does: Generates a link and sends it to the user's account.

[0353] 4. Users can experience the designed home in a virtual space via a VR headset or PC via the link.

[0354] Input: VR environment access link

[0355] Output: Virtual architectural experience

[0356] Specific action: Experience a virtual space using a VR device such as Oculus Rift or HTC Vive.

[0357] Step 6: Transparent management and support

[0358] 1. The server updates the construction progress and cost details in real time and displays them in the user interface.

[0359] Input: Construction process data, cost data

[0360] Output: Displaying progress and costs

[0361] Specific actions: Visualize progress and cost data using tools such as Google Charts.

[0362] 2. Users can view progress and cost details and communicate with the builder if necessary.

[0363] Input: View progress and costs

[0364] Output: User feedback and communication requests

[0365] What it does: Check progress and cost details, and send questions if you have any questions.

[0366] 3. The Emotion Engine recognizes users' emotions in real time during the construction process and provides appropriate assistance and alerts.

[0367] Input: Real-time user data (face data, voice data)

[0368] Output: Support message, alert notification

[0369] Specific behavior: Display appropriate motivational messages and alerts to users based on emotional data.

[0370] (Application example 2)

[0371] 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."

[0372] Conventional custom home design systems proposed plans based on the user's preferences and budget, but they lacked the ability to adjust design plans based on the user's emotions or optimize the design through a virtual construction experience. Therefore, a new proposal method was needed to increase user satisfaction. Furthermore, transparency in the design and construction processes was insufficient, making it difficult for users to collaborate with trusted contractors.

[0373] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user information, means for using a generation AI to generate a design plan based on the acquired user information, means for recommending a professional contractor based on the generated design plan, means for providing a virtual construction experience using virtual reality technology, means for transparently managing information on the construction process and costs, means for using an emotion engine to recognize the user's emotions in real time and adjust the design plan based on the results, means for experiencing a home designed in a virtual space based on the generated design plan, and means for providing feedback on the user's emotions during the virtual space experience and for the generation AI to optimize the design plan. This enables optimal proposals and adjustments that take the user's emotions into consideration, thereby improving user satisfaction. Furthermore, transparent management enhances user trust and enables smooth collaboration with contractors.

[0374] "User information" refers to basic information such as the user's family composition, budget, preferences, etc.

[0375] "Design plan" refers to a proposed house design based on user information.

[0376] "Generative AI" refers to artificial intelligence (AI) that creates design plans based on user information.

[0377] "Specialist contractor" refers to a contractor that carries out construction and installation based on a design plan.

[0378] "Virtual reality technology" refers to the technology of creating a virtual space that resembles reality using computer technology.

[0379] "Virtual architectural experience" refers to the use of virtual reality technology to allow users to experience the design of a home in a virtual space.

[0380] An "emotion engine" is an engine that uses technologies such as facial recognition and voice analysis to recognize and analyze users' emotions in real time.

[0381] "Cost information" refers to details of various costs and budgets incurred during the construction process.

[0382] "Transparent management" means presenting information to users clearly and in real time, eliminating opacity.

[0383] "Virtual space" refers to a three-dimensional digital space generated within a computer using virtual reality technology.

[0384] "Feedback" refers to collecting user emotional data and providing information to adjust design plans based on that data.

[0385] "Optimizing" refers to adjusting proposals and plans to the best possible state based on the user's feelings and desires.

[0386] The following system configuration is shown as an embodiment of this invention. The invention includes a generation AI that acquires user information and generates an optimal design plan based on it, recommendation of specialist contractors, a virtual building experience using virtual reality technology, real-time feedback by an emotion engine, and transparent management.

[0387] System Program

[0388] The system mainly consists of the following hardware and software:

[0389] User device: smartphone, tablet, or computer

[0390] Server: Cloud server (AWS, Google Cloud, etc.)

[0391] Generative AI models: Natural language processing models such as GPT-3 and Claude

[0392] Emotion engine: Emotion recognition software such as Affectiva SDK

[0393] AR Platform: Apple ARKit, Google ARCore

[0394] Retrieving User Information

[0395] Users log in to the app using their devices and enter basic information (family composition, budget, preferences, etc.). This information is sent from the user's device to the server, which then stores the received information in a cloud database.

[0396] Generative AI creates design plans

[0397] The server sends the saved user information to the generative AI model and requests it to generate an optimal design plan. The generative AI model generates a design plan that matches the user's preferences and budget and returns it to the server. The server displays this design plan to the user.

[0398] Professional recommendation

[0399] After the user selects a design plan, the server will ask the AI ​​to generate a list of the most suitable specialists based on factors such as area, budget, and reputation. This list will be presented to the user, who can then select the contractor that best suits them.

[0400] Feedback using an emotion engine

[0401] As users select a design plan and experience the virtual building process, their emotions are monitored in real time via the user's device's camera and microphone. The emotion engine analyzes the collected data and determines the user's emotions. The server sends the emotion engine's results to the generation AI, which adjusts the design plan based on the feedback. For example, if the user responds positively to a proposed design, a new plan is generated that emphasizes those elements.

[0402] Providing a virtual building experience and transparent management

[0403] The server sends the design plan created by the generative AI to the user's device via the AR platform, allowing them to experience the designed home in a virtual space. Users can virtually place the home using the AR function of their smartphone or tablet and check the feel of it in the real environment. In addition, transparent management of the construction process and costs allows users to check the project progress and costs in real time.

[0404] Examples of specific examples and prompts

[0405] For example, if a user attempts to arrange furniture in a virtual space and expresses their feelings about the arrangement, for example, "If I put a sofa here, it would feel more spacious," the generative AI will use that emotion data to suggest new furniture arrangements.

[0406] Example prompt sentence:

[0407] "A user looks at the proposed furniture arrangement and says, 'If I put a sofa here, it would feel even bigger.' Suggest a new furniture arrangement that reflects this."

[0408] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0409] Step 1:

[0410] Users log in to the application using their devices and enter basic information such as family composition, budget, and housing preferences into the login form. This information is sent from the user device to the server and stored in a cloud database.

[0411] Input: User's basic information (family structure, budget, preferences, etc.)

[0412] Output: User information stored in a cloud database

[0413] Specific operation: The user enters the required information into the form presented on the smartphone or tablet and presses the "Submit" button.

[0414] Step 2:

[0415] The server acquires user information and sends it to a generative AI model, which generates a design plan based on the user's preferences and budget and sends it back to the server.

[0416] Input: User information stored in a cloud database

[0417] Output: Design plans generated by the generative AI

[0418] Specific operation: The server sends an appropriate prompt to the generation AI, which processes the user's information to create the optimal design plan.

[0419] Step 3:

[0420] The server sends the design plans received from the generative AI model to the user's device and displays them to the user, who then checks the presented design plans and makes a selection.

[0421] Input: Design plan returned from the generative AI

[0422] Output: Design plan displayed on the user's device

[0423] Specific operation: The server generates the design plan in HTML format and displays it to the user through a web interface.

[0424] Step 4:

[0425] After the user selects a design plan, the server again sends a request to the generative AI model to recommend a specialist contractor. The generative AI model then lists the most suitable specialist contractors based on location, budget, reputation, etc., and sends the list back to the server.

[0426] Input: User selected design plan and user information

[0427] Output: A list of the best professionals

[0428] Specific operation: The server again sends the prompt sentence to the generation AI model, which generates a list of candidate specialists based on the design plan.

[0429] Step 5:

[0430] The server sends a list of specialists to the user terminal and displays it to the user, allowing the user to select from the list.

[0431] Input: A list of specialists returned by the generation AI

[0432] Output: A list of specialists displayed on the user's device

[0433] Specific operation: The user selects a suitable vendor from the presented list of vendors.

[0434] Step 6:

[0435] While reviewing design plans and experiencing the virtual world, the user's emotions are observed in real time using the camera and microphone on the user's device. The emotion engine analyzes this data and determines the user's emotions.

[0436] Input: User's facial expression and voice data

[0437] Output: Analyzed user emotion data

[0438] How it works: Using the smartphone's camera and microphone, the emotion engine analyzes this data to identify emotions.

[0439] Step 7:

[0440] The server sends the results of the emotion engine to the generative AI, which then adjusts the design plan, for example, highlighting design elements for which users expressed positive emotions and improving negative elements.

[0441] Input: Analyzed emotion data, user information

[0442] Output: New adjusted design plan

[0443] Specific operation: The server uses a prompt statement to ask the generation AI to create a new design plan.

[0444] Step 8:

[0445] The server sends the new design plan adjusted by the generative AI to the user's device via the AR platform, providing an experience in a virtual space.

[0446] Input: New design plan adjusted by the generative AI

[0447] Output: Virtual experience displayed on the user's device

[0448] Specific operation: The user uses the AR function of their smartphone to virtually experience new design plans.

[0449] Step 9:

[0450] The server manages the progress and costs of the construction process in real time and displays them on the user's device, allowing the user to constantly check the progress and costs of the project.

[0451] Input: Construction process and cost information

[0452] Output: Real-time progress and cost information displayed on the user's device

[0453] What it does: The server uses a project management tool to monitor progress and costs, and displays that information to the user in HTML format.

[0454] 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.

[0455] 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.

[0456] 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.

[0457] [Second embodiment]

[0458] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0459] 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.

[0460] 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).

[0461] 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.

[0462] 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.

[0463] 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).

[0464] 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. 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.

[0465] 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.

[0466] 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.

[0467] 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.

[0468] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0469] 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."

[0470] This is a system that allows users to easily design and build custom homes. The system starts by collecting user information, then generates design plans using generative AI, recommends professional contractors, provides a virtual building experience, and transparently manages the construction process and costs to provide users with the perfect home.

[0471] Retrieving User Information

[0472] The server authenticates users when they access the platform and provides them with a login form. After logging in, users are provided with a form to enter basic information such as family composition, budget, and housing preferences. Users enter the required information into the indicated form and submit it to the server, which then securely stores the submitted information in a database.

[0473] Design proposals using generative AI

[0474] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[0475] Professional recommendation

[0476] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[0477] Providing a virtual architectural experience

[0478] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides an access link to the VR environment to the user's device, allowing the user to experience the designed home in virtual space through the link.

[0479] Transparent Management

[0480] The server constantly updates the construction progress and cost details and displays them in real time through the user interface. Users can check the progress and costs through the interface provided, ensuring transparency of the construction process and costs.

[0481] summary

[0482] The system of the present invention allows users to easily design and build the home that best suits them by linking the processes of acquiring user information, providing design suggestions using generative AI, recommending professional contractors, providing a virtual building experience, and transparently managing the building process and costs. This system allows users to realize a home that meets their needs without experiencing the opacity of the building industry.

[0483] The processing flow will be explained below.

[0484] Step 1:

[0485] The server authenticates the user when they access the platform and provides a login form. If the user successfully logs in, the server displays a form for entering user information.

[0486] Step 2:

[0487] The user fills in the form with basic information such as family composition, budget, housing preferences, etc. Once the information is complete, the user presses the "Submit" button to send the information to the server.

[0488] Step 3:

[0489] The server receives the information sent by the user, stores it in a database, and then sends a request to the generation AI to create a plan.

[0490] Step 4:

[0491] The generation AI analyzes the received user information, generates multiple home design plans based on the user's preferences and budget, and returns the generated design plans to the server.

[0492] Step 5:

[0493] The server presents the design plans returned by the generation AI to the user, who then selects one of the plans.

[0494] Step 6:

[0495] The server sends a request to the generation AI to recommend the most suitable specialist based on the design plan selected by the user.

[0496] Step 7:

[0497] The generation AI analyzes the area, budget, ratings, etc., and generates a list of the most suitable specialist contractors that correspond to the selected design plan. The generated contractor list is returned to the server.

[0498] Step 8:

[0499] The server presents the list of vendors returned by the generation AI to the user, who then selects a vendor from the list based on their preferences and reliability.

[0500] Step 9:

[0501] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space.

[0502] Step 10:

[0503] The VR module generates a 3D model based on the design plan, creates a virtual environment, and returns an access link to the virtual environment to the server.

[0504] Step 11:

[0505] The server provides users with an access link to the VR environment, through which they can experience the designed house in a virtual space.

[0506] Step 12:

[0507] The server constantly updates the construction progress and cost details and displays them on the user interface, allowing users to check the progress and costs in real time and maintaining transparency of the construction process and costs.

[0508] Example 1

[0509] 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."

[0510] In the traditional home design and construction process, users must go through complicated procedures, making it difficult to select the right design and contractor without specialized knowledge. Furthermore, the construction process and costs are not transparent, making it difficult for users to track the progress and manage costs of a construction project. For these reasons, there is a demand for a system that allows users to design and build custom homes easily and smoothly.

[0511] 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.

[0512] In this invention, the server includes means for acquiring user information, means for using a generation AI to generate a design plan based on the acquired user information, means for sending a design plan creation request to the generation AI, means for presenting the generated design plan to the user, means for recommending a professional contractor based on the generated design plan, means for presenting a list of recommended contractors to the user, means for providing a virtual construction experience using virtual reality technology, and means for transparently managing information on the construction process and costs. This allows users to obtain optimal design and construction plans even without specialized knowledge, and enables transparent and real-time management of the construction process and costs.

[0513] "Means for obtaining user information" refers to a function for collecting personal information, family composition, budget, housing preferences, etc. provided by the user.

[0514] "Means of using generation AI to generate design plans based on acquired user information" refers to a function that uses generation AI to automatically create optimal home design plans based on information obtained from the user.

[0515] The "means for sending a design plan creation request to the generation AI" is a function that generates a prompt message based on user information to request the generation AI to create a design plan, and sends this message.

[0516] "Means for presenting the generated design plan to the user" refers to a function that displays and proposes the design plan created by the generation AI to the user.

[0517] The "means for recommending specialist contractors based on the generated design plan" is a function that selects and recommends specialist contractors that are suitable for the user's area and budget in accordance with the optimal design plan.

[0518] "Means for presenting a list of recommended contractors to the user" refers to a function that displays a list of multiple specialist contractors selected by the generation AI to the user, allowing them to make a selection.

[0519] "Means for providing a virtual architectural experience using virtual reality technology" refers to a function that reproduces the generated design plan as a 3D model, allowing users to experience a home in a virtual reality environment.

[0520] "A means for transparently managing information on construction processes and costs" is a management function that updates the progress and cost details of construction projects in real time, allowing users to easily check this information.

[0521] This is a system that allows users to easily design and build custom homes. The system starts by collecting user information, then generates design plans using generative AI, recommends professional contractors, provides a virtual building experience, and transparently manages the construction process and costs to provide users with the perfect home.

[0522] Retrieving User Information

[0523] The server authenticates users when they access the platform and provides them with a login form. For authentication, Firebase Authentication, a common authentication system, is used. After logging in, users are given a form to enter basic information such as family composition, budget, and housing preferences, which they then enter and send to the server. After receiving the information, the server securely stores it in a database (e.g., Amazon RDS).

[0524] Examples:

[0525] The user enters "Family composition: 4 people, Budget: 30 million yen, Preferences: Modern" into the form and submits it.

[0526] Design proposals using generative AI

[0527] The server generates a prompt sentence based on the acquired user information to send to the generation AI a request to create a design plan. For example, the generated prompt sentence might be, "Please generate a modern house design plan for a family of four with a budget of 30 million yen." The server sends this to a generative AI model (e.g., OpenAI GPT-4). The generation AI generates the optimal house design plan based on the user's preferences and budget and returns it to the server. The server presents the generated design plan to the user, displaying it in a selectable format.

[0528] Example prompt sentence:

[0529] "Generate a modern home design plan for a family of four with a budget of 30 million yen."

[0530] Professional recommendation

[0531] The user selects their preferred plan from the presented design plans. Based on the selected design plan, the server sends a request to the generation AI to recommend the most suitable specialist contractor. The generation AI considers conditions such as budget, region, and reputation, generates a list of the most suitable contractors, and returns it to the server. The server presents the list of recommended contractors to the user, allowing the user to make a selection.

[0532] Examples:

[0533] After the user selects "4LDK with modern design," the generating AI creates a list of highly rated specialist contractors in Tokyo and returns this to the server.

[0534] Providing a virtual architectural experience

[0535] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan using software such as Unity and creates a virtual environment. The server provides the user's device with an access link to the VR environment, allowing the user to experience the designed home in virtual space through the link.

[0536] Examples:

[0537] The user accesses the link provided by the server on their Oculus Quest 2 and tours the designed home in a virtual environment.

[0538] Transparent Management

[0539] The server operates a system to constantly update the progress and cost details of the construction process. For this, a management system is built using Python and Django. The server displays this information to users in real time through a user interface. Users can check the progress and costs through the interface provided, maintaining transparency of the construction process and costs.

[0540] Examples:

[0541] The user checks details on the dashboard, such as "Current phase: foundation work, progress rate: 60%, cumulative cost: 18 million yen."

[0542] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0543] Step 1:

[0544] Retrieving User Information

[0545] The server authenticates users when they access the platform and provides them with a login form. The user enters their login information into the form and sends it to the server. The server receives it and authenticates them using Firebase Authentication. If authentication is successful, it displays a form for entering user information. The user enters information such as family composition, budget, and housing preferences and sends it to the server. The server stores the received information in an Amazon RDS database.

[0546] Input: User login information, personal information form (family composition, budget, preferences, etc.)

[0547] Output: Authentication result, message that saving to database is complete

[0548] Specific operation: The user enters "User name: user123, Password: pass123, Family composition: 4 people, Budget: 30 million yen, Preferences: Modern" into the form and submits it.

[0549] Step 2:

[0550] Design proposals using generative AI

[0551] The server generates a prompt based on the acquired user information to send a request to the generative AI to create a design plan. The server then sends this prompt to a generative AI model (e.g., OpenAI GPT-4). The generative AI generates an optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plan to the user.

[0552] Input: User information (family structure, budget, preferences, etc.), prompt text

[0553] Output: Generated design plan

[0554] Specific operation: The server generates a prompt sentence, "Please generate a modern house design plan for a family of four with a budget of 30 million yen," and sends it to the generation AI. The generation AI generates a plan proposing a modern design for a 4LDK and returns it to the server.

[0555] Step 3:

[0556] Professional recommendation

[0557] After the user selects their preferred plan from the presented design plans, the server sends a request to the generation AI to recommend the most suitable specialist contractors, including local information, based on the selected design plan. The generation AI considers conditions such as budget, area, and reputation, generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user.

[0558] Input: Selected design plan, local information

[0559] Output: A list of specialists

[0560] Specific operation: After the user selects "4LDK with modern design," the server uses that information to request highly rated specialist contractors in Tokyo with a budget of 30 million yen or less from the generation AI, and presents the generated contractor list to the user.

[0561] Step 4:

[0562] Providing a virtual architectural experience

[0563] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides an access link to the VR environment to the user's device, allowing the user to experience the designed home in virtual space through the link.

[0564] Input: Generated design plan

[0565] Output: VR environment link

[0566] Specific operation: The user accesses the link provided by the server on Oculus Quest 2 and tours the designed home in a virtual environment.

[0567] Step 5:

[0568] Transparent Management

[0569] The server operates a system to constantly update the construction progress and cost details. The management system is built using Python and Django. The server displays this information to users in real time through a user interface. Users can check the progress and costs through the interface provided, maintaining transparency of the construction process and costs.

[0570] Input: Construction progress information, cost information

[0571] Output: Real-time progress and cost information

[0572] Specific operation: The user checks details on the dashboard, such as "Current phase: foundation work, progress rate: 60%, cumulative cost: 18 million yen."

[0573] (Application example 1)

[0574] 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."

[0575] Conventional home design systems required extensive specialized knowledge for users to design their ideal home, and checking and correcting design plans required a lot of time and money. Furthermore, it was difficult to fully experience the real world, and virtual environments were limited in scope. Furthermore, transparency of the process and costs from design to construction was often lacking, reducing user satisfaction.

[0576] 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.

[0577] In this invention, the server includes a means for acquiring user information, a means for using a generation AI to generate a design plan based on the acquired user information, a VR module that is a means for displaying the generated design plan as a 3D model using virtual reality technology, a means for using a generation AI to recommend a professional contractor based on the generated design plan, a means for providing a virtual construction experience using virtual reality technology, a means for transparently managing information on the construction process and costs, a means for acquiring user location information using a location identification device, and a means for displaying information using smart glasses. This allows users without specialized knowledge to easily create an optimal home design and enjoy a detailed virtual experience in real time, ensuring transparency of the process and costs from design to construction.

[0578] "User information" refers to basic information such as the user's family structure, budget, and housing preferences.

[0579] "Design plans" refer to the blueprints and layouts of homes generated based on the user's preferences and budget.

[0580] "Generative AI" is an artificial intelligence system that generates optimal design plans based on user information.

[0581] The "VR Module" is a system that uses virtual reality technology to display design plans as 3D models, providing users with a virtual architectural experience.

[0582] "Recommending specialists" refers to the process by which the generative AI selects and recommends the most suitable specialists based on the user's design plan.

[0583] "Virtual architectural experience" refers to the process of allowing users to experience generated design plans in a virtual reality environment.

[0584] "Transparent management" means providing users with real-time updates on the construction process and costs.

[0585] "Location-determining device" refers to a device used to obtain a user's location information.

[0586] "Smart glasses" are wearable devices for displaying information and providing visual feedback to users.

[0587] This invention is a system that allows users to easily design and build custom homes, and includes the following processes:

[0588] Retrieving User Information

[0589] The server authenticates users when they access the platform and provides them with a login form. After logging in, users are provided with a form to enter basic information such as family composition, budget, and housing preferences. Users enter the required information into the indicated form and submit it to the server, which then securely stores the submitted information in a database.

[0590] Generate design plans

[0591] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[0592] Virtual reality experience

[0593] The server passes the design plan created by the generative AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides the user's device with an access link to the VR environment, allowing the user to experience the designed home in virtual space through the link.

[0594] Professional recommendation

[0595] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[0596] Transparent Management

[0597] The server constantly updates the progress and cost details of the construction process and displays them in real time through the user interface. Users can check the progress and costs through the interface provided, ensuring transparency of the construction process and costs.

[0598] Using smart glasses

[0599] Furthermore, smart glasses can be used to visually display information, allowing users to check design plans and experience them virtually on the spot by using the smart glasses installed in showrooms and stores.

[0600] Use of location-specific devices

[0601] By using location-specific devices to obtain user location information, the in-store experience can be improved in real time, and optimal information can be provided based on the user's movement.

[0602] Examples and prompts

[0603] For example, in a scenario where a user visiting a housing exhibition puts on smart glasses and designs a custom home on the spot, the following prompt is generated based on the information entered by the user:

[0604] Family composition: 4 people

[0605] Budget: 50,000,000 yen

[0606] Style: Modern

[0607] Number of rooms: 3

[0608] Use this information to generate the best home design plans.

[0609] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0610] Step 1:

[0611] When a user accesses the platform, the server sends an authentication request. The user enters information into the login form and completes authentication. The input data is a username and password, and the server compares this with the database as authentication information and returns the authentication result. The output is the authentication result (success / failure).

[0612] Step 2:

[0613] The server provides a form for users who have been successfully authenticated to enter basic information such as family composition, budget, and housing preferences. The user enters the information into this form and sends it to the server. The input data, such as family composition, budget, and preferred style, is securely stored in a database by the server. The output is a confirmation that the user information has been saved.

[0614] Step 3:

[0615] The server generates a prompt sentence based on the saved user information. Using the generated prompt sentence, it sends a design plan generation request to the generation AI. The input data is user information, which is converted into a prompt sentence generated by the server and sent to the generation AI. The output is a confirmation that the design plan generation request has been sent.

[0616] Step 4:

[0617] The generation AI generates a house design plan based on the received prompt and returns it to the server. The input data is the prompt, and the generation AI analyzes this prompt to generate a design plan. The output is the design plan, which is sent back to the server.

[0618] Step 5:

[0619] The server passes the generated design plan to the VR module and sends a request to display it as a 3D model. The input data is the design plan, which the server sends to the VR module. The output is a confirmation of the sending of the 3D model generation request.

[0620] Step 6:

[0621] The VR module creates a virtual environment based on the design plan and returns a link to the server that can be accessed on the user's device. The input data is the design plan, which the VR module converts into a 3D model. The output is a link to access the virtual environment.

[0622] Step 7:

[0623] The server provides the user with an access link to the virtual environment, through which the user experiences the designed house in the virtual space. The input data is the virtual environment access link, which the user uses to perform the virtual experience. The output is the user's experience information.

[0624] Step 8:

[0625] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable specialist. The input data is the design plan, which the server sends to the generation AI. The output is a confirmation of the submission of the specialist recommendation request.

[0626] Step 9:

[0627] The generation AI analyzes the region, budget, ratings, etc., and generates a list of the most suitable contractors, which it returns to the server. The input data is the design plan and contractor information, which the generation AI analyzes. The output is a list of recommended contractors.

[0628] Step 10:

[0629] The server provides the user with a list of recommended vendors, from which the user can select the vendor that best suits them. The input data is the list of recommended vendors, which the server displays to the user. The output is the user's selection of vendors.

[0630] Step 11:

[0631] The server updates the progress and cost details of the construction process and displays them in real time through the user interface. The input data is the progress and cost details of the construction process, which the server records in a database and provides to the user. The output is a display of the progress and cost information.

[0632] Step 12:

[0633] The user checks the progress and costs through the provided interface. The input data are the details of the progress and costs provided by the server, which the user can view. The output is the confirmation result.

[0634] 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.

[0635] This is a system that allows users to easily design and build custom homes, and in particular, incorporates an emotion engine to provide optimal design plans and services that take user emotions into consideration. This system includes the processes of acquiring user information, generating design plans using AI, recommending professional contractors, providing a virtual building experience, and transparently managing the construction process and costs.

[0636] Retrieving User Information

[0637] The server authenticates users when they access the platform and provides them with a login form. If the user successfully logs in, a form is displayed for them to enter basic information such as their family composition, budget, and housing preferences. The user enters the required information into the form and submits it to the server, which stores the submitted information in a database.

[0638] Design proposals using generative AI

[0639] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[0640] Professional recommendation

[0641] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[0642] Implementing the Emotion Engine

[0643] The server uses an emotion engine to recognize users' emotions in real time as they select design plans or engage in virtual building experiences. The emotion engine analyzes users' emotions using facial recognition, voice analysis, and other technologies, and feeds the results back to the generative AI and other system components.

[0644] Providing a virtual architectural experience

[0645] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in a virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides the user with an access link to the VR environment. The user experiences the designed house in a virtual space through the link.

[0646] Feedback combined with emotion engine

[0647] The emotion engine recognizes users' emotions in real time during the virtual building experience and provides that data to the generative AI. The generative AI can then use this feedback to adjust the design plan. For example, if a user expresses positive emotions about a design plan, the system will generate a plan that emphasizes those elements. If a user expresses negative emotions, the system will generate a plan to improve those elements.

[0648] Transparent management and support

[0649] The server constantly updates the progress and cost details of the construction process and displays them on the user interface. Users can check the progress and costs in real time and communicate with the builder if necessary. In addition, the emotion engine recognizes the user's emotions during this process and provides appropriate assistance and alerts.

[0650] summary

[0651] The system of this invention allows users to easily design and build their ideal home by combining user information acquisition, design suggestions using generative AI, recommendation of professional contractors, provision of a virtual building experience incorporating an emotion engine, and transparent management of the building process and costs. This system will eliminate opacity in the building industry and increase user satisfaction and peace of mind.

[0652] The processing flow will be explained below.

[0653] Step 1:

[0654] The server authenticates users when they access the platform and provides them with a login form. If the user successfully logs in, they are presented with a form to enter basic information such as family composition, budget, and housing preferences.

[0655] Step 2:

[0656] The user enters the necessary information into the displayed form and sends it to the server. For example, the user might enter "family of four" as the family composition, "50 million yen" as the budget, and "modern style" as the preference.

[0657] Step 3:

[0658] The server receives the information sent by the user, stores it in a database, and then sends a request to the generation AI to create a plan.

[0659] Step 4:

[0660] The generation AI analyzes the received user information and generates multiple home design plans based on the user's preferences and budget. The generated design plans are then returned to the server. For example, it generates three modern-style design plans and sends that information to the server.

[0661] Step 5:

[0662] The server presents the design plans returned by the generation AI to the user, who then selects one of the plans. At this time, details and images of the design plan are also displayed.

[0663] Step 6:

[0664] The server sends a request to the generation AI to recommend the most suitable specialist based on the design plan selected by the user.

[0665] Step 7:

[0666] The Generative AI analyzes the area, budget, and ratings to generate a list of the most suitable professional contractors for the selected design plan. For example, it selects three contractors based on the user's area, budget, and past ratings. The generated contractor list is then returned to the server.

[0667] Step 8:

[0668] The server presents the list of vendors returned by the AI ​​to the user, who then selects the vendor that best suits them. The list also includes detailed information and ratings for each vendor.

[0669] Step 9:

[0670] The server uses an emotion engine to recognize the user's emotions in real time based on the design plan and professional contractor information selected by the user, and this information is fed back to the generative AI.

[0671] Step 10:

[0672] The emotion engine analyzes emotions from facial expressions and voice when a user selects a design plan or browses a list of contractors, and sends the data to a server. For example, if a user smiles while looking at a plan, it determines that the emotion is positive.

[0673] Step 11:

[0674] Based on the feedback data from the emotion engine, the server asks the generative AI to adjust the design plan, for example, to generate a new plan that emphasizes elements that have been identified as generating positive emotions.

[0675] Step 12:

[0676] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space.

[0677] Step 13:

[0678] The VR module generates a 3D model based on the design plan, creates a virtual environment, and returns an access link to the virtual environment to the server.

[0679] Step 14:

[0680] The server provides users with an access link to the VR environment, through which they can experience the designed house in a virtual space.

[0681] Step 15:

[0682] The server constantly updates the progress and cost details of the construction process and displays them on the user interface. Users can check the progress and costs in real time and communicate with the builder if necessary. In addition, the emotion engine recognizes the user's emotions during this process and provides appropriate assistance and alerts.

[0683] Example 2

[0684] 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."

[0685] Conventional custom home design and construction systems have difficulty providing design plans that adequately reflect the complex needs and feelings of users. Furthermore, because individual processes such as proposing design plans, recommending specialist contractors, and providing virtual construction experiences are not integrated, the process is cumbersome and opaque for users. Furthermore, the lack of transparency in the management of the construction process and costs has led to a lack of security for users.

[0686] 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.

[0687] In this invention, the server includes means for acquiring user information, means for using artificial intelligence to generate a design plan based on the acquired user information, means for recommending a contractor based on the generated design plan, means for recognizing the user's emotions using an emotion engine and providing feedback based on the emotions, means for providing a virtual construction experience using virtual reality technology, and means for transparently managing information on the construction process and costs. This makes it possible to provide a design plan that reflects the user's emotions and needs, recommend the most suitable contractor, provide a virtual construction experience using real-time emotion feedback, and transparently manage the construction process and costs.

[0688] "User Information" refers to personal information about a User, such as family composition, budget, and housing preferences, that is necessary for the design and construction of a custom home.

[0689] "Artificial intelligence" refers to digital technology that uses machine learning and deep learning techniques to generate optimal home design plans based on user information.

[0690] "Specialist contractors" refer to the craftsmen and companies that actually carry out the construction and installation in the design and building of custom homes.

[0691] An "emotion engine" refers to technology that recognizes and analyzes the emotions of users in real time when using a system.

[0692] "Virtual reality technology" is a technology that provides an experience close to the real world in a digital space, and is used to allow users to experience a house before it is built in a virtual space.

[0693] "Virtual architectural experience" refers to the use of virtual reality technology to allow users to experience a home designed in a digital space in real time.

[0694] "Transparent information management" means providing users with real-time details about the construction process and costs, and sharing the latest information at all times, eliminating any opacity for users.

[0695] This is a system that allows users to easily design and build custom homes, and in particular, incorporates an emotion engine to provide optimal design plans and services that take user emotions into consideration. This system includes the processes of acquiring user information, generating design plans using AI, recommending professional contractors, providing a virtual building experience, and transparently managing the construction process and costs.

[0696] First, the server authenticates the user when they access the platform and provides them with a login form. If the user successfully logs in, a form is displayed for them to enter basic information such as their family composition, budget, and housing preferences. The user enters this information and sends it to the server. The server stores the submitted information in a database. This process uses a relational database management system such as the MySQL database.

[0697] Next, the server requests the generation AI to generate a design plan based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one. The generation AI uses models such as GPT-3 that use deep learning technology.

[0698] Once the user selects a design plan, the server sends a request to the generation AI to recommend the most suitable specialist contractor. The generation AI analyzes the area, budget, and evaluation data, generates a list of the most suitable contractors, and returns it to the server. The server then presents this list to the user, who can then select the contractor that best suits them.

[0699] When selecting a design plan or experiencing a virtual building, the server uses an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotions using facial recognition technology (e.g., OpenCV) and voice analysis technology. This emotion data is fed back to the generative AI and other system components.

[0700] To provide a virtual architectural experience, the server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in a virtual space. The VR module generates a 3D model based on the design plan using a 3D game engine such as Unity, creating a virtual environment. The server provides the user with an access link to the VR environment, allowing the user to experience the designed house in the virtual space through the link.

[0701] Furthermore, the server updates the progress and cost details of the construction process in real time and displays them on the user interface. Users can check this and communicate with the builder if necessary. The emotion engine recognizes the user's emotions during the construction process and provides appropriate assistance and alerts.

[0702] Prompt Sentence Examples

[0703] User information: Family composition (couple and two children), budget (50 million yen), housing preferences (modern, spacious kitchen)

[0704] Generate the best home design plan based on the user information above.

[0705] In this way, the system can provide design plans that reflect the user's emotions and needs, recommend professional contractors, provide a virtual building experience with real-time emotional feedback, and transparently manage the construction process and costs.

[0706] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0707] Step 1: Get user information

[0708] 1. The server initiates the authentication process when the user accesses the platform and displays a login form.

[0709] Input: User ID, Password

[0710] Output: Authentication result (success / failure), form display status

[0711] Specific behavior: Validates the authentication information and displays the next input form if the user successfully logs in.

[0712] 2. The user enters the required information into the login form and presses the submit button.

[0713] Input: User ID, Password

[0714] Output: User authentication request

[0715] Specific operation: Sends authentication information to the server.

[0716] 3. The server verifies the authentication information entered and, if successful, displays a form for entering basic information such as family composition, budget, and housing preferences.

[0717] Input: User authentication request

[0718] Output: User information input form

[0719] Specific operation: Check the database and dynamically generate the next form depending on the authentication result.

[0720] 4. The user enters basic information and presses the send button.

[0721] Inputs: Family composition, budget, housing preferences

[0722] Output: User information request

[0723] Specific operation: Send basic information to the server.

[0724] 5. The server stores the entered user information in a database.

[0725] Input: User Information Request

[0726] Output: Status of saving to database

[0727] What it does: Stores user information using a relational database management system such as a MySQL database.

[0728] Step 2: Generate a design plan

[0729] 1. The server requests the generation AI to generate a design plan based on the stored user information.

[0730] Input: User information

[0731] Output: Design plan generation request

[0732] Specific operation: A Python program is used to call the generative AI's API and send a prompt containing user information.

[0733] 2. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server.

[0734] Input: Design plan generation request

[0735] Output: Generated house design plan

[0736] Specific operation: Generate a design plan using deep learning technology (e.g., GPT-3).

[0737] 3. The server presents the generated design plans to the user for selection.

[0738] Input: Generated house design plan

[0739] Output: Present the design plan to the user

[0740] What it does: Display the design plan on a web page or application interface.

[0741] Step 3: Professional Recommendations

[0742] 1. The user selects one of the presented design plans.

[0743] Input: Multiple design plans

[0744] Output: Selected design plan

[0745] Specific behavior: Review the design plans and select the best one.

[0746] 2. The server sends a request to the generating AI to generate a list of the most suitable specialists based on the design plan information selected by the user.

[0747] Input: Selected design plan information

[0748] Output: Contractor selection request

[0749] Specific operation: Include vendor evaluation data in the prompt text sent to the generation AI.

[0750] 3. The generative AI analyzes the region, budget, and rating data to create a list of optimal contractors and return it to the server.

[0751] Input: Contractor selection request

[0752] Output: A list of the best specialists

[0753] Specific operation: Select the best vendor using a machine learning algorithm.

[0754] 4. The server presents this list of vendors to the user.

[0755] Input: List of best professional contractors

[0756] Output: Present a list of vendors to the user

[0757] What it does: Displays a list of vendors on a web page or application interface.

[0758] 5. The user selects the appropriate provider from the list.

[0759] Input: Professional Contractor List

[0760] Output: Selected vendor information

[0761] Specific actions: Check the vendor list and select the appropriate vendor.

[0762] Step 4: Implementing the Emotion Engine

[0763] 1. The server runs an emotion engine that recognizes the user's emotions in real time as they select design plans and engage in virtual architectural experiences.

[0764] Input: Real-time user data (face data, voice data)

[0765] Output: User emotion data

[0766] What it does: Captures real-time facial and audio data using a webcam and microphone.

[0767] 2. The emotion engine analyzes the user's facial recognition data and voice data to determine their emotional state.

[0768] Input: Real-time face data, voice data

[0769] Output: User emotion judgment result

[0770] Specific operation: Analyzes emotion data using OpenCV and speech analysis libraries.

[0771] 3. The server feeds this emotion data back to system components such as generative AI, triggering corresponding actions.

[0772] Input: User's emotion judgment result

[0773] Output: Feedback data, trigger actions

[0774] Specific behavior: Dynamically change the content of the user interface based on emotion data.

[0775] Step 5: Providing a virtual building experience

[0776] 1. The server passes the design plan created by the generation AI to the VR module and sends a request to reproduce it in virtual space.

[0777] Input: User design plan

[0778] Output: Virtual space generation request

[0779] Specific operation: Calls the API to send data to the VR module.

[0780] 2. The VR module generates a 3D model based on the design plan and creates a virtual environment.

[0781] Input: User design plan

[0782] Output: The generated virtual environment

[0783] Specific operation: Build a virtual environment using a 3D game engine such as Unity.

[0784] 3. The server provides the user with an access link to this VR environment.

[0785] Input: The generated virtual environment

[0786] Output: VR environment access link to user

[0787] What it does: Generates a link and sends it to the user's account.

[0788] 4. Users can experience the designed home in a virtual space via a VR headset or PC via the link.

[0789] Input: VR environment access link

[0790] Output: Virtual architectural experience

[0791] Specific action: Experience a virtual space using a VR device such as Oculus Rift or HTC Vive.

[0792] Step 6: Transparent management and support

[0793] 1. The server updates the construction progress and cost details in real time and displays them in the user interface.

[0794] Input: Construction process data, cost data

[0795] Output: Displaying progress and costs

[0796] Specific actions: Visualize progress and cost data using tools such as Google Charts.

[0797] 2. Users can view progress and cost details and communicate with the builder if necessary.

[0798] Input: View progress and costs

[0799] Output: User feedback and communication requests

[0800] What it does: Check progress and cost details, and send questions if you have any questions.

[0801] 3. The Emotion Engine recognizes users' emotions in real time during the construction process and provides appropriate assistance and alerts.

[0802] Input: Real-time user data (face data, voice data)

[0803] Output: Support message, alert notification

[0804] Specific behavior: Display appropriate motivational messages and alerts to users based on emotional data.

[0805] (Application example 2)

[0806] 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."

[0807] Conventional custom home design systems proposed plans based on the user's preferences and budget, but they lacked the ability to adjust design plans based on the user's emotions or optimize the design through a virtual construction experience. Therefore, a new proposal method was needed to increase user satisfaction. Furthermore, transparency in the design and construction processes was insufficient, making it difficult for users to collaborate with trusted contractors.

[0808] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user information, means for using a generation AI to generate a design plan based on the acquired user information, means for recommending a professional contractor based on the generated design plan, means for providing a virtual construction experience using virtual reality technology, means for transparently managing information on the construction process and costs, means for using an emotion engine to recognize the user's emotions in real time and adjust the design plan based on the results, means for experiencing a home designed in a virtual space based on the generated design plan, and means for providing feedback on the user's emotions during the virtual space experience and for the generation AI to optimize the design plan. This enables optimal proposals and adjustments that take the user's emotions into consideration, thereby improving user satisfaction. Furthermore, transparent management enhances user trust and enables smooth collaboration with contractors.

[0809] "User information" refers to basic information such as the user's family composition, budget, preferences, etc.

[0810] "Design plan" refers to a proposed house design based on user information.

[0811] "Generative AI" refers to artificial intelligence (AI) that creates design plans based on user information.

[0812] "Specialist contractor" refers to a contractor that carries out construction and installation based on a design plan.

[0813] "Virtual reality technology" refers to the technology of creating a virtual space that resembles reality using computer technology.

[0814] "Virtual architectural experience" refers to the use of virtual reality technology to allow users to experience the design of a home in a virtual space.

[0815] An "emotion engine" is an engine that uses technologies such as facial recognition and voice analysis to recognize and analyze users' emotions in real time.

[0816] "Cost information" refers to details of various costs and budgets incurred during the construction process.

[0817] "Transparent management" means presenting information to users clearly and in real time, eliminating opacity.

[0818] "Virtual space" refers to a three-dimensional digital space generated within a computer using virtual reality technology.

[0819] "Feedback" refers to collecting user emotional data and providing information to adjust design plans based on that data.

[0820] "Optimizing" refers to adjusting proposals and plans to the best possible state based on the user's feelings and desires.

[0821] The following system configuration is shown as an embodiment of this invention. The invention includes a generation AI that acquires user information and generates an optimal design plan based on it, recommendation of specialist contractors, a virtual building experience using virtual reality technology, real-time feedback by an emotion engine, and transparent management.

[0822] System Program

[0823] The system mainly consists of the following hardware and software:

[0824] User device: smartphone, tablet, or computer

[0825] Server: Cloud server (AWS, Google Cloud, etc.)

[0826] Generative AI models: Natural language processing models such as GPT-3 and Claude

[0827] Emotion engine: Emotion recognition software such as Affectiva SDK

[0828] AR Platform: Apple ARKit, Google ARCore

[0829] Retrieving User Information

[0830] Users log in to the app using their devices and enter basic information (family composition, budget, preferences, etc.). This information is sent from the user's device to the server, which then stores the received information in a cloud database.

[0831] Generative AI creates design plans

[0832] The server sends the saved user information to the generative AI model and requests it to generate an optimal design plan. The generative AI model generates a design plan that matches the user's preferences and budget and returns it to the server. The server displays this design plan to the user.

[0833] Professional recommendation

[0834] After the user selects a design plan, the server will ask the AI ​​to generate a list of the most suitable specialists based on factors such as area, budget, and reputation. This list will be presented to the user, who can then select the contractor that best suits them.

[0835] Feedback using an emotion engine

[0836] As users select a design plan and experience the virtual building process, their emotions are monitored in real time via the user's device's camera and microphone. The emotion engine analyzes the collected data and determines the user's emotions. The server sends the emotion engine's results to the generation AI, which adjusts the design plan based on the feedback. For example, if the user responds positively to a proposed design, a new plan is generated that emphasizes those elements.

[0837] Providing a virtual building experience and transparent management

[0838] The server sends the design plan created by the generative AI to the user's device via the AR platform, allowing them to experience the designed home in a virtual space. Users can virtually place the home using the AR function of their smartphone or tablet and check the feel of it in the real environment. In addition, transparent management of the construction process and costs allows users to check the project progress and costs in real time.

[0839] Examples of specific examples and prompts

[0840] For example, if a user attempts to arrange furniture in a virtual space and expresses their feelings about the arrangement, for example, "If I put a sofa here, it would feel more spacious," the generative AI will use that emotion data to suggest new furniture arrangements.

[0841] Example prompt sentence:

[0842] "A user looks at the proposed furniture arrangement and says, 'If I put a sofa here, it would feel even bigger.' Suggest a new furniture arrangement that reflects this."

[0843] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0844] Step 1:

[0845] Users log in to the application using their devices and enter basic information such as family composition, budget, and housing preferences into the login form. This information is sent from the user device to the server and stored in a cloud database.

[0846] Input: User's basic information (family structure, budget, preferences, etc.)

[0847] Output: User information stored in a cloud database

[0848] Specific operation: The user enters the required information into the form presented on the smartphone or tablet and presses the "Submit" button.

[0849] Step 2:

[0850] The server acquires user information and sends it to a generative AI model, which generates a design plan based on the user's preferences and budget and sends it back to the server.

[0851] Input: User information stored in a cloud database

[0852] Output: Design plans generated by the generative AI

[0853] Specific operation: The server sends an appropriate prompt to the generation AI, which processes the user's information to create the optimal design plan.

[0854] Step 3:

[0855] The server sends the design plans received from the generative AI model to the user's device and displays them to the user, who then checks the presented design plans and makes a selection.

[0856] Input: Design plan returned from the generative AI

[0857] Output: Design plan displayed on the user's device

[0858] Specific operation: The server generates the design plan in HTML format and displays it to the user through a web interface.

[0859] Step 4:

[0860] After the user selects a design plan, the server again sends a request to the generative AI model to recommend a specialist contractor. The generative AI model then lists the most suitable specialist contractors based on location, budget, reputation, etc., and sends the list back to the server.

[0861] Input: User selected design plan and user information

[0862] Output: A list of the best professionals

[0863] Specific operation: The server again sends the prompt sentence to the generation AI model, which generates a list of candidate specialists based on the design plan.

[0864] Step 5:

[0865] The server sends a list of specialists to the user terminal and displays it to the user, allowing the user to select from the list.

[0866] Input: A list of specialists returned by the generation AI

[0867] Output: A list of specialists displayed on the user's device

[0868] Specific operation: The user selects a suitable vendor from the presented list of vendors.

[0869] Step 6:

[0870] While reviewing design plans and experiencing the virtual world, the user's emotions are observed in real time using the camera and microphone on the user's device. The emotion engine analyzes this data and determines the user's emotions.

[0871] Input: User's facial expression and voice data

[0872] Output: Analyzed user emotion data

[0873] How it works: Using the smartphone's camera and microphone, the emotion engine analyzes this data to identify emotions.

[0874] Step 7:

[0875] The server sends the results of the emotion engine to the generative AI, which then adjusts the design plan, for example, highlighting design elements for which users expressed positive emotions and improving negative elements.

[0876] Input: Analyzed emotion data, user information

[0877] Output: New adjusted design plan

[0878] Specific operation: The server uses a prompt statement to ask the generation AI to create a new design plan.

[0879] Step 8:

[0880] The server sends the new design plan adjusted by the generative AI to the user's device via the AR platform, providing an experience in a virtual space.

[0881] Input: New design plan adjusted by the generative AI

[0882] Output: Virtual experience displayed on the user's device

[0883] Specific operation: The user uses the AR function of their smartphone to virtually experience new design plans.

[0884] Step 9:

[0885] The server manages the progress and costs of the construction process in real time and displays them on the user's device, allowing the user to constantly check the progress and costs of the project.

[0886] Input: Construction process and cost information

[0887] Output: Real-time progress and cost information displayed on the user's device

[0888] What it does: The server uses a project management tool to monitor progress and costs, and displays that information to the user in HTML format.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] [Third embodiment]

[0893] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0894] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0895] 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).

[0896] 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.

[0897] 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.

[0898] 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).

[0899] 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. 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.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] 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."

[0905] This is a system that allows users to easily design and build custom homes. The system starts by collecting user information, then generates design plans using generative AI, recommends professional contractors, provides a virtual building experience, and transparently manages the construction process and costs to provide users with the perfect home.

[0906] Retrieving User Information

[0907] The server authenticates users when they access the platform and provides them with a login form. After logging in, users are provided with a form to enter basic information such as family composition, budget, and housing preferences. Users enter the required information into the indicated form and submit it to the server, which then securely stores the submitted information in a database.

[0908] Design proposals using generative AI

[0909] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[0910] Professional recommendation

[0911] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[0912] Providing a virtual architectural experience

[0913] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides an access link to the VR environment to the user's device, allowing the user to experience the designed home in virtual space through the link.

[0914] Transparent Management

[0915] The server constantly updates the construction progress and cost details and displays them in real time through the user interface. Users can check the progress and costs through the interface provided, ensuring transparency of the construction process and costs.

[0916] summary

[0917] The system of the present invention allows users to easily design and build the home that best suits them by linking the processes of acquiring user information, providing design suggestions using generative AI, recommending professional contractors, providing a virtual building experience, and transparently managing the building process and costs. This system allows users to realize a home that meets their needs without experiencing the opacity of the building industry.

[0918] The processing flow will be explained below.

[0919] Step 1:

[0920] The server authenticates the user when they access the platform and provides a login form. If the user successfully logs in, the server displays a form for entering user information.

[0921] Step 2:

[0922] The user fills in the form with basic information such as family composition, budget, housing preferences, etc. Once the information is complete, the user presses the "Submit" button to send the information to the server.

[0923] Step 3:

[0924] The server receives the information sent by the user, stores it in a database, and then sends a request to the generation AI to create a plan.

[0925] Step 4:

[0926] The generation AI analyzes the received user information, generates multiple home design plans based on the user's preferences and budget, and returns the generated design plans to the server.

[0927] Step 5:

[0928] The server presents the design plans returned by the generation AI to the user, who then selects one of the plans.

[0929] Step 6:

[0930] The server sends a request to the generation AI to recommend the most suitable specialist based on the design plan selected by the user.

[0931] Step 7:

[0932] The generation AI analyzes the area, budget, ratings, etc., and generates a list of the most suitable specialist contractors that correspond to the selected design plan. The generated contractor list is returned to the server.

[0933] Step 8:

[0934] The server presents the list of vendors returned by the generation AI to the user, who then selects a vendor from the list based on their preferences and reliability.

[0935] Step 9:

[0936] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space.

[0937] Step 10:

[0938] The VR module generates a 3D model based on the design plan, creates a virtual environment, and returns an access link to the virtual environment to the server.

[0939] Step 11:

[0940] The server provides users with an access link to the VR environment, through which they can experience the designed house in a virtual space.

[0941] Step 12:

[0942] The server constantly updates the construction progress and cost details and displays them on the user interface, allowing users to check the progress and costs in real time and maintaining transparency of the construction process and costs.

[0943] Example 1

[0944] 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."

[0945] In the traditional home design and construction process, users must go through complicated procedures, making it difficult to select the right design and contractor without specialized knowledge. Furthermore, the construction process and costs are not transparent, making it difficult for users to track the progress and manage costs of a construction project. For these reasons, there is a demand for a system that allows users to design and build custom homes easily and smoothly.

[0946] 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.

[0947] In this invention, the server includes means for acquiring user information, means for using a generation AI to generate a design plan based on the acquired user information, means for sending a design plan creation request to the generation AI, means for presenting the generated design plan to the user, means for recommending a professional contractor based on the generated design plan, means for presenting a list of recommended contractors to the user, means for providing a virtual construction experience using virtual reality technology, and means for transparently managing information on the construction process and costs. This allows users to obtain optimal design and construction plans even without specialized knowledge, and enables transparent and real-time management of the construction process and costs.

[0948] "Means for obtaining user information" refers to a function for collecting personal information, family composition, budget, housing preferences, etc. provided by the user.

[0949] "Means of using generation AI to generate design plans based on acquired user information" refers to a function that uses generation AI to automatically create optimal home design plans based on information obtained from the user.

[0950] The "means for sending a design plan creation request to the generation AI" is a function that generates a prompt message based on user information to request the generation AI to create a design plan, and sends this message.

[0951] "Means for presenting the generated design plan to the user" refers to a function that displays and proposes the design plan created by the generation AI to the user.

[0952] The "means for recommending specialist contractors based on the generated design plan" is a function that selects and recommends specialist contractors that are suitable for the user's area and budget in accordance with the optimal design plan.

[0953] "Means for presenting a list of recommended contractors to the user" refers to a function that displays a list of multiple specialist contractors selected by the generation AI to the user, allowing them to make a selection.

[0954] "Means for providing a virtual architectural experience using virtual reality technology" refers to a function that reproduces the generated design plan as a 3D model, allowing users to experience a home in a virtual reality environment.

[0955] "A means for transparently managing information on construction processes and costs" is a management function that updates the progress and cost details of construction projects in real time, allowing users to easily check this information.

[0956] This is a system that allows users to easily design and build custom homes. The system starts by collecting user information, then generates design plans using generative AI, recommends professional contractors, provides a virtual building experience, and transparently manages the construction process and costs to provide users with the perfect home.

[0957] Retrieving User Information

[0958] The server authenticates users when they access the platform and provides them with a login form. For authentication, Firebase Authentication, a common authentication system, is used. After logging in, users are given a form to enter basic information such as family composition, budget, and housing preferences, which they then enter and send to the server. After receiving the information, the server securely stores it in a database (e.g., Amazon RDS).

[0959] Examples:

[0960] The user enters "Family composition: 4 people, Budget: 30 million yen, Preferences: Modern" into the form and submits it.

[0961] Design proposals using generative AI

[0962] The server generates a prompt sentence based on the acquired user information to send to the generation AI a request to create a design plan. For example, the generated prompt sentence might be, "Please generate a modern house design plan for a family of four with a budget of 30 million yen." The server sends this to a generative AI model (e.g., OpenAI GPT-4). The generation AI generates the optimal house design plan based on the user's preferences and budget and returns it to the server. The server presents the generated design plan to the user, displaying it in a selectable format.

[0963] Example prompt sentence:

[0964] "Generate a modern home design plan for a family of four with a budget of 30 million yen."

[0965] Professional recommendation

[0966] The user selects their preferred plan from the presented design plans. Based on the selected design plan, the server sends a request to the generation AI to recommend the most suitable specialist contractor. The generation AI considers conditions such as budget, region, and reputation, generates a list of the most suitable contractors, and returns it to the server. The server presents the list of recommended contractors to the user, allowing the user to make a selection.

[0967] Examples:

[0968] After the user selects "4LDK with modern design," the generating AI creates a list of highly rated specialist contractors in Tokyo and returns this to the server.

[0969] Providing a virtual architectural experience

[0970] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan using software such as Unity and creates a virtual environment. The server provides the user's device with an access link to the VR environment, allowing the user to experience the designed home in virtual space through the link.

[0971] Examples:

[0972] The user accesses the link provided by the server on their Oculus Quest 2 and tours the designed home in a virtual environment.

[0973] Transparent Management

[0974] The server operates a system to constantly update the progress and cost details of the construction process. For this, a management system is built using Python and Django. The server displays this information to users in real time through a user interface. Users can check the progress and costs through the interface provided, maintaining transparency of the construction process and costs.

[0975] Examples:

[0976] The user checks details on the dashboard, such as "Current phase: foundation work, progress rate: 60%, cumulative cost: 18 million yen."

[0977] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0978] Step 1:

[0979] Retrieving User Information

[0980] The server authenticates users when they access the platform and provides them with a login form. The user enters their login information into the form and sends it to the server. The server receives it and authenticates them using Firebase Authentication. If authentication is successful, it displays a form for entering user information. The user enters information such as family composition, budget, and housing preferences and sends it to the server. The server stores the received information in an Amazon RDS database.

[0981] Input: User login information, personal information form (family composition, budget, preferences, etc.)

[0982] Output: Authentication result, message that saving to database is complete

[0983] Specific operation: The user enters "User name: user123, Password: pass123, Family composition: 4 people, Budget: 30 million yen, Preferences: Modern" into the form and submits it.

[0984] Step 2:

[0985] Design proposals using generative AI

[0986] The server generates a prompt based on the acquired user information to send a request to the generative AI to create a design plan. The server then sends this prompt to a generative AI model (e.g., OpenAI GPT-4). The generative AI generates an optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plan to the user.

[0987] Input: User information (family structure, budget, preferences, etc.), prompt text

[0988] Output: Generated design plan

[0989] Specific operation: The server generates a prompt sentence, "Please generate a modern house design plan for a family of four with a budget of 30 million yen," and sends it to the generation AI. The generation AI generates a plan proposing a modern design for a 4LDK and returns it to the server.

[0990] Step 3:

[0991] Professional recommendation

[0992] After the user selects their preferred plan from the presented design plans, the server sends a request to the generation AI to recommend the most suitable specialist contractors, including local information, based on the selected design plan. The generation AI considers conditions such as budget, area, and reputation, generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user.

[0993] Input: Selected design plan, local information

[0994] Output: A list of specialists

[0995] Specific operation: After the user selects "4LDK with modern design," the server uses that information to request highly rated specialist contractors in Tokyo with a budget of 30 million yen or less from the generation AI, and presents the generated contractor list to the user.

[0996] Step 4:

[0997] Providing a virtual architectural experience

[0998] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides an access link to the VR environment to the user's device, allowing the user to experience the designed home in virtual space through the link.

[0999] Input: Generated design plan

[1000] Output: VR environment link

[1001] Specific operation: The user accesses the link provided by the server on Oculus Quest 2 and tours the designed home in a virtual environment.

[1002] Step 5:

[1003] Transparent Management

[1004] The server operates a system to constantly update the construction progress and cost details. The management system is built using Python and Django. The server displays this information to users in real time through a user interface. Users can check the progress and costs through the interface provided, maintaining transparency of the construction process and costs.

[1005] Input: Construction progress information, cost information

[1006] Output: Real-time progress and cost information

[1007] Specific operation: The user checks details on the dashboard, such as "Current phase: foundation work, progress rate: 60%, cumulative cost: 18 million yen."

[1008] (Application example 1)

[1009] 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."

[1010] Conventional home design systems required extensive specialized knowledge for users to design their ideal home, and checking and correcting design plans required a lot of time and money. Furthermore, it was difficult to fully experience the real world, and virtual environments were limited in scope. Furthermore, transparency of the process and costs from design to construction was often lacking, reducing user satisfaction.

[1011] 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.

[1012] In this invention, the server includes a means for acquiring user information, a means for using a generation AI to generate a design plan based on the acquired user information, a VR module that is a means for displaying the generated design plan as a 3D model using virtual reality technology, a means for using a generation AI to recommend a professional contractor based on the generated design plan, a means for providing a virtual construction experience using virtual reality technology, a means for transparently managing information on the construction process and costs, a means for acquiring user location information using a location identification device, and a means for displaying information using smart glasses. This allows users without specialized knowledge to easily create an optimal home design and enjoy a detailed virtual experience in real time, ensuring transparency of the process and costs from design to construction.

[1013] "User information" refers to basic information such as the user's family structure, budget, and housing preferences.

[1014] "Design plans" refer to the blueprints and layouts of homes generated based on the user's preferences and budget.

[1015] "Generative AI" is an artificial intelligence system that generates optimal design plans based on user information.

[1016] The "VR Module" is a system that uses virtual reality technology to display design plans as 3D models, providing users with a virtual architectural experience.

[1017] "Recommending specialists" refers to the process by which the generative AI selects and recommends the most suitable specialists based on the user's design plan.

[1018] "Virtual architectural experience" refers to the process of allowing users to experience generated design plans in a virtual reality environment.

[1019] "Transparent management" means providing users with real-time updates on the construction process and costs.

[1020] "Location-determining device" refers to a device used to obtain a user's location information.

[1021] "Smart glasses" are wearable devices for displaying information and providing visual feedback to users.

[1022] This invention is a system that allows users to easily design and build custom homes, and includes the following processes:

[1023] Retrieving User Information

[1024] The server authenticates users when they access the platform and provides them with a login form. After logging in, users are provided with a form to enter basic information such as family composition, budget, and housing preferences. Users enter the required information into the indicated form and submit it to the server, which then securely stores the submitted information in a database.

[1025] Generate design plans

[1026] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[1027] Virtual reality experience

[1028] The server passes the design plan created by the generative AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides the user's device with an access link to the VR environment, allowing the user to experience the designed home in virtual space through the link.

[1029] Professional recommendation

[1030] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[1031] Transparent Management

[1032] The server constantly updates the progress and cost details of the construction process and displays them in real time through the user interface. Users can check the progress and costs through the interface provided, ensuring transparency of the construction process and costs.

[1033] Using smart glasses

[1034] Furthermore, smart glasses can be used to visually display information, allowing users to check design plans and experience them virtually on the spot by using the smart glasses installed in showrooms and stores.

[1035] Use of location-specific devices

[1036] By using location-specific devices to obtain user location information, the in-store experience can be improved in real time, and optimal information can be provided based on the user's movement.

[1037] Examples and prompts

[1038] For example, in a scenario where a user visiting a housing exhibition puts on smart glasses and designs a custom home on the spot, the following prompt is generated based on the information entered by the user:

[1039] Family composition: 4 people

[1040] Budget: 50,000,000 yen

[1041] Style: Modern

[1042] Number of rooms: 3

[1043] Use this information to generate the best home design plans.

[1044] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1045] Step 1:

[1046] When a user accesses the platform, the server sends an authentication request. The user enters information into the login form and completes authentication. The input data is a username and password, and the server compares this with the database as authentication information and returns the authentication result. The output is the authentication result (success / failure).

[1047] Step 2:

[1048] The server provides a form for users who have been successfully authenticated to enter basic information such as family composition, budget, and housing preferences. The user enters the information into this form and sends it to the server. The input data, such as family composition, budget, and preferred style, is securely stored in a database by the server. The output is a confirmation that the user information has been saved.

[1049] Step 3:

[1050] The server generates a prompt sentence based on the saved user information. Using the generated prompt sentence, it sends a design plan generation request to the generation AI. The input data is user information, which is converted into a prompt sentence generated by the server and sent to the generation AI. The output is a confirmation that the design plan generation request has been sent.

[1051] Step 4:

[1052] The generation AI generates a house design plan based on the received prompt and returns it to the server. The input data is the prompt, and the generation AI analyzes this prompt to generate a design plan. The output is the design plan, which is sent back to the server.

[1053] Step 5:

[1054] The server passes the generated design plan to the VR module and sends a request to display it as a 3D model. The input data is the design plan, which the server sends to the VR module. The output is a confirmation of the sending of the 3D model generation request.

[1055] Step 6:

[1056] The VR module creates a virtual environment based on the design plan and returns a link to the server that can be accessed on the user's device. The input data is the design plan, which the VR module converts into a 3D model. The output is a link to access the virtual environment.

[1057] Step 7:

[1058] The server provides the user with an access link to the virtual environment, through which the user experiences the designed house in the virtual space. The input data is the virtual environment access link, which the user uses to perform the virtual experience. The output is the user's experience information.

[1059] Step 8:

[1060] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable specialist. The input data is the design plan, which the server sends to the generation AI. The output is a confirmation of the submission of the specialist recommendation request.

[1061] Step 9:

[1062] The generation AI analyzes the region, budget, ratings, etc., and generates a list of the most suitable contractors, which it returns to the server. The input data is the design plan and contractor information, which the generation AI analyzes. The output is a list of recommended contractors.

[1063] Step 10:

[1064] The server provides the user with a list of recommended vendors, from which the user can select the vendor that best suits them. The input data is the list of recommended vendors, which the server displays to the user. The output is the user's selection of vendors.

[1065] Step 11:

[1066] The server updates the progress and cost details of the construction process and displays them in real time through the user interface. The input data is the progress and cost details of the construction process, which the server records in a database and provides to the user. The output is a display of the progress and cost information.

[1067] Step 12:

[1068] The user checks the progress and costs through the provided interface. The input data are the details of the progress and costs provided by the server, which the user can view. The output is the confirmation result.

[1069] 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.

[1070] This is a system that allows users to easily design and build custom homes, and in particular, incorporates an emotion engine to provide optimal design plans and services that take user emotions into consideration. This system includes the processes of acquiring user information, generating design plans using AI, recommending professional contractors, providing a virtual building experience, and transparently managing the construction process and costs.

[1071] Retrieving User Information

[1072] The server authenticates users when they access the platform and provides them with a login form. If the user successfully logs in, a form is displayed for them to enter basic information such as their family composition, budget, and housing preferences. The user enters the required information into the form and submits it to the server, which stores the submitted information in a database.

[1073] Design proposals using generative AI

[1074] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[1075] Professional recommendation

[1076] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[1077] Implementing the Emotion Engine

[1078] The server uses an emotion engine to recognize users' emotions in real time as they select design plans or engage in virtual building experiences. The emotion engine analyzes users' emotions using facial recognition, voice analysis, and other technologies, and feeds the results back to the generative AI and other system components.

[1079] Providing a virtual architectural experience

[1080] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in a virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides the user with an access link to the VR environment. The user experiences the designed house in a virtual space through the link.

[1081] Feedback combined with emotion engine

[1082] The emotion engine recognizes users' emotions in real time during the virtual building experience and provides that data to the generative AI. The generative AI can then use this feedback to adjust the design plan. For example, if a user expresses positive emotions about a design plan, the system will generate a plan that emphasizes those elements. If a user expresses negative emotions, the system will generate a plan to improve those elements.

[1083] Transparent management and support

[1084] The server constantly updates the progress and cost details of the construction process and displays them on the user interface. Users can check the progress and costs in real time and communicate with the builder if necessary. In addition, the emotion engine recognizes the user's emotions during this process and provides appropriate assistance and alerts.

[1085] summary

[1086] The system of this invention allows users to easily design and build their ideal home by combining user information acquisition, design suggestions using generative AI, recommendation of professional contractors, provision of a virtual building experience incorporating an emotion engine, and transparent management of the building process and costs. This system will eliminate opacity in the building industry and increase user satisfaction and peace of mind.

[1087] The processing flow will be explained below.

[1088] Step 1:

[1089] The server authenticates users when they access the platform and provides them with a login form. If the user successfully logs in, they are presented with a form to enter basic information such as family composition, budget, and housing preferences.

[1090] Step 2:

[1091] The user enters the necessary information into the displayed form and sends it to the server. For example, the user might enter "family of four" as the family composition, "50 million yen" as the budget, and "modern style" as the preference.

[1092] Step 3:

[1093] The server receives the information sent by the user, stores it in a database, and then sends a request to the generation AI to create a plan.

[1094] Step 4:

[1095] The generation AI analyzes the received user information and generates multiple home design plans based on the user's preferences and budget. The generated design plans are then returned to the server. For example, it generates three modern-style design plans and sends that information to the server.

[1096] Step 5:

[1097] The server presents the design plans returned by the generation AI to the user, who then selects one of the plans. At this time, details and images of the design plan are also displayed.

[1098] Step 6:

[1099] The server sends a request to the generation AI to recommend the most suitable specialist based on the design plan selected by the user.

[1100] Step 7:

[1101] The Generative AI analyzes the area, budget, and ratings to generate a list of the most suitable professional contractors for the selected design plan. For example, it selects three contractors based on the user's area, budget, and past ratings. The generated contractor list is then returned to the server.

[1102] Step 8:

[1103] The server presents the list of vendors returned by the AI ​​to the user, who then selects the vendor that best suits them. The list also includes detailed information and ratings for each vendor.

[1104] Step 9:

[1105] The server uses an emotion engine to recognize the user's emotions in real time based on the design plan and professional contractor information selected by the user, and this information is fed back to the generative AI.

[1106] Step 10:

[1107] The emotion engine analyzes emotions from facial expressions and voice when a user selects a design plan or browses a list of contractors, and sends the data to a server. For example, if a user smiles while looking at a plan, it determines that the emotion is positive.

[1108] Step 11:

[1109] Based on the feedback data from the emotion engine, the server asks the generative AI to adjust the design plan, for example, to generate a new plan that emphasizes elements that have been identified as generating positive emotions.

[1110] Step 12:

[1111] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space.

[1112] Step 13:

[1113] The VR module generates a 3D model based on the design plan, creates a virtual environment, and returns an access link to the virtual environment to the server.

[1114] Step 14:

[1115] The server provides users with an access link to the VR environment, through which they can experience the designed house in a virtual space.

[1116] Step 15:

[1117] The server constantly updates the progress and cost details of the construction process and displays them on the user interface. Users can check the progress and costs in real time and communicate with the builder if necessary. In addition, the emotion engine recognizes the user's emotions during this process and provides appropriate assistance and alerts.

[1118] Example 2

[1119] 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."

[1120] Conventional custom home design and construction systems have difficulty providing design plans that adequately reflect the complex needs and feelings of users. Furthermore, because individual processes such as proposing design plans, recommending specialist contractors, and providing virtual construction experiences are not integrated, the process is cumbersome and opaque for users. Furthermore, the lack of transparency in the management of the construction process and costs has led to a lack of security for users.

[1121] 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.

[1122] In this invention, the server includes means for acquiring user information, means for using artificial intelligence to generate a design plan based on the acquired user information, means for recommending a contractor based on the generated design plan, means for recognizing the user's emotions using an emotion engine and providing feedback based on the emotions, means for providing a virtual construction experience using virtual reality technology, and means for transparently managing information on the construction process and costs. This makes it possible to provide a design plan that reflects the user's emotions and needs, recommend the most suitable contractor, provide a virtual construction experience using real-time emotion feedback, and transparently manage the construction process and costs.

[1123] "User Information" refers to personal information about a User, such as family composition, budget, and housing preferences, that is necessary for the design and construction of a custom home.

[1124] "Artificial intelligence" refers to digital technology that uses machine learning and deep learning techniques to generate optimal home design plans based on user information.

[1125] "Specialist contractors" refer to the craftsmen and companies that actually carry out the construction and installation in the design and building of custom homes.

[1126] An "emotion engine" refers to technology that recognizes and analyzes the emotions of users in real time when using a system.

[1127] "Virtual reality technology" is a technology that provides an experience close to the real world in a digital space, and is used to allow users to experience a house before it is built in a virtual space.

[1128] "Virtual architectural experience" refers to the use of virtual reality technology to allow users to experience a home designed in a digital space in real time.

[1129] "Transparent information management" means providing users with real-time details about the construction process and costs, and sharing the latest information at all times, eliminating any opacity for users.

[1130] This is a system that allows users to easily design and build custom homes, and in particular, incorporates an emotion engine to provide optimal design plans and services that take user emotions into consideration. This system includes the processes of acquiring user information, generating design plans using AI, recommending professional contractors, providing a virtual building experience, and transparently managing the construction process and costs.

[1131] First, the server authenticates the user when they access the platform and provides them with a login form. If the user successfully logs in, a form is displayed for them to enter basic information such as their family composition, budget, and housing preferences. The user enters this information and sends it to the server. The server stores the submitted information in a database. This process uses a relational database management system such as the MySQL database.

[1132] Next, the server requests the generation AI to generate a design plan based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one. The generation AI uses models such as GPT-3 that use deep learning technology.

[1133] Once the user selects a design plan, the server sends a request to the generation AI to recommend the most suitable specialist contractor. The generation AI analyzes the area, budget, and evaluation data, generates a list of the most suitable contractors, and returns it to the server. The server then presents this list to the user, who can then select the contractor that best suits them.

[1134] When selecting a design plan or experiencing a virtual building, the server uses an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotions using facial recognition technology (e.g., OpenCV) and voice analysis technology. This emotion data is fed back to the generative AI and other system components.

[1135] To provide a virtual architectural experience, the server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in a virtual space. The VR module generates a 3D model based on the design plan using a 3D game engine such as Unity, creating a virtual environment. The server provides the user with an access link to the VR environment, allowing the user to experience the designed house in the virtual space through the link.

[1136] Furthermore, the server updates the progress and cost details of the construction process in real time and displays them on the user interface. Users can check this and communicate with the builder if necessary. The emotion engine recognizes the user's emotions during the construction process and provides appropriate assistance and alerts.

[1137] Prompt Sentence Examples

[1138] User information: Family composition (couple and two children), budget (50 million yen), housing preferences (modern, spacious kitchen)

[1139] Generate the best home design plan based on the user information above.

[1140] In this way, the system can provide design plans that reflect the user's emotions and needs, recommend professional contractors, provide a virtual building experience with real-time emotional feedback, and transparently manage the construction process and costs.

[1141] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1142] Step 1: Get user information

[1143] 1. The server initiates the authentication process when the user accesses the platform and displays a login form.

[1144] Input: User ID, Password

[1145] Output: Authentication result (success / failure), form display status

[1146] Specific behavior: Validates the authentication information and displays the next input form if the user successfully logs in.

[1147] 2. The user enters the required information into the login form and presses the submit button.

[1148] Input: User ID, Password

[1149] Output: User authentication request

[1150] Specific operation: Sends authentication information to the server.

[1151] 3. The server verifies the authentication information entered and, if successful, displays a form for entering basic information such as family composition, budget, and housing preferences.

[1152] Input: User authentication request

[1153] Output: User information input form

[1154] Specific operation: Check the database and dynamically generate the next form depending on the authentication result.

[1155] 4. The user enters basic information and presses the send button.

[1156] Inputs: Family composition, budget, housing preferences

[1157] Output: User information request

[1158] Specific operation: Send basic information to the server.

[1159] 5. The server stores the entered user information in a database.

[1160] Input: User Information Request

[1161] Output: Status of saving to database

[1162] What it does: Stores user information using a relational database management system such as a MySQL database.

[1163] Step 2: Generate a design plan

[1164] 1. The server requests the generation AI to generate a design plan based on the stored user information.

[1165] Input: User information

[1166] Output: Design plan generation request

[1167] Specific operation: A Python program is used to call the generative AI's API and send a prompt containing user information.

[1168] 2. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server.

[1169] Input: Design plan generation request

[1170] Output: Generated house design plan

[1171] Specific operation: Generate a design plan using deep learning technology (e.g., GPT-3).

[1172] 3. The server presents the generated design plans to the user for selection.

[1173] Input: Generated house design plan

[1174] Output: Present the design plan to the user

[1175] What it does: Display the design plan on a web page or application interface.

[1176] Step 3: Professional Recommendations

[1177] 1. The user selects one of the presented design plans.

[1178] Input: Multiple design plans

[1179] Output: Selected design plan

[1180] Specific behavior: Review the design plans and select the best one.

[1181] 2. The server sends a request to the generating AI to generate a list of the most suitable specialists based on the design plan information selected by the user.

[1182] Input: Selected design plan information

[1183] Output: Contractor selection request

[1184] Specific operation: Include vendor evaluation data in the prompt text sent to the generation AI.

[1185] 3. The generative AI analyzes the region, budget, and rating data to create a list of optimal contractors and return it to the server.

[1186] Input: Contractor selection request

[1187] Output: A list of the best specialists

[1188] Specific operation: Select the best vendor using a machine learning algorithm.

[1189] 4. The server presents this list of vendors to the user.

[1190] Input: List of best professional contractors

[1191] Output: Present a list of vendors to the user

[1192] What it does: Displays a list of vendors on a web page or application interface.

[1193] 5. The user selects the appropriate provider from the list.

[1194] Input: Professional Contractor List

[1195] Output: Selected vendor information

[1196] Specific actions: Check the vendor list and select the appropriate vendor.

[1197] Step 4: Implementing the Emotion Engine

[1198] 1. The server runs an emotion engine that recognizes the user's emotions in real time as they select design plans and engage in virtual architectural experiences.

[1199] Input: Real-time user data (face data, voice data)

[1200] Output: User emotion data

[1201] What it does: Captures real-time facial and audio data using a webcam and microphone.

[1202] 2. The emotion engine analyzes the user's facial recognition data and voice data to determine their emotional state.

[1203] Input: Real-time face data, voice data

[1204] Output: User emotion judgment result

[1205] Specific operation: Analyzes emotion data using OpenCV and speech analysis libraries.

[1206] 3. The server feeds this emotion data back to system components such as generative AI, triggering corresponding actions.

[1207] Input: User's emotion judgment result

[1208] Output: Feedback data, trigger actions

[1209] Specific behavior: Dynamically change the content of the user interface based on emotion data.

[1210] Step 5: Providing a virtual building experience

[1211] 1. The server passes the design plan created by the generation AI to the VR module and sends a request to reproduce it in virtual space.

[1212] Input: User design plan

[1213] Output: Virtual space generation request

[1214] Specific operation: Calls the API to send data to the VR module.

[1215] 2. The VR module generates a 3D model based on the design plan and creates a virtual environment.

[1216] Input: User design plan

[1217] Output: The generated virtual environment

[1218] Specific operation: Build a virtual environment using a 3D game engine such as Unity.

[1219] 3. The server provides the user with an access link to this VR environment.

[1220] Input: The generated virtual environment

[1221] Output: VR environment access link to user

[1222] What it does: Generates a link and sends it to the user's account.

[1223] 4. Users can experience the designed home in a virtual space via a VR headset or PC via the link.

[1224] Input: VR environment access link

[1225] Output: Virtual architectural experience

[1226] Specific action: Experience a virtual space using a VR device such as Oculus Rift or HTC Vive.

[1227] Step 6: Transparent management and support

[1228] 1. The server updates the construction progress and cost details in real time and displays them in the user interface.

[1229] Input: Construction process data, cost data

[1230] Output: Displaying progress and costs

[1231] Specific actions: Visualize progress and cost data using tools such as Google Charts.

[1232] 2. Users can view progress and cost details and communicate with the builder if necessary.

[1233] Input: View progress and costs

[1234] Output: User feedback and communication requests

[1235] What it does: Check progress and cost details, and send questions if you have any questions.

[1236] 3. The Emotion Engine recognizes users' emotions in real time during the construction process and provides appropriate assistance and alerts.

[1237] Input: Real-time user data (face data, voice data)

[1238] Output: Support message, alert notification

[1239] Specific behavior: Display appropriate motivational messages and alerts to users based on emotional data.

[1240] (Application example 2)

[1241] 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."

[1242] Conventional custom home design systems proposed plans based on the user's preferences and budget, but they lacked the ability to adjust design plans based on the user's emotions or optimize the design through a virtual construction experience. Therefore, a new proposal method was needed to increase user satisfaction. Furthermore, transparency in the design and construction processes was insufficient, making it difficult for users to collaborate with trusted contractors.

[1243] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user information, means for using a generation AI to generate a design plan based on the acquired user information, means for recommending a professional contractor based on the generated design plan, means for providing a virtual construction experience using virtual reality technology, means for transparently managing information on the construction process and costs, means for using an emotion engine to recognize the user's emotions in real time and adjust the design plan based on the results, means for experiencing a home designed in a virtual space based on the generated design plan, and means for providing feedback on the user's emotions during the virtual space experience and for the generation AI to optimize the design plan. This enables optimal proposals and adjustments that take the user's emotions into consideration, thereby improving user satisfaction. Furthermore, transparent management enhances user trust and enables smooth collaboration with contractors.

[1244] "User information" refers to basic information such as the user's family composition, budget, preferences, etc.

[1245] "Design plan" refers to a proposed house design based on user information.

[1246] "Generative AI" refers to artificial intelligence (AI) that creates design plans based on user information.

[1247] "Specialist contractor" refers to a contractor that carries out construction and installation based on a design plan.

[1248] "Virtual reality technology" refers to the technology of creating a virtual space that resembles reality using computer technology.

[1249] "Virtual architectural experience" refers to the use of virtual reality technology to allow users to experience the design of a home in a virtual space.

[1250] An "emotion engine" is an engine that uses technologies such as facial recognition and voice analysis to recognize and analyze users' emotions in real time.

[1251] "Cost information" refers to details of various costs and budgets incurred during the construction process.

[1252] "Transparent management" means presenting information to users clearly and in real time, eliminating opacity.

[1253] "Virtual space" refers to a three-dimensional digital space generated within a computer using virtual reality technology.

[1254] "Feedback" refers to collecting user emotional data and providing information to adjust design plans based on that data.

[1255] "Optimizing" refers to adjusting proposals and plans to the best possible state based on the user's feelings and desires.

[1256] The following system configuration is shown as an embodiment of this invention. The invention includes a generation AI that acquires user information and generates an optimal design plan based on it, recommendation of specialist contractors, a virtual building experience using virtual reality technology, real-time feedback by an emotion engine, and transparent management.

[1257] System Program

[1258] The system mainly consists of the following hardware and software:

[1259] User device: smartphone, tablet, or computer

[1260] Server: Cloud server (AWS, Google Cloud, etc.)

[1261] Generative AI models: Natural language processing models such as GPT-3 and Claude

[1262] Emotion engine: Emotion recognition software such as Affectiva SDK

[1263] AR Platform: Apple ARKit, Google ARCore

[1264] Retrieving User Information

[1265] Users log in to the app using their devices and enter basic information (family composition, budget, preferences, etc.). This information is sent from the user's device to the server, which then stores the received information in a cloud database.

[1266] Generative AI creates design plans

[1267] The server sends the saved user information to the generative AI model and requests it to generate an optimal design plan. The generative AI model generates a design plan that matches the user's preferences and budget and returns it to the server. The server displays this design plan to the user.

[1268] Professional recommendation

[1269] After the user selects a design plan, the server will ask the AI ​​to generate a list of the most suitable specialists based on factors such as area, budget, and reputation. This list will be presented to the user, who can then select the contractor that best suits them.

[1270] Feedback using an emotion engine

[1271] As users select a design plan and experience the virtual building process, their emotions are monitored in real time via the user's device's camera and microphone. The emotion engine analyzes the collected data and determines the user's emotions. The server sends the emotion engine's results to the generation AI, which adjusts the design plan based on the feedback. For example, if the user responds positively to a proposed design, a new plan is generated that emphasizes those elements.

[1272] Providing a virtual building experience and transparent management

[1273] The server sends the design plan created by the generative AI to the user's device via the AR platform, allowing them to experience the designed home in a virtual space. Users can virtually place the home using the AR function of their smartphone or tablet and check the feel of it in the real environment. In addition, transparent management of the construction process and costs allows users to check the project progress and costs in real time.

[1274] Examples of specific examples and prompts

[1275] For example, if a user attempts to arrange furniture in a virtual space and expresses their feelings about the arrangement, for example, "If I put a sofa here, it would feel more spacious," the generative AI will use that emotion data to suggest new furniture arrangements.

[1276] Example prompt sentence:

[1277] "A user looks at the proposed furniture arrangement and says, 'If I put a sofa here, it would feel even bigger.' Suggest a new furniture arrangement that reflects this."

[1278] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1279] Step 1:

[1280] Users log in to the application using their devices and enter basic information such as family composition, budget, and housing preferences into the login form. This information is sent from the user device to the server and stored in a cloud database.

[1281] Input: User's basic information (family structure, budget, preferences, etc.)

[1282] Output: User information stored in a cloud database

[1283] Specific operation: The user enters the required information into the form presented on the smartphone or tablet and presses the "Submit" button.

[1284] Step 2:

[1285] The server acquires user information and sends it to a generative AI model, which generates a design plan based on the user's preferences and budget and sends it back to the server.

[1286] Input: User information stored in a cloud database

[1287] Output: Design plans generated by the generative AI

[1288] Specific operation: The server sends an appropriate prompt to the generation AI, which processes the user's information to create the optimal design plan.

[1289] Step 3:

[1290] The server sends the design plans received from the generative AI model to the user's device and displays them to the user, who then checks the presented design plans and makes a selection.

[1291] Input: Design plan returned from the generative AI

[1292] Output: Design plan displayed on the user's device

[1293] Specific operation: The server generates the design plan in HTML format and displays it to the user through a web interface.

[1294] Step 4:

[1295] After the user selects a design plan, the server again sends a request to the generative AI model to recommend a specialist contractor. The generative AI model then lists the most suitable specialist contractors based on location, budget, reputation, etc., and sends the list back to the server.

[1296] Input: User selected design plan and user information

[1297] Output: A list of the best professionals

[1298] Specific operation: The server again sends the prompt sentence to the generation AI model, which generates a list of candidate specialists based on the design plan.

[1299] Step 5:

[1300] The server sends a list of specialists to the user terminal and displays it to the user, allowing the user to select from the list.

[1301] Input: A list of specialists returned by the generation AI

[1302] Output: A list of specialists displayed on the user's device

[1303] Specific operation: The user selects a suitable vendor from the presented list of vendors.

[1304] Step 6:

[1305] While reviewing design plans and experiencing the virtual world, the user's emotions are observed in real time using the camera and microphone on the user's device. The emotion engine analyzes this data and determines the user's emotions.

[1306] Input: User's facial expression and voice data

[1307] Output: Analyzed user emotion data

[1308] How it works: Using the smartphone's camera and microphone, the emotion engine analyzes this data to identify emotions.

[1309] Step 7:

[1310] The server sends the results of the emotion engine to the generative AI, which then adjusts the design plan, for example, highlighting design elements for which users expressed positive emotions and improving negative elements.

[1311] Input: Analyzed emotion data, user information

[1312] Output: New adjusted design plan

[1313] Specific operation: The server uses a prompt statement to ask the generation AI to create a new design plan.

[1314] Step 8:

[1315] The server sends the new design plan adjusted by the generative AI to the user's device via the AR platform, providing an experience in a virtual space.

[1316] Input: New design plan adjusted by the generative AI

[1317] Output: Virtual experience displayed on the user's device

[1318] Specific operation: The user uses the AR function of their smartphone to virtually experience new design plans.

[1319] Step 9:

[1320] The server manages the progress and costs of the construction process in real time and displays them on the user's device, allowing the user to constantly check the progress and costs of the project.

[1321] Input: Construction process and cost information

[1322] Output: Real-time progress and cost information displayed on the user's device

[1323] What it does: The server uses a project management tool to monitor progress and costs, and displays that information to the user in HTML format.

[1324] 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.

[1325] 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.

[1326] 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.

[1327] [Fourth embodiment]

[1328] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1329] 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.

[1330] 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).

[1331] 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.

[1332] 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.

[1333] 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).

[1334] 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. 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.

[1335] 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.

[1336] 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.

[1337] 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.

[1338] 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.

[1339] 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.

[1340] 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."

[1341] This is a system that allows users to easily design and build custom homes. The system starts by collecting user information, then generates design plans using generative AI, recommends professional contractors, provides a virtual building experience, and transparently manages the construction process and costs to provide users with the perfect home.

[1342] Retrieving User Information

[1343] The server authenticates users when they access the platform and provides them with a login form. After logging in, users are provided with a form to enter basic information such as family composition, budget, and housing preferences. Users enter the required information into the indicated form and submit it to the server, which then securely stores the submitted information in a database.

[1344] Design proposals using generative AI

[1345] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[1346] Professional recommendation

[1347] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[1348] Providing a virtual architectural experience

[1349] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides an access link to the VR environment to the user's device, allowing the user to experience the designed home in virtual space through the link.

[1350] Transparent Management

[1351] The server constantly updates the construction progress and cost details and displays them in real time through the user interface. Users can check the progress and costs through the interface provided, ensuring transparency of the construction process and costs.

[1352] summary

[1353] The system of the present invention allows users to easily design and build the home that best suits them by linking the processes of acquiring user information, providing design suggestions using generative AI, recommending professional contractors, providing a virtual building experience, and transparently managing the building process and costs. This system allows users to realize a home that meets their needs without experiencing the opacity of the building industry.

[1354] The processing flow will be explained below.

[1355] Step 1:

[1356] The server authenticates the user when they access the platform and provides a login form. If the user successfully logs in, the server displays a form for entering user information.

[1357] Step 2:

[1358] The user fills in the form with basic information such as family composition, budget, housing preferences, etc. Once the information is complete, the user presses the "Submit" button to send the information to the server.

[1359] Step 3:

[1360] The server receives the information sent by the user, stores it in a database, and then sends a request to the generation AI to create a plan.

[1361] Step 4:

[1362] The generation AI analyzes the received user information, generates multiple home design plans based on the user's preferences and budget, and returns the generated design plans to the server.

[1363] Step 5:

[1364] The server presents the design plans returned by the generation AI to the user, who then selects one of the plans.

[1365] Step 6:

[1366] The server sends a request to the generation AI to recommend the most suitable specialist based on the design plan selected by the user.

[1367] Step 7:

[1368] The generation AI analyzes the area, budget, ratings, etc., and generates a list of the most suitable specialist contractors that correspond to the selected design plan. The generated contractor list is returned to the server.

[1369] Step 8:

[1370] The server presents the list of vendors returned by the generation AI to the user, who then selects a vendor from the list based on their preferences and reliability.

[1371] Step 9:

[1372] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space.

[1373] Step 10:

[1374] The VR module generates a 3D model based on the design plan, creates a virtual environment, and returns an access link to the virtual environment to the server.

[1375] Step 11:

[1376] The server provides users with an access link to the VR environment, through which they can experience the designed house in a virtual space.

[1377] Step 12:

[1378] The server constantly updates the construction progress and cost details and displays them on the user interface, allowing users to check the progress and costs in real time and maintaining transparency of the construction process and costs.

[1379] Example 1

[1380] 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."

[1381] In the traditional home design and construction process, users must go through complicated procedures, making it difficult to select the right design and contractor without specialized knowledge. Furthermore, the construction process and costs are not transparent, making it difficult for users to track the progress and manage costs of a construction project. For these reasons, there is a demand for a system that allows users to design and build custom homes easily and smoothly.

[1382] 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.

[1383] In this invention, the server includes means for acquiring user information, means for using a generation AI to generate a design plan based on the acquired user information, means for sending a design plan creation request to the generation AI, means for presenting the generated design plan to the user, means for recommending a professional contractor based on the generated design plan, means for presenting a list of recommended contractors to the user, means for providing a virtual construction experience using virtual reality technology, and means for transparently managing information on the construction process and costs. This allows users to obtain optimal design and construction plans even without specialized knowledge, and enables transparent and real-time management of the construction process and costs.

[1384] "Means for obtaining user information" refers to a function for collecting personal information, family composition, budget, housing preferences, etc. provided by the user.

[1385] "Means of using generation AI to generate design plans based on acquired user information" refers to a function that uses generation AI to automatically create optimal home design plans based on information obtained from the user.

[1386] The "means for sending a design plan creation request to the generation AI" is a function that generates a prompt message based on user information to request the generation AI to create a design plan, and sends this message.

[1387] "Means for presenting the generated design plan to the user" refers to a function that displays and proposes the design plan created by the generation AI to the user.

[1388] The "means for recommending specialist contractors based on the generated design plan" is a function that selects and recommends specialist contractors that are suitable for the user's area and budget in accordance with the optimal design plan.

[1389] "Means for presenting a list of recommended contractors to the user" refers to a function that displays a list of multiple specialist contractors selected by the generation AI to the user, allowing them to make a selection.

[1390] "Means for providing a virtual architectural experience using virtual reality technology" refers to a function that reproduces the generated design plan as a 3D model, allowing users to experience a home in a virtual reality environment.

[1391] "A means for transparently managing information on construction processes and costs" is a management function that updates the progress and cost details of construction projects in real time, allowing users to easily check this information.

[1392] This is a system that allows users to easily design and build custom homes. The system starts by collecting user information, then generates design plans using generative AI, recommends professional contractors, provides a virtual building experience, and transparently manages the construction process and costs to provide users with the perfect home.

[1393] Retrieving User Information

[1394] The server authenticates users when they access the platform and provides them with a login form. For authentication, Firebase Authentication, a common authentication system, is used. After logging in, users are given a form to enter basic information such as family composition, budget, and housing preferences, which they then enter and send to the server. After receiving the information, the server securely stores it in a database (e.g., Amazon RDS).

[1395] Examples:

[1396] The user enters "Family composition: 4 people, Budget: 30 million yen, Preferences: Modern" into the form and submits it.

[1397] Design proposals using generative AI

[1398] The server generates a prompt sentence based on the acquired user information to send to the generation AI a request to create a design plan. For example, the generated prompt sentence might be, "Please generate a modern house design plan for a family of four with a budget of 30 million yen." The server sends this to a generative AI model (e.g., OpenAI GPT-4). The generation AI generates the optimal house design plan based on the user's preferences and budget and returns it to the server. The server presents the generated design plan to the user, displaying it in a selectable format.

[1399] Example prompt sentence:

[1400] "Generate a modern home design plan for a family of four with a budget of 30 million yen."

[1401] Professional recommendation

[1402] The user selects their preferred plan from the presented design plans. Based on the selected design plan, the server sends a request to the generation AI to recommend the most suitable specialist contractor. The generation AI considers conditions such as budget, region, and reputation, generates a list of the most suitable contractors, and returns it to the server. The server presents the list of recommended contractors to the user, allowing the user to make a selection.

[1403] Examples:

[1404] After the user selects "4LDK with modern design," the generating AI creates a list of highly rated specialist contractors in Tokyo and returns this to the server.

[1405] Providing a virtual architectural experience

[1406] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan using software such as Unity and creates a virtual environment. The server provides the user's device with an access link to the VR environment, allowing the user to experience the designed home in virtual space through the link.

[1407] Examples:

[1408] The user accesses the link provided by the server on their Oculus Quest 2 and tours the designed home in a virtual environment.

[1409] Transparent Management

[1410] The server operates a system to constantly update the progress and cost details of the construction process. For this, a management system is built using Python and Django. The server displays this information to users in real time through a user interface. Users can check the progress and costs through the interface provided, maintaining transparency of the construction process and costs.

[1411] Examples:

[1412] The user checks details on the dashboard, such as "Current phase: foundation work, progress rate: 60%, cumulative cost: 18 million yen."

[1413] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1414] Step 1:

[1415] Retrieving User Information

[1416] The server authenticates users when they access the platform and provides them with a login form. The user enters their login information into the form and sends it to the server. The server receives it and authenticates them using Firebase Authentication. If authentication is successful, it displays a form for entering user information. The user enters information such as family composition, budget, and housing preferences and sends it to the server. The server stores the received information in an Amazon RDS database.

[1417] Input: User login information, personal information form (family composition, budget, preferences, etc.)

[1418] Output: Authentication result, message that saving to database is complete

[1419] Specific operation: The user enters "User name: user123, Password: pass123, Family composition: 4 people, Budget: 30 million yen, Preferences: Modern" into the form and submits it.

[1420] Step 2:

[1421] Design proposals using generative AI

[1422] The server generates a prompt based on the acquired user information to send a request to the generative AI to create a design plan. The server then sends this prompt to a generative AI model (e.g., OpenAI GPT-4). The generative AI generates an optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plan to the user.

[1423] Input: User information (family structure, budget, preferences, etc.), prompt text

[1424] Output: Generated design plan

[1425] Specific operation: The server generates a prompt sentence, "Please generate a modern house design plan for a family of four with a budget of 30 million yen," and sends it to the generation AI. The generation AI generates a plan proposing a modern design for a 4LDK and returns it to the server.

[1426] Step 3:

[1427] Professional recommendation

[1428] After the user selects their preferred plan from the presented design plans, the server sends a request to the generation AI to recommend the most suitable specialist contractors, including local information, based on the selected design plan. The generation AI considers conditions such as budget, area, and reputation, generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user.

[1429] Input: Selected design plan, local information

[1430] Output: A list of specialists

[1431] Specific operation: After the user selects "4LDK with modern design," the server uses that information to request highly rated specialist contractors in Tokyo with a budget of 30 million yen or less from the generation AI, and presents the generated contractor list to the user.

[1432] Step 4:

[1433] Providing a virtual architectural experience

[1434] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides an access link to the VR environment to the user's device, allowing the user to experience the designed home in virtual space through the link.

[1435] Input: Generated design plan

[1436] Output: VR environment link

[1437] Specific operation: The user accesses the link provided by the server on Oculus Quest 2 and tours the designed home in a virtual environment.

[1438] Step 5:

[1439] Transparent Management

[1440] The server operates a system to constantly update the construction progress and cost details. The management system is built using Python and Django. The server displays this information to users in real time through a user interface. Users can check the progress and costs through the interface provided, maintaining transparency of the construction process and costs.

[1441] Input: Construction progress information, cost information

[1442] Output: Real-time progress and cost information

[1443] Specific operation: The user checks details on the dashboard, such as "Current phase: foundation work, progress rate: 60%, cumulative cost: 18 million yen."

[1444] (Application example 1)

[1445] 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."

[1446] Conventional home design systems required extensive specialized knowledge for users to design their ideal home, and checking and correcting design plans required a lot of time and money. Furthermore, it was difficult to fully experience the real world, and virtual environments were limited in scope. Furthermore, transparency of the process and costs from design to construction was often lacking, reducing user satisfaction.

[1447] 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.

[1448] In this invention, the server includes a means for acquiring user information, a means for using a generation AI to generate a design plan based on the acquired user information, a VR module that is a means for displaying the generated design plan as a 3D model using virtual reality technology, a means for using a generation AI to recommend a professional contractor based on the generated design plan, a means for providing a virtual construction experience using virtual reality technology, a means for transparently managing information on the construction process and costs, a means for acquiring user location information using a location identification device, and a means for displaying information using smart glasses. This allows users without specialized knowledge to easily create an optimal home design and enjoy a detailed virtual experience in real time, ensuring transparency of the process and costs from design to construction.

[1449] "User information" refers to basic information such as the user's family structure, budget, and housing preferences.

[1450] "Design plans" refer to the blueprints and layouts of homes generated based on the user's preferences and budget.

[1451] "Generative AI" is an artificial intelligence system that generates optimal design plans based on user information.

[1452] The "VR Module" is a system that uses virtual reality technology to display design plans as 3D models, providing users with a virtual architectural experience.

[1453] "Recommending specialists" refers to the process by which the generative AI selects and recommends the most suitable specialists based on the user's design plan.

[1454] "Virtual architectural experience" refers to the process of allowing users to experience generated design plans in a virtual reality environment.

[1455] "Transparent management" means providing users with real-time updates on the construction process and costs.

[1456] "Location-determining device" refers to a device used to obtain a user's location information.

[1457] "Smart glasses" are wearable devices for displaying information and providing visual feedback to users.

[1458] This invention is a system that allows users to easily design and build custom homes, and includes the following processes:

[1459] Retrieving User Information

[1460] The server authenticates users when they access the platform and provides them with a login form. After logging in, users are provided with a form to enter basic information such as family composition, budget, and housing preferences. Users enter the required information into the indicated form and submit it to the server, which then securely stores the submitted information in a database.

[1461] Generate design plans

[1462] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[1463] Virtual reality experience

[1464] The server passes the design plan created by the generative AI to the VR module and sends a request to recreate it in virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides the user's device with an access link to the VR environment, allowing the user to experience the designed home in virtual space through the link.

[1465] Professional recommendation

[1466] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[1467] Transparent Management

[1468] The server constantly updates the progress and cost details of the construction process and displays them in real time through the user interface. Users can check the progress and costs through the interface provided, ensuring transparency of the construction process and costs.

[1469] Using smart glasses

[1470] Furthermore, smart glasses can be used to visually display information, allowing users to check design plans and experience them virtually on the spot by using the smart glasses installed in showrooms and stores.

[1471] Use of location-specific devices

[1472] By using location-specific devices to obtain user location information, the in-store experience can be improved in real time, and optimal information can be provided based on the user's movement.

[1473] Examples and prompts

[1474] For example, in a scenario where a user visiting a housing exhibition puts on smart glasses and designs a custom home on the spot, the following prompt is generated based on the information entered by the user:

[1475] Family composition: 4 people

[1476] Budget: 50,000,000 yen

[1477] Style: Modern

[1478] Number of rooms: 3

[1479] Use this information to generate the best home design plans.

[1480] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1481] Step 1:

[1482] When a user accesses the platform, the server sends an authentication request. The user enters information into the login form and completes authentication. The input data is a username and password, and the server compares this with the database as authentication information and returns the authentication result. The output is the authentication result (success / failure).

[1483] Step 2:

[1484] The server provides a form for users who have been successfully authenticated to enter basic information such as family composition, budget, and housing preferences. The user enters the information into this form and sends it to the server. The input data, such as family composition, budget, and preferred style, is securely stored in a database by the server. The output is a confirmation that the user information has been saved.

[1485] Step 3:

[1486] The server generates a prompt sentence based on the saved user information. Using the generated prompt sentence, it sends a design plan generation request to the generation AI. The input data is user information, which is converted into a prompt sentence generated by the server and sent to the generation AI. The output is a confirmation that the design plan generation request has been sent.

[1487] Step 4:

[1488] The generation AI generates a house design plan based on the received prompt and returns it to the server. The input data is the prompt, and the generation AI analyzes this prompt to generate a design plan. The output is the design plan, which is sent back to the server.

[1489] Step 5:

[1490] The server passes the generated design plan to the VR module and sends a request to display it as a 3D model. The input data is the design plan, which the server sends to the VR module. The output is a confirmation of the sending of the 3D model generation request.

[1491] Step 6:

[1492] The VR module creates a virtual environment based on the design plan and returns a link to the server that can be accessed on the user's device. The input data is the design plan, which the VR module converts into a 3D model. The output is a link to access the virtual environment.

[1493] Step 7:

[1494] The server provides the user with an access link to the virtual environment, through which the user experiences the designed house in the virtual space. The input data is the virtual environment access link, which the user uses to perform the virtual experience. The output is the user's experience information.

[1495] Step 8:

[1496] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable specialist. The input data is the design plan, which the server sends to the generation AI. The output is a confirmation of the submission of the specialist recommendation request.

[1497] Step 9:

[1498] The generation AI analyzes the region, budget, ratings, etc., and generates a list of the most suitable contractors, which it returns to the server. The input data is the design plan and contractor information, which the generation AI analyzes. The output is a list of recommended contractors.

[1499] Step 10:

[1500] The server provides the user with a list of recommended vendors, from which the user can select the vendor that best suits them. The input data is the list of recommended vendors, which the server displays to the user. The output is the user's selection of vendors.

[1501] Step 11:

[1502] The server updates the progress and cost details of the construction process and displays them in real time through the user interface. The input data is the progress and cost details of the construction process, which the server records in a database and provides to the user. The output is a display of the progress and cost information.

[1503] Step 12:

[1504] The user checks the progress and costs through the provided interface. The input data are the details of the progress and costs provided by the server, which the user can view. The output is the confirmation result.

[1505] 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.

[1506] This is a system that allows users to easily design and build custom homes, and in particular, incorporates an emotion engine to provide optimal design plans and services that take user emotions into consideration. This system includes the processes of acquiring user information, generating design plans using AI, recommending professional contractors, providing a virtual building experience, and transparently managing the construction process and costs.

[1507] Retrieving User Information

[1508] The server authenticates users when they access the platform and provides them with a login form. If the user successfully logs in, a form is displayed for them to enter basic information such as their family composition, budget, and housing preferences. The user enters the required information into the form and submits it to the server, which stores the submitted information in a database.

[1509] Design proposals using generative AI

[1510] The server sends a plan creation request to the generation AI based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one.

[1511] Professional recommendation

[1512] Based on the design plan selected by the user, the server sends a request to the generation AI to recommend the most suitable professional contractor. The generation AI analyzes the region, budget, ratings, etc., generates a list of the most suitable contractors, and returns it to the server. The server then presents the list of recommended contractors to the user, who can then select the contractor that best suits them.

[1513] Implementing the Emotion Engine

[1514] The server uses an emotion engine to recognize users' emotions in real time as they select design plans or engage in virtual building experiences. The emotion engine analyzes users' emotions using facial recognition, voice analysis, and other technologies, and feeds the results back to the generative AI and other system components.

[1515] Providing a virtual architectural experience

[1516] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in a virtual space. The VR module generates a 3D model based on the design plan and creates a virtual environment. The server provides the user with an access link to the VR environment. The user experiences the designed house in a virtual space through the link.

[1517] Feedback combined with emotion engine

[1518] The emotion engine recognizes users' emotions in real time during the virtual building experience and provides that data to the generative AI. The generative AI can then use this feedback to adjust the design plan. For example, if a user expresses positive emotions about a design plan, the system will generate a plan that emphasizes those elements. If a user expresses negative emotions, the system will generate a plan to improve those elements.

[1519] Transparent management and support

[1520] The server constantly updates the progress and cost details of the construction process and displays them on the user interface. Users can check the progress and costs in real time and communicate with the builder if necessary. In addition, the emotion engine recognizes the user's emotions during this process and provides appropriate assistance and alerts.

[1521] summary

[1522] The system of this invention allows users to easily design and build their ideal home by combining user information acquisition, design suggestions using generative AI, recommendation of professional contractors, provision of a virtual building experience incorporating an emotion engine, and transparent management of the building process and costs. This system will eliminate opacity in the building industry and increase user satisfaction and peace of mind.

[1523] The processing flow will be explained below.

[1524] Step 1:

[1525] The server authenticates users when they access the platform and provides them with a login form. If the user successfully logs in, they are presented with a form to enter basic information such as family composition, budget, and housing preferences.

[1526] Step 2:

[1527] The user enters the necessary information into the displayed form and sends it to the server. For example, the user might enter "family of four" as the family composition, "50 million yen" as the budget, and "modern style" as the preference.

[1528] Step 3:

[1529] The server receives the information sent by the user, stores it in a database, and then sends a request to the generation AI to create a plan.

[1530] Step 4:

[1531] The generation AI analyzes the received user information and generates multiple home design plans based on the user's preferences and budget. The generated design plans are then returned to the server. For example, it generates three modern-style design plans and sends that information to the server.

[1532] Step 5:

[1533] The server presents the design plans returned by the generation AI to the user, who then selects one of the plans. At this time, details and images of the design plan are also displayed.

[1534] Step 6:

[1535] The server sends a request to the generation AI to recommend the most suitable specialist based on the design plan selected by the user.

[1536] Step 7:

[1537] The Generative AI analyzes the area, budget, and ratings to generate a list of the most suitable professional contractors for the selected design plan. For example, it selects three contractors based on the user's area, budget, and past ratings. The generated contractor list is then returned to the server.

[1538] Step 8:

[1539] The server presents the list of vendors returned by the AI ​​to the user, who then selects the vendor that best suits them. The list also includes detailed information and ratings for each vendor.

[1540] Step 9:

[1541] The server uses an emotion engine to recognize the user's emotions in real time based on the design plan and professional contractor information selected by the user, and this information is fed back to the generative AI.

[1542] Step 10:

[1543] The emotion engine analyzes emotions from facial expressions and voice when a user selects a design plan or browses a list of contractors, and sends the data to a server. For example, if a user smiles while looking at a plan, it determines that the emotion is positive.

[1544] Step 11:

[1545] Based on the feedback data from the emotion engine, the server asks the generative AI to adjust the design plan, for example, to generate a new plan that emphasizes elements that have been identified as generating positive emotions.

[1546] Step 12:

[1547] The server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in virtual space.

[1548] Step 13:

[1549] The VR module generates a 3D model based on the design plan, creates a virtual environment, and returns an access link to the virtual environment to the server.

[1550] Step 14:

[1551] The server provides users with an access link to the VR environment, through which they can experience the designed house in a virtual space.

[1552] Step 15:

[1553] The server constantly updates the progress and cost details of the construction process and displays them on the user interface. Users can check the progress and costs in real time and communicate with the builder if necessary. In addition, the emotion engine recognizes the user's emotions during this process and provides appropriate assistance and alerts.

[1554] Example 2

[1555] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1556] Conventional custom home design and construction systems have difficulty providing design plans that adequately reflect the complex needs and feelings of users. Furthermore, because individual processes such as proposing design plans, recommending specialist contractors, and providing virtual construction experiences are not integrated, the process is cumbersome and opaque for users. Furthermore, the lack of transparency in the management of the construction process and costs has led to a lack of security for users.

[1557] 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.

[1558] In this invention, the server includes means for acquiring user information, means for using artificial intelligence to generate a design plan based on the acquired user information, means for recommending a contractor based on the generated design plan, means for recognizing the user's emotions using an emotion engine and providing feedback based on the emotions, means for providing a virtual construction experience using virtual reality technology, and means for transparently managing information on the construction process and costs. This makes it possible to provide a design plan that reflects the user's emotions and needs, recommend the most suitable contractor, provide a virtual construction experience using real-time emotion feedback, and transparently manage the construction process and costs.

[1559] "User Information" refers to personal information about a User, such as family composition, budget, and housing preferences, that is necessary for the design and construction of a custom home.

[1560] "Artificial intelligence" refers to digital technology that uses machine learning and deep learning techniques to generate optimal home design plans based on user information.

[1561] "Specialist contractors" refer to the craftsmen and companies that actually carry out the construction and installation in the design and building of custom homes.

[1562] An "emotion engine" refers to technology that recognizes and analyzes the emotions of users in real time when using a system.

[1563] "Virtual reality technology" is a technology that provides an experience close to the real world in a digital space, and is used to allow users to experience a house before it is built in a virtual space.

[1564] "Virtual architectural experience" refers to the use of virtual reality technology to allow users to experience a home designed in a digital space in real time.

[1565] "Transparent information management" means providing users with real-time details about the construction process and costs, and sharing the latest information at all times, eliminating any opacity for users.

[1566] This is a system that allows users to easily design and build custom homes, and in particular, incorporates an emotion engine to provide optimal design plans and services that take user emotions into consideration. This system includes the processes of acquiring user information, generating design plans using AI, recommending professional contractors, providing a virtual building experience, and transparently managing the construction process and costs.

[1567] First, the server authenticates the user when they access the platform and provides them with a login form. If the user successfully logs in, a form is displayed for them to enter basic information such as their family composition, budget, and housing preferences. The user enters this information and sends it to the server. The server stores the submitted information in a database. This process uses a relational database management system such as the MySQL database.

[1568] Next, the server requests the generation AI to generate a design plan based on the acquired user information. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server. The server then presents the generated design plans to the user, allowing them to select one. The generation AI uses models such as GPT-3 that use deep learning technology.

[1569] Once the user selects a design plan, the server sends a request to the generation AI to recommend the most suitable specialist contractor. The generation AI analyzes the area, budget, and evaluation data, generates a list of the most suitable contractors, and returns it to the server. The server then presents this list to the user, who can then select the contractor that best suits them.

[1570] When selecting a design plan or experiencing a virtual building, the server uses an emotion engine to recognize the user's emotions in real time. The emotion engine analyzes the user's emotions using facial recognition technology (e.g., OpenCV) and voice analysis technology. This emotion data is fed back to the generative AI and other system components.

[1571] To provide a virtual architectural experience, the server passes the design plan created by the generation AI to the VR module and sends a request to recreate it in a virtual space. The VR module generates a 3D model based on the design plan using a 3D game engine such as Unity, creating a virtual environment. The server provides the user with an access link to the VR environment, allowing the user to experience the designed house in the virtual space through the link.

[1572] Furthermore, the server updates the progress and cost details of the construction process in real time and displays them on the user interface. Users can check this and communicate with the builder if necessary. The emotion engine recognizes the user's emotions during the construction process and provides appropriate assistance and alerts.

[1573] Prompt Sentence Examples

[1574] User information: Family composition (couple and two children), budget (50 million yen), housing preferences (modern, spacious kitchen)

[1575] Generate the best home design plan based on the user information above.

[1576] In this way, the system can provide design plans that reflect the user's emotions and needs, recommend professional contractors, provide a virtual building experience with real-time emotional feedback, and transparently manage the construction process and costs.

[1577] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1578] Step 1: Get user information

[1579] 1. The server initiates the authentication process when the user accesses the platform and displays a login form.

[1580] Input: User ID, Password

[1581] Output: Authentication result (success / failure), form display status

[1582] Specific behavior: Validates the authentication information and displays the next input form if the user successfully logs in.

[1583] 2. The user enters the required information into the login form and presses the submit button.

[1584] Input: User ID, Password

[1585] Output: User authentication request

[1586] Specific operation: Sends authentication information to the server.

[1587] 3. The server verifies the authentication information entered and, if successful, displays a form for entering basic information such as family composition, budget, and housing preferences.

[1588] Input: User authentication request

[1589] Output: User information input form

[1590] Specific operation: Check the database and dynamically generate the next form depending on the authentication result.

[1591] 4. The user enters basic information and presses the send button.

[1592] Inputs: Family composition, budget, housing preferences

[1593] Output: User information request

[1594] Specific operation: Send basic information to the server.

[1595] 5. The server stores the entered user information in a database.

[1596] Input: User Information Request

[1597] Output: Status of saving to database

[1598] What it does: Stores user information using a relational database management system such as a MySQL database.

[1599] Step 2: Generate a design plan

[1600] 1. The server requests the generation AI to generate a design plan based on the stored user information.

[1601] Input: User information

[1602] Output: Design plan generation request

[1603] Specific operation: A Python program is used to call the generative AI's API and send a prompt containing user information.

[1604] 2. The generation AI generates the optimal home design plan based on the user's preferences and budget and returns it to the server.

[1605] Input: Design plan generation request

[1606] Output: Generated house design plan

[1607] Specific operation: Generate a design plan using deep learning technology (e.g., GPT-3).

[1608] 3. The server presents the generated design plans to the user for selection.

[1609] Input: Generated house design plan

[1610] Output: Present the design plan to the user

[1611] What it does: Display the design plan on a web page or application interface.

[1612] Step 3: Professional Recommendations

[1613] 1. The user selects one of the presented design plans.

[1614] Input: Multiple design plans

[1615] Output: Selected design plan

[1616] Specific behavior: Review the design plans and select the best one.

[1617] 2. The server sends a request to the generating AI to generate a list of the most suitable specialists based on the design plan information selected by the user.

[1618] Input: Selected design plan information

[1619] Output: Contractor selection request

[1620] Specific operation: Include vendor evaluation data in the prompt text sent to the generation AI.

[1621] 3. The generative AI analyzes the region, budget, and rating data to create a list of optimal contractors and return it to the server.

[1622] Input: Contractor selection request

[1623] Output: A list of the best specialists

[1624] Specific operation: Select the best vendor using a machine learning algorithm.

[1625] 4. The server presents this list of vendors to the user.

[1626] Input: List of best professional contractors

[1627] Output: Present a list of vendors to the user

[1628] What it does: Displays a list of vendors on a web page or application interface.

[1629] 5. The user selects the appropriate provider from the list.

[1630] Input: Professional Contractor List

[1631] Output: Selected vendor information

[1632] Specific actions: Check the vendor list and select the appropriate vendor.

[1633] Step 4: Implementing the Emotion Engine

[1634] 1. The server runs an emotion engine that recognizes the user's emotions in real time as they select design plans and engage in virtual architectural experiences.

[1635] Input: Real-time user data (face data, voice data)

[1636] Output: User emotion data

[1637] What it does: Captures real-time facial and audio data using a webcam and microphone.

[1638] 2. The emotion engine analyzes the user's facial recognition data and voice data to determine their emotional state.

[1639] Input: Real-time face data, voice data

[1640] Output: User emotion judgment result

[1641] Specific operation: Analyzes emotion data using OpenCV and speech analysis libraries.

[1642] 3. The server feeds this emotion data back to system components such as generative AI, triggering corresponding actions.

[1643] Input: User's emotion judgment result

[1644] Output: Feedback data, trigger actions

[1645] Specific behavior: Dynamically change the content of the user interface based on emotion data.

[1646] Step 5: Providing a virtual building experience

[1647] 1. The server passes the design plan created by the generation AI to the VR module and sends a request to reproduce it in virtual space.

[1648] Input: User design plan

[1649] Output: Virtual space generation request

[1650] Specific operation: Calls the API to send data to the VR module.

[1651] 2. The VR module generates a 3D model based on the design plan and creates a virtual environment.

[1652] Input: User design plan

[1653] Output: The generated virtual environment

[1654] Specific operation: Build a virtual environment using a 3D game engine such as Unity.

[1655] 3. The server provides the user with an access link to this VR environment.

[1656] Input: The generated virtual environment

[1657] Output: VR environment access link to user

[1658] What it does: Generates a link and sends it to the user's account.

[1659] 4. Users can experience the designed home in a virtual space via a VR headset or PC via the link.

[1660] Input: VR environment access link

[1661] Output: Virtual architectural experience

[1662] Specific action: Experience a virtual space using a VR device such as Oculus Rift or HTC Vive.

[1663] Step 6: Transparent management and support

[1664] 1. The server updates the construction progress and cost details in real time and displays them in the user interface.

[1665] Input: Construction process data, cost data

[1666] Output: Displaying progress and costs

[1667] Specific actions: Visualize progress and cost data using tools such as Google Charts.

[1668] 2. Users can view progress and cost details and communicate with the builder if necessary.

[1669] Input: View progress and costs

[1670] Output: User feedback and communication requests

[1671] What it does: Check progress and cost details, and send questions if you have any questions.

[1672] 3. The Emotion Engine recognizes users' emotions in real time during the construction process and provides appropriate assistance and alerts.

[1673] Input: Real-time user data (face data, voice data)

[1674] Output: Support message, alert notification

[1675] Specific behavior: Display appropriate motivational messages and alerts to users based on emotional data.

[1676] (Application example 2)

[1677] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1678] Conventional custom home design systems proposed plans based on the user's preferences and budget, but they lacked the ability to adjust design plans based on the user's emotions or optimize the design through a virtual construction experience. Therefore, a new proposal method was needed to increase user satisfaction. Furthermore, transparency in the design and construction processes was insufficient, making it difficult for users to collaborate with trusted contractors.

[1679] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user information, means for using a generation AI to generate a design plan based on the acquired user information, means for recommending a professional contractor based on the generated design plan, means for providing a virtual construction experience using virtual reality technology, means for transparently managing information on the construction process and costs, means for using an emotion engine to recognize the user's emotions in real time and adjust the design plan based on the results, means for experiencing a home designed in a virtual space based on the generated design plan, and means for providing feedback on the user's emotions during the virtual space experience and for the generation AI to optimize the design plan. This enables optimal proposals and adjustments that take the user's emotions into consideration, thereby improving user satisfaction. Furthermore, transparent management enhances user trust and enables smooth collaboration with contractors.

[1680] "User information" refers to basic information such as the user's family composition, budget, preferences, etc.

[1681] "Design plan" refers to a proposed house design based on user information.

[1682] "Generative AI" refers to artificial intelligence (AI) that creates design plans based on user information.

[1683] "Specialist contractor" refers to a contractor that carries out construction and installation based on a design plan.

[1684] "Virtual reality technology" refers to the technology of creating a virtual space that resembles reality using computer technology.

[1685] "Virtual architectural experience" refers to the use of virtual reality technology to allow users to experience the design of a home in a virtual space.

[1686] An "emotion engine" is an engine that uses technologies such as facial recognition and voice analysis to recognize and analyze users' emotions in real time.

[1687] "Cost information" refers to details of various costs and budgets incurred during the construction process.

[1688] "Transparent management" means presenting information to users clearly and in real time, eliminating opacity.

[1689] "Virtual space" refers to a three-dimensional digital space generated within a computer using virtual reality technology.

[1690] "Feedback" refers to collecting user emotional data and providing information to adjust design plans based on that data.

[1691] "Optimizing" refers to adjusting proposals and plans to the best possible state based on the user's feelings and desires.

[1692] The following system configuration is shown as an embodiment of this invention. The invention includes a generation AI that acquires user information and generates an optimal design plan based on it, recommendation of specialist contractors, a virtual building experience using virtual reality technology, real-time feedback by an emotion engine, and transparent management.

[1693] System Program

[1694] The system mainly consists of the following hardware and software:

[1695] User device: smartphone, tablet, or computer

[1696] Server: Cloud server (AWS, Google Cloud, etc.)

[1697] Generative AI models: Natural language processing models such as GPT-3 and Claude

[1698] Emotion engine: Emotion recognition software such as Affectiva SDK

[1699] AR Platform: Apple ARKit, Google ARCore

[1700] Retrieving User Information

[1701] Users log in to the app using their devices and enter basic information (family composition, budget, preferences, etc.). This information is sent from the user's device to the server, which then stores the received information in a cloud database.

[1702] Generative AI creates design plans

[1703] The server sends the saved user information to the generative AI model and requests it to generate an optimal design plan. The generative AI model generates a design plan that matches the user's preferences and budget and returns it to the server. The server displays this design plan to the user.

[1704] Professional recommendation

[1705] After the user selects a design plan, the server will ask the AI ​​to generate a list of the most suitable specialists based on factors such as area, budget, and reputation. This list will be presented to the user, who can then select the contractor that best suits them.

[1706] Feedback using an emotion engine

[1707] As users select a design plan and experience the virtual building process, their emotions are monitored in real time via the user's device's camera and microphone. The emotion engine analyzes the collected data and determines the user's emotions. The server sends the emotion engine's results to the generation AI, which adjusts the design plan based on the feedback. For example, if the user responds positively to a proposed design, a new plan is generated that emphasizes those elements.

[1708] Providing a virtual building experience and transparent management

[1709] The server sends the design plan created by the generative AI to the user's device via the AR platform, allowing them to experience the designed home in a virtual space. Users can virtually place the home using the AR function of their smartphone or tablet and check the feel of it in the real environment. In addition, transparent management of the construction process and costs allows users to check the project progress and costs in real time.

[1710] Examples of specific examples and prompts

[1711] For example, if a user attempts to arrange furniture in a virtual space and expresses their feelings about the arrangement, for example, "If I put a sofa here, it would feel more spacious," the generative AI will use that emotion data to suggest new furniture arrangements.

[1712] Example prompt sentence:

[1713] "A user looks at the proposed furniture arrangement and says, 'If I put a sofa here, it would feel even bigger.' Suggest a new furniture arrangement that reflects this."

[1714] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1715] Step 1:

[1716] Users log in to the application using their devices and enter basic information such as family composition, budget, and housing preferences into the login form. This information is sent from the user device to the server and stored in a cloud database.

[1717] Input: User's basic information (family structure, budget, preferences, etc.)

[1718] Output: User information stored in a cloud database

[1719] Specific operation: The user enters the required information into the form presented on the smartphone or tablet and presses the "Submit" button.

[1720] Step 2:

[1721] The server acquires user information and sends it to a generative AI model, which generates a design plan based on the user's preferences and budget and sends it back to the server.

[1722] Input: User information stored in a cloud database

[1723] Output: Design plans generated by the generative AI

[1724] Specific operation: The server sends an appropriate prompt to the generation AI, which processes the user's information to create the optimal design plan.

[1725] Step 3:

[1726] The server sends the design plans received from the generative AI model to the user's device and displays them to the user, who then checks the presented design plans and makes a selection.

[1727] Input: Design plan returned from the generative AI

[1728] Output: Design plan displayed on the user's device

[1729] Specific operation: The server generates the design plan in HTML format and displays it to the user through a web interface.

[1730] Step 4:

[1731] After the user selects a design plan, the server again sends a request to the generative AI model to recommend a specialist contractor. The generative AI model then lists the most suitable specialist contractors based on location, budget, reputation, etc., and sends the list back to the server.

[1732] Input: User selected design plan and user information

[1733] Output: A list of the best professionals

[1734] Specific operation: The server again sends the prompt sentence to the generation AI model, which generates a list of candidate specialists based on the design plan.

[1735] Step 5:

[1736] The server sends a list of specialists to the user terminal and displays it to the user, allowing the user to select from the list.

[1737] Input: A list of specialists returned by the generation AI

[1738] Output: A list of specialists displayed on the user's device

[1739] Specific operation: The user selects a suitable vendor from the presented list of vendors.

[1740] Step 6:

[1741] While reviewing design plans and experiencing the virtual world, the user's emotions are observed in real time using the camera and microphone on the user's device. The emotion engine analyzes this data and determines the user's emotions.

[1742] Input: User's facial expression and voice data

[1743] Output: Analyzed user emotion data

[1744] How it works: Using the smartphone's camera and microphone, the emotion engine analyzes this data to identify emotions.

[1745] Step 7:

[1746] The server sends the results of the emotion engine to the generative AI, which then adjusts the design plan, for example, highlighting design elements for which users expressed positive emotions and improving negative elements.

[1747] Input: Analyzed emotion data, user information

[1748] Output: New adjusted design plan

[1749] Specific operation: The server uses a prompt statement to ask the generation AI to create a new design plan.

[1750] Step 8:

[1751] The server sends the new design plan adjusted by the generative AI to the user's device via the AR platform, providing an experience in a virtual space.

[1752] Input: New design plan adjusted by the generative AI

[1753] Output: Virtual experience displayed on the user's device

[1754] Specific operation: The user uses the AR function of their smartphone to virtually experience new design plans.

[1755] Step 9:

[1756] The server manages the progress and costs of the construction process in real time and displays them on the user's device, allowing the user to constantly check the progress and costs of the project.

[1757] Input: Construction process and cost information

[1758] Output: Real-time progress and cost information displayed on the user's device

[1759] What it does: The server uses a project management tool to monitor progress and costs, and displays that information to the user in HTML format.

[1760] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1761] 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.

[1762] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1763] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1764] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1765] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1766] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1767] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1768] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1769] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1770] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1771] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1772] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1773] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1774] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1775] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1776] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1777] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1778] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1779] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1780] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1781] The following is further disclosed regarding the above embodiment.

[1782] (Claim 1)

[1783] A means for obtaining user information;

[1784] A means for using a generation AI to generate a design plan based on the acquired user information;

[1785] A means for recommending a specialist contractor based on the generated design plan;

[1786] A means for providing a virtual architectural experience using virtual reality technology;

[1787] A means of transparently managing information on the construction process and costs;

[1788] A system including:

[1789] (Claim 2)

[1790] The system of claim 1 , further comprising: means for displaying the generated design plan.

[1791] (Claim 3)

[1792] 10. The system of claim 1, further comprising means for displaying a list of recommended professionals and allowing a user to select from the list.

[1793] "Example 1"

[1794] (Claim 1)

[1795] A means for obtaining user information;

[1796] A means for using a generation AI to generate a design plan based on the acquired user information;

[1797] A means for sending a design plan creation request to the generation AI;

[1798] a means for presenting the generated design plan to a user;

[1799] A means for recommending a specialist contractor based on the generated design plan;

[1800] a means for presenting a list of recommended vendors to the user;

[1801] A means for providing a virtual architectural experience using virtual reality technology;

[1802] A means of transparently managing information on the construction process and costs;

[1803] A system including:

[1804] (Claim 2)

[1805] The system of claim 1 , further comprising: means for displaying the generated design plan.

[1806] (Claim 3)

[1807] 10. The system of claim 1, further comprising means for displaying a list of recommended professionals and allowing a user to select from the list.

[1808] "Application Example 1"

[1809] (Claim 1)

[1810] A means for obtaining user information;

[1811] A means for using a generation AI to generate a design plan based on the acquired user information;

[1812] A VR module is a means of displaying the generated design plan as a 3D model using virtual reality technology;

[1813] A means for using the generative AI to recommend a contractor based on the generated design plan;

[1814] A means for providing a virtual architectural experience using virtual reality technology;

[1815] A means of transparently managing information on the construction process and costs;

[1816] means for acquiring user location information using a location identification device;

[1817] a means for displaying information using smart glasses;

[1818] A system including:

[1819] (Claim 2)

[1820] The system of claim 1 , further comprising: means for displaying the generated design plan.

[1821] (Claim 3)

[1822] 10. The system of claim 1, further comprising means for displaying a list of recommended professionals and allowing a user to select from the list.

[1823] "Example 2: Combining Emotion Engines"

[1824] (Claim 1)

[1825] A means for obtaining user information;

[1826] A means using artificial intelligence to generate a design plan based on the acquired user information;

[1827] A means for recommending a specialist contractor based on the generated design plan;

[1828] a means for recognizing a user's emotions using an emotion engine and providing feedback based thereon;

[1829] A means for providing a virtual architectural experience using virtual reality technology;

[1830] A means of transparently managing information on the construction process and costs;

[1831] A system including:

[1832] (Claim 2)

[1833] The system of claim 1 , further comprising: means for displaying the generated design plan.

[1834] (Claim 3)

[1835] 10. The system of claim 1, further comprising means for displaying a list of recommended professionals and allowing a user to select from the list.

[1836] "Application example 2 when combining emotion engines"

[1837] (Claim 1)

[1838] A means for obtaining user information;

[1839] A means for using a generation AI to generate a design plan based on the acquired user information;

[1840] A means for recommending a specialist contractor based on the generated design plan;

[1841] A means for providing a virtual architectural experience using virtual reality technology;

[1842] A means of transparently managing information on the construction process and costs;

[1843] Using an emotion engine that recognizes user emotions in real time and adjusts design plans based on the results.

[1844] A means to experience a house designed in a virtual space based on the generated design plan, and

[1845] A means for generative AI to optimize design plans based on user feedback during vi...

Claims

1. A means for obtaining user information; A means for using a generation AI to generate a design plan based on the acquired user information; A means for recommending a specialist contractor based on the generated design plan; A means for providing a virtual architectural experience using virtual reality technology; A means of transparently managing information on the construction process and costs; A system including:

2. The system of claim 1 further comprising means for displaying the generated design plan.

3. 10. The system of claim 1, further comprising means for displaying a list of recommended professionals and allowing a user to select from the list.

Images