system

Abstract

Provide a system. 【Solution means】 Means for inputting the conditions of the land desired by the user, Means for crawling the land database based on the above conditions and obtaining land information that meets the conditions, Means for filtering the obtained land information and selecting the optimal land, Means for notifying the user of the selected land information, Means for automatically generating drawings based on the above land information, Means for inputting a request for modification to the above drawings, Means for regenerating the drawings based on the above modification request, Means for recommending furniture based on the above drawings, A system including the above.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, in the services provided by real estate and housing manufacturers to customers, it has been difficult to quickly and efficiently find the optimal land based on the conditions desired by the user. Also, the work of creating drawings based on the selected land information is time-consuming, and it is difficult to quickly respond to correction requests. Furthermore, it has been complicated to make appropriate furniture recommendations based on the drawings. To solve such problems, a system that consistently performs from land selection to drawing creation, correction, and furniture recommendation has been demanded.

Means for Solving the Problems

[0005] The present invention solves the above problems with a system that includes means for the user to input desired land conditions, means for crawling a land database based on the conditions and obtaining land information that matches the conditions, means for filtering the obtained land information and selecting the optimal land, means for notifying the user of the selected land information, means for automatically generating drawings based on the land information, means for inputting revision requests for the drawings, means for regenerating the drawings based on the revision requests, and means for recommending furniture based on the drawings. This makes it possible to quickly and efficiently select the optimal land that matches the user's conditions and consistently provide appropriate drawings and furniture recommendations.

[0006] A "user" is an individual or group that uses the system to input land conditions and receives land information, drawings, and furniture recommendations.

[0007] "Conditions" refer to criteria such as the price, area, location, and surrounding environment of the land desired by the user.

[0008] A "land database" is a database that stores and allows users to search for land information.

[0009] "Crawling" is the process by which a system automatically traverses a database to retrieve the latest land information.

[0010] "Filtering" is the process of narrowing down acquired land information to those that match the user's criteria.

[0011] "Recommended land" refers to land that has been deemed optimal from the filtered land information.

[0012] "Notification" is the process by which the system informs the user of land information it has selected.

[0013] "Drawings" include basic design drawings and elevation drawings of a building designed based on the land.

[0014] "Revision Request" refers to the content that the user wishes to change or add to the drawing.

[0015] "Regeneration" is the operation of creating the drawing again based on the revision request.

[0016] "Furniture Recommendation" proposes appropriate furniture and its arrangement based on the completed drawing.

[0017] "System" refers to the technical combination that consistently performs land recommendation, drawing creation and modification, and furniture recommendation from the user's condition input.

Brief Explanation of Drawings

[0018] [Figure 1] It is a conceptual diagram showing an example of the configuration of the data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of the data processing device and the smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of the data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of the data processing device and the smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of the data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of the data processing device and the headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of the data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of the data processing device and the robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] System Configuration

[0040] An embodiment of the present invention consists of a terminal in which the user inputs the desired land conditions, a server that crawls a land database, acquires and filters land information that matches the conditions, and selects the most suitable land, and a server and terminal that automatically generate and modify drawings based on the land information and further recommend furniture.

[0041] System processing flow

[0042] 1. Enter conditions

[0043] Operator: User

[0044] Operation: The user enters the desired land conditions (price, area, location, surrounding environment, etc.) using a form displayed on the terminal, and then presses the submit button to send that information to the server.

[0045] 2. Acquisition of land information

[0046] Operating entity: Server

[0047] Operation: Based on the user's specified conditions, the server periodically crawls the land database and retrieves the latest land information that matches those conditions.

[0048] 3. Filtering land information

[0049] Operating entity: Server

[0050] Operation: The server filters land information acquired based on user criteria and selects suitable land information.

[0051] 4. Notification of land information

[0052] Operating entity: Server

[0053] Operation: The server notifies the user's terminal of information about the selected suitable land. This notification includes detailed information about the land (location, price, area, etc.).

[0054] 5. Automatic generation of recommended drawings

[0055] Operating entity: Server

[0056] Operation: Based on the notified land information, the server automatically generates basic drawings and elevations using dedicated CAD software.

[0057] 6. Revision of drawings

[0058] Operator: User

[0059] Operation: The user reviews the generated drawing via the terminal and enters any necessary revision requests.

[0060] 7. Generation of revised drawings

[0061] Operating entity: Server

[0062] Operation: The server receives a correction request from the user and regenerates the drawing based on the correction. The regenerated drawing is then sent back to the user's terminal.

[0063] 8. Furniture Recommendations

[0064] Operating entity: Server

[0065] Operation: Based on the completed drawings, the server recommends the most suitable furniture and its placement from an online furniture catalog. The recommendation information is sent to the user's device.

[0066] Specific example

[0067] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[0068] 1. Enter the conditions:

[0069] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[0070] 2. Obtaining land information:

[0071] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[0072] 3. Filtering land information:

[0073] Based on the land information acquired by the server, the system recommends suitable land in Shinjuku Ward to the user.

[0074] 4. Notification of land information:

[0075] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[0076] 5. Automatic generation of recommended drawings:

[0077] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward and sends them to the user.

[0078] 6. Revision of drawings:

[0079] The user enters a modification request stating, "I would like the living room to be a little larger."

[0080] 7. Generating revised drawings:

[0081] The server receives the correction request, regenerates the drawing, and resends it to the user.

[0082] 8. Furniture Recommendations:

[0083] The server recommends furniture such as sofas and tables suitable for a living room based on the floor plan, and sends the recommendations to the user's terminal.

[0084] In this way, the system of the present invention can efficiently perform a consistent process from land selection to drawing creation, modification, and furniture recommendation, based on the user's requirements.

[0085] The following describes the processing flow.

[0086] Step 1:

[0087] The user uses the input form displayed on the terminal to enter the desired land conditions (price, area, location, surrounding environment, etc.) and presses the submit button. The terminal then sends these conditions to the server.

[0088] Step 2:

[0089] The server crawls the real estate database based on the user's criteria received. The crawling process is performed periodically to retrieve the latest land information.

[0090] Step 3:

[0091] The server crawls and retrieves land information, which is then filtered based on the user's criteria. This filtering process selects land information that meets the specified conditions.

[0092] Step 4:

[0093] The server selects the most suitable land from the filtered land information. The selection criteria include user conditions as well as evaluation criteria pre-configured on the server.

[0094] Step 5:

[0095] The server notifies the user's terminal of the land information it has selected. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[0096] Step 6:

[0097] The user's device receives and displays a notification from the server. The user then reviews the presented land information.

[0098] Step 7:

[0099] Based on the recommended land information, the server automatically generates basic drawings and elevations using specialized CAD software.

[0100] Step 8:

[0101] The server automatically generates drawings and elevations and sends them to the user's terminal. The terminal then displays the received drawings.

[0102] Step 9:

[0103] The user reviews the provided drawings and enters any necessary revision requests. Examples of revision requests include changes to room size or layout. The user then submits the revision requests.

[0104] Step 10:

[0105] The server receives a modification request from the user and regenerates the drawing using CAD software. The regenerated drawing is based on the modification request.

[0106] Step 11:

[0107] The server sends the regenerated drawing back to the user's terminal. The terminal displays the corrected drawing.

[0108] Step 12:

[0109] Based on the completed drawings, the server crawls online furniture catalogs to retrieve furniture information suitable for those drawings. Factors such as furniture type, size, and design are taken into consideration.

[0110] Step 13:

[0111] The server sends a list of selected furniture and recommended placement suggestions to the user's device. The device then displays the furniture recommendations.

[0112] Step 14:

[0113] Users review the recommended furniture and make final adjustments to purchases and placement as needed.

[0114] (Example 1)

[0115] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0116] When purchasing a modern home, many users spend considerable time and effort finding suitable land, creating optimal blueprints, and then selecting furniture. Traditional methods fragment the process, requiring users to interact with multiple platforms and vendors at each stage, as these tasks—land information gathering and filtering, blueprint creation and revision, and furniture selection—are disconnected. This process is inefficient and often leads to lower overall satisfaction. Furthermore, challenges include the inability to obtain suitable land information in a timely manner and the cumbersome process of revising blueprints.

[0117] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0118] In this invention, the server includes means for the user to input desired land conditions, means for crawling a land database based on the conditions and obtaining land information that matches the conditions, and means for filtering the obtained land information and selecting the optimal land. This allows the user to efficiently obtain desired land information and receive automatically generated blueprints and recommendations for optimal furniture based on that information. This enables the entire process from land selection to blueprint creation and furniture selection to be carried out efficiently in one go, thereby improving user satisfaction.

[0119] A "user" is an entity that uses this system to input desired land conditions and receives selected land information, blueprints, and furniture recommendations.

[0120] "Means for inputting conditions" refers to a device or system that provides an interface for users to input detailed conditions of land they desire (such as price, area, location, and surrounding environment).

[0121] A "land database" is a source of information that stores information on multiple plots of land and is used to retrieve land information that meets specific criteria through crawling.

[0122] "Crawling" refers to a software technology that involves a program or a series of operations for automatically collecting information from land databases on the internet.

[0123] "Filtering methods" refer to software algorithms used to select information that matches the user's input criteria from the acquired land information.

[0124] "Land information" refers to information about a specific piece of land, including details such as location, price, and area.

[0125] "Notification means" refers to communication methods for sending filtered land information to the user's device. This includes methods such as email and push notifications.

[0126] A "design drawing" is a diagram that shows the basic layout and structure of a building to be constructed on a desired plot of land.

[0127] "Means of automatic generation" refers to an algorithm or program that automatically creates building blueprints using specific software (e.g., CAD software) based on input land information.

[0128] A "means for inputting modification requests" refers to a system that provides an interface for users to review generated blueprints and input necessary changes or modifications.

[0129] A "means of regeneration" refers to a software algorithm for recreating the design blueprint to reflect the modification requests.

[0130] "A means of recommending furniture" refers to software that suggests appropriate furniture and its placement based on a completed blueprint.

[0131] The "reporting database" is a database used to temporarily store suitable land information after filtering.

[0132] "Means for generating furniture arrangement plans" refers to algorithms or software for creating the optimal furniture arrangement based on a completed design drawing.

[0133] An embodiment of the present invention consists of a terminal in which the user inputs desired land conditions, a server that crawls a land database to acquire and filter land information that matches the conditions and select the most suitable land, and a server and terminal that automatically generate and modify building blueprints based on the land information and further recommend furniture.

[0134] Hardware and software to be used

[0135] Terminal: A client device used by the user to operate the system (PC, tablet, smartphone, etc.)

[0136] Server: A central server that processes user input and performs tasks such as data retrieval, filtering, notifications, diagram generation, and recommendations.

[0137] Software and libraries to be used:

[0138] Web browser: Provides an interface for users to enter conditions.

[0139] Python: A programming language used for data crawling.

[0140] Beautiful Soup, Selenium: Libraries for crawling land databases

[0141] SQL (MySQL (registered trademark), PostgreSQL, etc.): Database management system

[0142] AutoCAD API: CAD software for automatically generating building blueprints.

[0143] Email sending API, push notification API: Communication methods for notifying users of land information and map URLs.

[0144] IKEA API, Amazon API: Online catalogs for recommending furniture

[0145] Explanation of the processing flow

[0146] 1. Enter conditions

[0147] Operator: User

[0148] Specific operation: The user opens a web page on their device, enters details of the desired land (price, area, location, surrounding environment, etc.) into a form, and clicks the submit button to send it to the server.

[0149] 2. Acquisition of land information

[0150] Operating entity: Server

[0151] Specific operation: The server uses Python to crawl a specified land database using Beautiful Soup or Selenium, retrieves land information that meets the criteria, and stores it in a temporary storage database.

[0152] 3. Filtering land information

[0153] Operating entity: Server

[0154] Specific operation: The server reads data retrieved from a temporary storage database and filters it based on user criteria. The filtered data is then saved to the reporting database as matching land information.

[0155] 4. Notification of land information

[0156] Operating entity: Server

[0157] Specific operation: The server uses email sending APIs and push notification APIs to notify users of filtered land information.

[0158] 5. Automatic generation of recommended drawings

[0159] Operating entity: Server

[0160] Specific operation: The server uses the AutoCAD API to automatically generate basic house drawings and elevations based on the provided land information. The generated drawings are saved on the server, and the URL is notified to the user.

[0161] 6. Revision of drawings

[0162] Operator: User

[0163] Specific operation: The user opens the notified URL and enters a request to review and modify the drawing. The modification request is sent to the server.

[0164] 7. Generation of revised drawings

[0165] Operating entity: Server

[0166] Specific operation: The server receives the correction request, regenerates the drawing using the AutoCAD API, and notifies the user again.

[0167] 8. Furniture Recommendations

[0168] Operating entity: Server

[0169] Specific operation: Based on the completed drawing, the server retrieves information on suitable furniture from the IKEA API and Amazon API, and notifies the user of the recommended furniture.

[0170] Specific example

[0171] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[0172] 1. Enter the conditions:

[0173] The user enters the following conditions on their device: "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Convenient transportation," and sends it to the server.

[0174] 2. Obtaining land information:

[0175] The server uses Python's Beautiful Soup to crawl the land database and finds a 120 square meter plot of land in Shinjuku Ward.

[0176] 3. Filtering land information:

[0177] The server filters the acquired land information, selects land information that meets the specified criteria, and saves it to the reporting database.

[0178] 4. Notification of land information:

[0179] The server uses an email API to notify users of selected land information (e.g., 120 square meters in Shinjuku Ward, priced at 30 million yen).

[0180] 5. Automatic generation of recommended drawings:

[0181] The server uses the AutoCAD API to automatically generate design drawings and elevation drawings based on the acquired land information, and notifies the user of the URL.

[0182] 6. Revision of drawings:

[0183] The user opens the URL they were notified with, enters a modification request such as "I want the living room to be a little bigger," and sends it to the server.

[0184] 7. Generating revised drawings:

[0185] The server receives the correction request, uses the AutoCAD API again to generate the corrected drawing, and notifies the user again.

[0186] 8. Furniture Recommendations:

[0187] The server uses the Amazon API to recommend furniture suitable for the generated drawings to the user.

[0188] Examples of prompts for generative AI models

[0189] The following are examples of prompt statements to input into the generative AI model.

[0190] "For users searching for land in Tokyo with a budget of 30 million yen, over 100 square meters, and convenient transportation access, please acquire, filter, and recommend appropriate land information. Furthermore, generate basic house plans based on the land, update the plans according to user requests, and finally, recommend furniture."

[0191] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0192] Step 1:

[0193] Condition Input

[0194] Operator: User

[0195] Specific actions:

[0196] The user starts up their device and opens the system's webpage in their browser. They enter their desired land conditions (price, area, location, surrounding environment, etc.) into the form. They click the "Submit" button to send the conditions to the server.

[0197] input:

[0198] Desired land conditions (price, area, location, surrounding environment, etc.)

[0199] output:

[0200] The entered conditions are sent to the server.

[0201] Step 2:

[0202] Acquisition of land information

[0203] Operating entity: Server

[0204] Specific actions:

[0205] The server receives the conditions sent by the user. Using Python libraries (such as Beautiful Soup or Selenium), it crawls the specified land database and retrieves the latest land information that matches the conditions. The retrieved land information is stored in a temporary storage database.

[0206] input:

[0207] Land conditions entered by the user

[0208] output:

[0209] Land information stored in a temporary storage database

[0210] Step 3:

[0211] Land information filtering

[0212] Operating entity: Server

[0213] Specific actions:

[0214] The server reads data retrieved from a temporary storage database and filters it using SQL queries based on user criteria. Based on the filtering results, it selects suitable land information and saves it to the reporting database.

[0215] input:

[0216] Land information stored in a temporary storage database

[0217] output:

[0218] Save filtered land information to the reporting database.

[0219] Step 4:

[0220] Land information notification

[0221] Operating entity: Server

[0222] Specific actions:

[0223] The server prepares to send notifications to users based on the filtered land information. It uses email sending APIs and push notification APIs to send the filtered land information to the user's device.

[0224] input:

[0225] Filtered land information stored in the reporting database

[0226] output:

[0227] Notifications to the user's device

[0228] Step 5:

[0229] Automatic generation of recommended drawings

[0230] Operating entity: Server

[0231] Specific actions:

[0232] Based on the provided land information, the server automatically generates basic house plans and elevations using the AutoCAD API. The generated plans are saved as image files on the server, and a URL for the plans is generated. This URL is then notified to the user.

[0233] input:

[0234] Land information stored in the reporting database

[0235] output:

[0236] Notification containing the URL of the generated drawing

[0237] Step 6:

[0238] Drawing revisions

[0239] Operator: User

[0240] Specific actions:

[0241] The user opens the URL of the drawing notified from the server using their device. They review the drawing and enter revision requests using the form or comment function. Revision requests are sent from the device to the server in real time.

[0242] input:

[0243] User correction request

[0244] output:

[0245] Correction request sent to the server

[0246] Step 7:

[0247] Generation of revised drawings

[0248] Operating entity: Server

[0249] Specific actions:

[0250] The server receives the user's modification request and uses the AutoCAD API, etc., again to regenerate the drawing that reflects the modifications. The URL of the regenerated drawing is then sent to the user's device again.

[0251] input:

[0252] User correction request

[0253] output:

[0254] Notification including the URL of the revised drawing

[0255] Step 8:

[0256] Furniture recommendations

[0257] Operating entity: Server

[0258] Specific actions:

[0259] The server crawls online furniture catalogs (such as the IKEA API and Amazon API) based on the completed drawings. It selects furniture suitable for the drawings and generates optimal furniture and layout plans. This recommendation information is then notified to the user's device.

[0260] input:

[0261] Completed drawings

[0262] output:

[0263] Furniture recommendation information sent to the user's device.

[0264] (Application Example 1)

[0265] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0266] Conventional land selection and drawing creation systems made it difficult for users to visually understand the area's layout during the process from inputting desired land conditions to modifying automatically generated drawings. Furthermore, the detailed information provided after land selection, including furniture placement suggestions, was limited, resulting in a poor user experience. To address this issue, there is a need for a more visual and interactive land selection and drawing generation system.

[0267] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0268] In this invention, the server includes means for inputting the land conditions desired by the user, means for crawling a real estate database based on the conditions and obtaining land information that meets the conditions, means for filtering the obtained land information and selecting the optimal land, means for notifying the user of the selected land information, means for automatically generating a drawing based on the land information, means for inputting a request for modification to the drawing, means for regenerating the drawing based on the modification request, means for recommending furniture based on the drawing, and means for providing real estate information as a 3D virtual tour based on the conditions input by the user and the selected land. This enables the user to select land and customize the drawing in a visual and interactive manner, and to receive more detailed information and suggestions for appropriate furniture placement.

[0269] "A means for users to input their desired land conditions" refers to an interface or form that allows users to input their desired conditions regarding land, such as specific price, area, location, and surrounding environment.

[0270] "Methods for crawling real estate databases and obtaining land information that meets the criteria" refers to programs or algorithms that automatically collect land information from the internet or specific databases based on conditions entered by the user.

[0271] "Methods for filtering acquired land information and selecting the most suitable land" refers to the process or algorithm used to narrow down collected land information according to the user's desired conditions and select the land that best meets those conditions.

[0272] "Means of notifying users of selected land information" refers to a system that notifies users of detailed information about selected land via email, in-app messages, or other means.

[0273] "Methods for automatically generating drawings based on land information" refers to the process of automatically creating drawings using specialized design software based on selected land.

[0274] "Means for inputting modification requests for drawings" refers to interfaces or forms that allow users to input changes or modifications to generated drawings.

[0275] "Means for regenerating drawings based on revision requests" refers to programs or algorithms that automatically regenerate drawings, reflecting revision requests entered by the user.

[0276] "Methods for recommending furniture based on drawings" refers to processes and algorithms that automatically suggest the optimal furniture and its placement based on completed drawings.

[0277] "A means of providing real estate information as a 3D virtual tour" refers to a system that allows users to visually tour a property using virtual reality or 3D simulation technology, based on selected land plots and generated blueprints.

[0278] This invention is a system that allows users to input their desired land conditions, crawls a land database based on those conditions, retrieves and filters land information that matches the conditions, and selects the most suitable land. Furthermore, it can automatically generate drawings based on the selected land information, regenerate them according to the user's modification requests, and recommend furniture based on the completed drawings. It also includes a function to provide users with real estate information as a 3D virtual tour.

[0279] The server receives the user's input criteria and crawls information from the internet or specific real estate databases. The crawl results are filtered, and land information that matches the criteria is collected. This allows the server to provide users with accurate and timely detailed information about the land they desire.

[0280] The server automatically generates architectural drawings based on land information. This process utilizes specialized computer-aided design (CAD) software to plan based on the shape and area of ​​the selected land. The CAD software streamlines the drawing generation process and provides highly accurate drawings.

[0281] The user can review the generated drawing and enter any necessary revision requests. The server receives this revision information and regenerates the drawing. In this way, customization according to the user's preferences becomes possible.

[0282] Based on the completed drawings, the server recommends the most suitable furniture. Furniture recommendations are performed using online catalogs and databases, allowing the user to be provided with appropriate furniture options.

[0283] Furthermore, the server provides a 3D virtual tour function, allowing users to virtually tour properties based on selected land information and generated drawings. Visualizing real estate information in 3D makes it easier for users to imagine the actual space, enabling more concrete consideration.

[0284] For example, when a user is looking for "land within Tokyo with a budget of less than 30 million yen and an area of 100 square meters or more", the following processing is performed. The user inputs the conditions through a smartphone application and sends them to the server. The server crawls and filters land information based on the specified conditions, selects the optimal land, and notifies the user. Next, the server automatically generates a 3D drawing based on the selected land information and provides it to the user. The user inputs a modification request while viewing the drawing and checks the regenerated drawing. Finally, the server provides a 3D virtual tour including furniture placement suggestions, allowing the user to more specifically visualize the land and building plan.

[0285] Example of a prompt sentence:

[0286] "Looking for land within Tokyo with a budget of less than 30 million yen and an area of 100 square meters or more. Please search for the optimal land, generate a virtual drawing, and further propose furniture placement."

[0287] Thus, the present invention provides a system that comprehensively supports from the selection of land that meets the user's conditions to drawing creation, virtual viewing, and furniture recommendation.

[0288] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0289] Step 1:

[0290] Input the conditions of the land desired by the user

[0291] The user uses a smartphone application to input the conditions (such as budget, area, location, surrounding environment, etc.) regarding the desired land into an input form and sends them to the server.

[0292] Input: Conditions of the land (price, area, location, surrounding environment, etc.)

[0293] Output: Input condition data

[0294] Step 2:

[0295] The server crawls the land database and obtains land information that meets the conditions

[0296] Based on the conditions input by the user, the server crawls the Internet or a specific real estate database and obtains land information that meets the conditions. For example, filtering by price, area, and location is performed

[0297] Input: Condition data

[0298] Output: Obtained land information (candidate list)

[0299] Step 3:

[0300] Filter the obtained land information and select the optimal land

[0301] The server filters the land information obtained by crawling based on the user's conditions and selects the most suitable land information. This filtering process includes comparisons of price, area, and location

[0302] Input: Obtained land information (candidate list)

[0303] Output: Optimal land information (selected item)

[0304] Step 4:

[0305] Notify the user of the selected land information

[0306] The server notifies the user's terminal of the selected optimal land information. The notified information includes detailed land information (location, price, area, etc.)

[0307] Input: Optimal land information (selected item)

[0308] Output: Notification message sent to the user's terminal

[0309] Step 5:

[0310] Automatically generate drawings based on land information.

[0311] The server automatically generates basic design drawings and elevations using specialized CAD software based on the selected land information. This process automatically takes into account the shape and area of ​​the land.

[0312] Input: Optimal land information (selected items)

[0313] Output: Automatically generated drawing data (basic design drawings and elevation drawings)

[0314] Step 6:

[0315] Enter a request for revisions to the drawing.

[0316] The user reviews the generated drawings and enters any necessary modification requests. For example, they might enter specific requests such as "I want to make the living room larger" or "I want to change the location of the kitchen."

[0317] Input: Automated drawing data

[0318] Output: User correction request

[0319] Step 7:

[0320] Regenerate the drawing based on the revision request.

[0321] The server regenerates the drawing based on the modification request received from the user. It generates a new design drawing that reflects the modification request and provides it to the user.

[0322] Input: User correction request

[0323] Output: Regenerated drawing data (corrected design drawings)

[0324] Step 8:

[0325] Recommend furniture based on the drawings.

[0326] The server recommends the most suitable furniture and its placement from an online furniture catalog based on the completed drawings. The recommendation information is sent to the user's terminal, providing specific furniture options and placement suggestions.

[0327] Input: Regenerated drawing data

[0328] Output: Furniture recommendation information

[0329] Step 9:

[0330] Providing real estate information as a 3D virtual tour.

[0331] The server provides users with a 3D virtual tour based on the selected land and generated drawings. Through this tour, users can virtually view the property and form a concrete image of it.

[0332] Input: Optimal land information, regenerated drawing data

[0333] Output: 3D virtual tour

[0334] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0335] System Configuration

[0336] An embodiment of the present invention consists of a terminal in which the user inputs desired land conditions, a server that crawls a land database to acquire and filter land information that matches the conditions and select the optimal land, a server and terminal that automatically generate and modify drawings based on the land information and further recommend furniture, and an emotion engine that recognizes the user's emotions and responds accordingly.

[0337] System processing flow

[0338] 1. Enter conditions

[0339] Operator: User

[0340] Operation: The user enters their desired land conditions (price, area, location, surrounding environment, etc.) using a form displayed on the terminal and presses the submit button. The terminal then sends these conditions to the server.

[0341] 2. Acquisition of land information

[0342] Operating entity: Server

[0343] Operation: Based on the user's specified conditions, the server periodically crawls the land database and retrieves the latest land information that matches those conditions.

[0344] 3. Filtering land information

[0345] Operating entity: Server

[0346] Operation: The server filters land information acquired based on user criteria. This filtering selects land information that meets the specified criteria.

[0347] 4. Notification of land information

[0348] Operating entity: Server

[0349] Operation: The server selects the most suitable land from the filtered land information and notifies the user's terminal of that information. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[0350] 5. Automatic generation of recommended drawings

[0351] Operating entity: Server

[0352] Operation: Based on the notified land information, the server automatically generates basic drawings and elevation drawings using dedicated CAD software.

[0353] 6. Revision of drawings

[0354] Operator: User

[0355] Operation: The user reviews the generated drawing via the terminal and enters any necessary revision requests.

[0356] 7. Generation of revised drawings

[0357] Operating entity: Server

[0358] Operation: The server receives a modification request from the user and regenerates the drawing using CAD software. The regenerated drawing is based on the modification request.

[0359] 8. Furniture Recommendations

[0360] Operating entity: Server

[0361] Operation: Based on the completed drawings, the server crawls online furniture catalogs and retrieves furniture information suitable for those drawings. Furniture type, size, and design are all taken into consideration.

[0362] 9. Notification of furniture information

[0363] Operating entity: Server

[0364] Operation: The server sends a list of selected furniture and recommended placement suggestions to the user's device. The device then displays the furniture recommendation information.

[0365] Emotion Engine Processing Flow

[0366] 1. Recognition of emotions

[0367] Operating entity: Server

[0368] Operation: The emotion engine installed on the server analyzes the user's emotions from facial expressions, voice, text input, etc. The emotion engine identifies the user's emotions such as joy, surprise, disappointment, and anger.

[0369] 2. Emotion-based adjustment

[0370] Operating entity: Server

[0371] Operation: Based on the user's emotions recognized by the emotion engine, the system adjusts its output (notifications, drawings, furniture recommendations, etc.). For example, if the user is disappointed, the system will provide more detailed explanations or additional options.

[0372] Specific example

[0373] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[0374] 1. Enter the conditions:

[0375] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[0376] 2. Obtaining land information:

[0377] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[0378] 3. Filtering land information:

[0379] Based on the land information acquired by the server, the system recommends suitable land in Shinjuku Ward to the user.

[0380] 4. Notification of land information:

[0381] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[0382] 5. Automatic generation of recommended drawings:

[0383] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward.

[0384] 6. Revision of drawings:

[0385] The user enters a modification request stating, "I would like the living room to be a little larger."

[0386] 7. Generating revised drawings:

[0387] The server receives the correction request, regenerates the drawing, and resends it to the user.

[0388] 8. Furniture Recommendations:

[0389] The server recommends furniture such as sofas and tables suitable for a living room based on the floor plan, and sends the recommendations to the user's terminal.

[0390] If the emotion engine recognizes the emotion of "surprise" from the user's facial expressions or voice, the server will confirm that emotion with the user. If it is positive, it will take action such as suggesting multiple similar properties. Conversely, if a negative emotion is recognized, it can respond quickly and appropriately by suggesting further details or other options.

[0391] In this way, the system of the present invention can efficiently and consistently perform tasks ranging from land selection and drawing creation to revision, furniture recommendations, and even personalized responses based on emotion recognition, all based on the user's requirements.

[0392] The following describes the processing flow.

[0393] Step 1:

[0394] The user uses the input form displayed on the terminal to enter the desired land conditions (price, area, location, surrounding environment, etc.) and presses the submit button. The terminal then sends these conditions to the server.

[0395] Step 2:

[0396] The server crawls the real estate database based on the user's criteria received. The server periodically performs the crawling process to obtain the latest land information.

[0397] Step 3:

[0398] The server crawls and retrieves land information, which is then filtered based on the user's criteria. This filtering process selects land information that meets the specified conditions.

[0399] Step 4:

[0400] The server selects the most suitable land from the filtered land information. The selection criteria include user conditions as well as evaluation criteria pre-configured on the server.

[0401] Step 5:

[0402] The server notifies the user's terminal of the land information it has selected. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[0403] Step 6:

[0404] The user's device receives and displays a notification from the server. The user then reviews the presented land information.

[0405] Step 7:

[0406] Based on the recommended land information, the server automatically generates basic drawings and elevations using specialized CAD software.

[0407] Step 8:

[0408] The server automatically generates drawings and elevations and sends them to the user's terminal. The terminal then displays the received drawings.

[0409] Step 9:

[0410] The user reviews the provided drawings and enters any necessary revision requests. Examples of revision requests include changes to room size or layout. The user then submits the revision requests.

[0411] Step 10:

[0412] The server receives a modification request from the user and regenerates the drawing using CAD software. The regenerated drawing is based on the modification request.

[0413] Step 11:

[0414] The server sends the regenerated drawing back to the user's terminal. The terminal displays the corrected drawing.

[0415] Step 12:

[0416] Based on the completed drawings, the server crawls online furniture catalogs to retrieve furniture information suitable for those drawings. Factors such as furniture type, size, and design are taken into consideration.

[0417] Step 13:

[0418] The server sends a list of selected furniture and recommended placement suggestions to the user's device. The device then displays the furniture recommendations.

[0419] Step 14:

[0420] Users review the recommended furniture and make final adjustments to purchases and placement as needed.

[0421] Step 15:

[0422] The emotion engine installed on the server analyzes the user's emotions from facial expressions, voice, text input, etc. The emotion engine identifies the user's emotions such as joy, surprise, disappointment, and anger.

[0423] Step 16:

[0424] The server adjusts the system's output (notifications, drawings, furniture recommendations, etc.) based on the user's emotions recognized by the emotion engine. For example, if the user is disappointed, the system will provide more detailed explanations or additional options.

[0425] Specific example

[0426] Step 1:

[0427] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[0428] Step 2:

[0429] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[0430] Step 3:

[0431] The server filters the acquired land information based on the user's criteria and recommends land in Shinjuku Ward to the user.

[0432] Step 4:

[0433] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[0434] Step 5:

[0435] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward.

[0436] Step 6:

[0437] The server automatically generates drawings and elevations, which are then sent to the user and displayed on the user's device.

[0438] Step 7:

[0439] The user enters a modification request stating, "I would like the living room to be a little larger."

[0440] Step 8:

[0441] The server receives the correction request, regenerates the drawing, and resends it to the user.

[0442] Step 9:

[0443] The server recommends furniture such as sofas and tables suitable for the living room based on the floor plan, and sends the recommendations to the user's device.

[0444] Step 10:

[0445] The emotion engine recognizes the emotion of "surprise" from the user's facial expressions and voice.

[0446] Step 11:

[0447] The server checks the user's sentiment and, if the response is positive, suggests several similar properties. If the response is negative, it suggests further details or other options.

[0448] In this way, the system of the present invention can efficiently and consistently perform tasks ranging from land selection and drawing creation to revision, furniture recommendations, and even personalized responses based on emotion recognition, all based on the user's requirements.

[0449] (Example 2)

[0450] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0451] The traditional process of acquiring land, designing a residence, and selecting furniture requires considerable effort and time from the user, and there are challenges in providing sufficient support to enhance user satisfaction. In particular, there is a need for a system that efficiently and consistently handles the entire process, from quickly and accurately acquiring land information that matches the user's desired conditions, to automatically generating and modifying drawings based on that information, and recommending furniture. Furthermore, there is a lack of a system that can recognize the user's emotions and respond appropriately based on them.

[0452] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0453] In this invention, the server includes means for crawling a land database based on user-specified conditions and obtaining land information that meets those conditions; means for filtering the obtained land information and selecting the optimal land; means for automatically generating drawings based on the selected land information; and means including an emotion engine that analyzes the user's emotions and adjusts the system's output based on those emotions. This enables efficient execution of a series of processes from land selection based on user conditions to drawing creation, modification, and furniture recommendations, and also allows for flexible responses in accordance with the user's emotions.

[0454] A "user" is an entity that uses the system to input land conditions or request modifications to drawings.

[0455] A "land database" is a collection of data where various types of land information are stored. Information is retrieved through crawling.

[0456] "Crawling" is the act of using automated programs to periodically visit the internet and specific databases to collect information.

[0457] "Filtering" is the process of extracting only those data items that match specific criteria from a set of data.

[0458] "Optimal land" refers to land information that best matches the conditions entered by the user.

[0459] "Notification" refers to the act of sending land information or other information from a system to a user.

[0460] A "drawing" is a design plan for a house or building that is automatically generated based on land information.

[0461] A "revision request" is an instruction from the user to request changes to an automatically generated drawing.

[0462] "Regeneration" is the process of regenerating a drawing based on the user's modification request.

[0463] "Furniture recommendation" is the act of suggesting appropriate furniture types, sizes, and designs based on completed drawings.

[0464] An "emotion engine" is a program that analyzes the user's emotions from facial expressions, voice, text input, etc., and adjusts the system's output based on the results.

[0465] "Computer-aided design software" refers to specialized software used to create and edit design drawings using a computer.

[0466] System Configuration

[0467] The system of this invention consists of the following components.

[0468] 1. A terminal where the user enters their desired land conditions.

[0469] 2. A server that crawls the land database, retrieves and filters land information that matches the criteria, and selects the most suitable land.

[0470] 3. Server for automatically generating and modifying drawings based on land information.

[0471] 4. Terminal for recommending furniture based on drawings.

[0472] 5. An emotion engine that recognizes user emotions and responds accordingly.

[0473] Hardware and software to be used

[0474] Devices: Personal computers and smartphones

[0475] Server: A server computer with high-performance computing capabilities.

[0476] Land database: A database system for storing land information.

[0477] CAD software: Computer-aided design software

[0478] Emotion Engine: An AI program for analyzing user emotions.

[0479] Data processing and data calculation

[0480] Condition Input: The user uses a terminal to input the desired land conditions (price, area, location, surrounding environment, etc.). The entered information is sent to the server.

[0481] Land Information Acquisition and Filtering: The server crawls the land database based on the conditions received from the user. The acquired land information is filtered based on the conditions, and the most suitable land is selected.

[0482] Land Information Notification: Filtered information is sent to the user's device. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[0483] Automatic drawing generation: Based on the notified land information, the server automatically generates basic drawings and elevations using CAD software.

[0484] Drawing modification and regeneration: The user reviews the generated drawing via the terminal and enters any necessary modification requests. The server then regenerates the drawing based on these modification requests.

[0485] Furniture Recommendation: Based on the completed drawings, the server crawls online furniture catalogs to retrieve furniture information suitable for those drawings. Furniture type, size, and design are all taken into consideration.

[0486] Emotional Engine Processing

[0487] Emotion Recognition: The emotion engine analyzes emotions from the user's facial expressions, voice, text input, etc.

[0488] Emotion-based response: The emotion engine adjusts the system's output (notifications, drawings, furniture recommendations, etc.) based on the user's emotions.

[0489] Specific example

[0490] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[0491] 1. Enter the conditions:

[0492] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[0493] 2. Obtaining land information:

[0494] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[0495] 3. Filtering land information:

[0496] Based on the land information acquired by the server, the system recommends suitable land in Shinjuku Ward to the user.

[0497] 4. Notification of land information:

[0498] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[0499] 5. Automatic generation of recommended drawings:

[0500] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward.

[0501] 6. Revision of drawings:

[0502] The user enters a modification request stating, "I would like the living room to be a little larger."

[0503] 7. Generating revised drawings:

[0504] The server receives the correction request, regenerates the drawing, and resends it to the user.

[0505] 8. Furniture Recommendations:

[0506] The server recommends furniture such as sofas and tables suitable for a living room based on the floor plan, and sends the recommendations to the user's terminal.

[0507] Furthermore, if the emotion engine recognizes the emotion of "surprise" from the user's facial expressions or voice, the server will confirm this emotion with the user. If it is positive, it will take action such as suggesting multiple similar properties. Conversely, if a negative emotion is recognized, it can respond quickly and appropriately by suggesting further details or other options.

[0508] In this way, the system of the present invention can efficiently and consistently perform tasks ranging from land selection and drawing creation to revision, furniture recommendations, and even personalized responses based on emotion recognition, all based on the user's requirements.

[0509] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0510] Step 1: Enter the conditions

[0511] Operator: User

[0512] Input: The user enters their desired land conditions (price, area, location, surrounding environment, etc.) into the input form.

[0513] Specific actions:

[0514] 1. The user launches a land information search application on their personal computer or smartphone.

[0515] 2. The application's initial screen displays a form where you can enter conditions such as "budget," "area," "location," and "surrounding environment."

[0516] 3. The user enters the respective conditions and presses the submit button.

[0517] Output: The terminal sends the entered condition information to the server.

[0518] Step 2: Obtaining land information

[0519] Operating entity: Server

[0520] Input: Data of desired conditions submitted by the user.

[0521] Specific actions:

[0522] 1. The server generates a query (search request) based on the conditions received from the user.

[0523] 2. The server uses this query to crawl the land database and collect land information that matches the criteria.

[0524] 3. The information obtained from the database covers a wide range of topics, including the location, price, area, and surrounding environment of the land.

[0525] Output: Temporarily save the list of land parcels obtained as search results and proceed to the next step.

[0526] Step 3: Filtering land information

[0527] Operating entity: Server

[0528] Input: List of searched land information

[0529] Specific actions:

[0530] 1. The server begins filtering the stored land information based on the user's criteria.

[0531] 2. The filtering process involves checking for matches against conditions such as price, area, location, and surrounding environment.

[0532] 3. Extract matching land information and create an optimal land information list.

[0533] Output: Generates a filtered list of optimal land information and proceeds to the next step.

[0534] Step 4: Notification of land information

[0535] Operating entity: Server

[0536] Input: Filtered list of optimal land information

[0537] Specific actions:

[0538] 1. The server formats the optimal land information and generates a message to notify the user.

[0539] 2. The message will include detailed information such as the land's location, price, area, and surrounding environment.

[0540] 3. Send the generated message to the user's device.

[0541] Output: A notification of land information is displayed on the user's device.

[0542] Step 5: Automatic generation of recommended drawings

[0543] Operating entity: Server

[0544] Input: Notified land information

[0545] Specific actions:

[0546] 1. The server launches dedicated computer-aided design software based on the selected land information.

[0547] 2. Input the shape and area of ​​the land, as well as the necessary house floor plan data, and issue commands to automatically generate the basic house plans and elevations.

[0548] 3. The drawing is generated within the software, and the result is saved to the server.

[0549] Output: Automatically generated basic drawings and elevations.

[0550] Step 6: Modify the drawing

[0551] Operator: User

[0552] Input: Auto-generated drawing

[0553] Specific actions:

[0554] 1. The user checks the automatically generated drawing displayed on the terminal.

[0555] 2. Enter any requests for modifications to the drawing, such as "I'd like the living room to be a little wider" or "I'd like the entrance to be on the right side," into the input form.

[0556] 3. Enter the correction request and press the submit button.

[0557] Output: The terminal sends a correction request to the server.

[0558] Step 7: Generate revised drawings

[0559] Operating entity: Server

[0560] Input: Correction request submitted by the user

[0561] Specific actions:

[0562] 1. The server analyzes the correction request received from the user.

[0563] 2. Based on the analysis results, restart the computer-aided design software.

[0564] 3. Issue an order to regenerate the drawing in accordance with the revision request, and generate a new drawing.

[0565] 4. Save the regenerated drawing and resend it to the user.

[0566] Output: The modified drawing is sent to the user's terminal.

[0567] Step 8: Furniture Recommendations

[0568] Operating entity: Server

[0569] Input: Completed drawing

[0570] Specific actions:

[0571] 1. The server analyzes the completed drawings and determines the optimal type, size, and design of furniture for each room.

[0572] 2. The server crawls online furniture catalogs and searches for furniture information that matches the determined criteria.

[0573] 3. Generate a furniture list and send it to the user's device along with a recommended layout.

[0574] Output: Furniture recommendations and suggested layouts are displayed on the user's device.

[0575] Step 9: Recognizing Emotions

[0576] Operating entity: Server

[0577] Input: User facial expressions, voice, text input

[0578] Specific actions:

[0579] 1. The emotion engine installed on the server captures the user's facial expressions and voice obtained from the webcam and microphone.

[0580] 2. Include text input as part of the analysis.

[0581] 3. The emotion engine analyzes this information to identify the user's emotions (joy, surprise, disappointment, anger, etc.).

[0582] Output: User sentiment data is generated.

[0583] Step 10: Emotion-based responses

[0584] Operating entity: Server

[0585] Input: Emotional data generated by the emotion engine

[0586] Specific actions:

[0587] 1. The system's output is adjusted based on the emotion type recognized by the emotion engine.

[0588] 2. For example, if the user is disappointed, the server will provide a detailed explanation or additional options.

[0589] 3. If the user is pleased, provide positive feedback, such as suggesting multiple similar properties.

[0590] Output: The output of the adjusted system is notified to the user.

[0591] In this way, the system can consistently and efficiently perform tasks such as land selection based on user conditions, drawing creation and modification, furniture recommendations, and even emotional recognition-based responses.

[0592] (Application Example 2)

[0593] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0594] Traditional real estate selection systems have struggled to efficiently find properties that meet users' desired criteria. Furthermore, post-purchase design and furniture selection can be burdensome for users. Similarly, in shopping, gathering information on desired products and improving customer satisfaction during purchase remain challenges. In particular, there has been a lack of mechanisms to reflect users' emotions in real time and provide appropriate suggestions.

[0595] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0596] In this invention, the server includes means for inputting the land conditions desired by the user; means for crawling a real estate database based on the conditions and obtaining real estate information that matches the conditions; means for filtering the obtained real estate information and selecting the most suitable real estate; means for notifying the user of the selected real estate information; means for automatically generating drawings based on the real estate information; means for inputting requests for modifications to the drawings; means for regenerating the drawings based on the modification requests; means for recommending furniture based on the drawings; means for inputting product conditions desired by the user and obtaining product information that matches the conditions; means for notifying the user of recommended products based on the product information; and means for recognizing the user's emotions and adjusting the suggested content according to those emotions.

[0597] This makes it possible to provide users with an efficient and satisfying experience, from selecting and designing their desired property to recommending furniture and even shopping.

[0598] "A means for users to input their desired land conditions" refers to an interface for users to input their desired real estate conditions (price, area, location, surrounding environment, etc.) and transmit this information to the system.

[0599] "A means of crawling real estate databases and obtaining real estate information that meets the specified conditions" refers to a mechanism for automatically collecting real estate information that matches specified conditions from multiple real estate databases on the internet.

[0600] "Methods for filtering acquired real estate information and selecting the most suitable property" refers to algorithms or software that select the property that best matches the user's criteria from the collected real estate information.

[0601] "Means of notifying users of selected real estate information" refers to a system for displaying, alerting, or otherwise communicating identified real estate information to the user's terminal.

[0602] "Methods for automatically generating drawings based on real estate information" refers to a function that automatically creates design drawings and elevation drawings using specialized design software based on acquired real estate information.

[0603] "Means for inputting modification requests for drawings" refers to an interface for users to input and submit requests for changes or modifications to generated drawings.

[0604] "Means for regenerating drawings based on revision requests" refers to algorithms or software for regenerating and updating design drawings to reflect revision requests from users.

[0605] "A means of recommending furniture based on drawings" refers to a function that considers the layout of the generated design drawings and proposes the most suitable furniture and interior design to the user.

[0606] "A means of inputting desired product conditions and obtaining product information that meets those conditions" refers to an interface and algorithm for inputting desired product conditions (price, features, performance, etc.) and collecting product information that matches those conditions.

[0607] "A means of notifying users of recommended products based on product information" refers to a system that selects the most suitable product for the user based on collected product information and notifies them of it.

[0608] "Means for recognizing user emotions and adjusting suggestions accordingly" refers to an emotion recognition engine and algorithm that analyzes the user's emotional state from their facial expressions and voice, and dynamically changes and adjusts the suggested content based on the results.

[0609] System Configuration

[0610] The system for implementing this invention consists of a terminal for the user to input desired conditions, a server that crawls a real estate database to acquire and filter information that matches the conditions and select the most suitable property, a server and terminal that automatically generate and modify drawings based on the property information and further recommend furniture, and an emotion engine that recognizes the user's emotions and responds accordingly.

[0611] Hardware and software used

[0612] Smartphone: Use an iPhone® or Android®-equipped smartphone as the user's input terminal.

[0613] Servers: For cloud services, we will use Amazon Web Services (AWS®) or Google® Cloud Platform.

[0614] Emotion Engine: Emotion recognition uses either the Microsoft® Azure® Emotion API or the Google Cloud Vision API.

[0615] Artificial intelligence: Generative AI models such as OpenAI's GPT-4 (registered trademark) are used.

[0616] Database: MongoDB or Firebase are used for data management.

[0617] Design software: Automatic drawing generation is performed using design software such as AutoCAD API.

[0618] System processing

[0619] At each processing stage of the system, data processing and calculations are performed as follows:

[0620] 1. Enter conditions

[0621] Users use a form in a smartphone app to enter their desired real estate conditions (price, area, location, surrounding environment, etc.) and product conditions (price, features, performance, etc.), and then submit them to the server.

[0622] 2. Acquisition and filtering of real estate information

[0623] The server crawls the specified real estate database and retrieves property information that matches the user's criteria. Then, it uses a filtering algorithm (written in Python) to select the most suitable property.

[0624] 3. Notification of real estate information

[0625] Filtered real estate information is sent to the user's smartphone. Detailed information (price, location, surrounding environment, etc.) is displayed.

[0626] 4. Automatic generation and modification of drawings

[0627] The server automatically generates design drawings and elevations using design software (AutoCAD API) based on the acquired real estate information. If a user requests revisions to the drawings, the server incorporates those changes and regenerates the drawings.

[0628] 5. Furniture Recommendations

[0629] Based on the automatically generated drawings, the server crawls online furniture catalogs and retrieves furniture information suitable for the drawings. It then provides recommendations considering furniture type, size, design, and other factors.

[0630] 6. Acquisition and notification of product information

[0631] Based on product criteria, the system crawls multiple product databases on the internet (such as the Google Shopping API and Amazon Product Advertising API) to retrieve suitable product information. The retrieved product information is then notified to the user, and detailed information is displayed.

[0632] 7. Emotion Recognition and Response Adjustment

[0633] The system uses the smartphone's built-in camera and microphone to collect the user's facial expressions and voice. An emotion engine (such as the Azure Emotion API) analyzes this data and adjusts the system's output according to the emotion. For positive emotions, it suggests additional related products; for negative emotions, it provides detailed explanations or other options.

[0634] Specific example

[0635] For example, if a user enters their desired real estate conditions as "budget of 30 million yen, area of ​​100 square meters or more, location: Tokyo, condition: good transportation access," the server crawls the land database and finds properties that match the conditions. Based on that information, it generates a blueprint and incorporates the user's modification requests. Finally, it recommends furniture that suits the generated blueprint. If the emotion engine recognizes the user's emotion of "surprise," the system will suggest additional similar properties.

[0636] Example of a prompt

[0637] Requirements: A smartwatch with a price under 30 million yen, in red, and featuring waterproof functionality. Please recommend related products and generate layout proposals.

[0638] This allows users to easily obtain real estate and product information that best suits their desired conditions, and furthermore, receive highly satisfying suggestions through emotion recognition.

[0639] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0640] Step 1:

[0641] Condition Input

[0642] Users use a smartphone app to input their desired real estate conditions (price, area, location, surrounding environment, etc.) and product conditions (price, features, performance, etc.). The entered conditions are sent to the server via the smartphone app.

[0643] Input: User's desired conditions (e.g., price 30 million yen, area 100 square meters or more, location: Tokyo, condition: convenient transportation)

[0644] Output: Conditional data sent to the server

[0645] Step 2:

[0646] Acquisition of real estate information

[0647] The server crawls the specified real estate database and retrieves property information that matches the user's criteria. During this process, periodic queries are executed. A crawl script, often using Python, is run to collect the latest property information that meets the specified criteria.

[0648] Input: Conditional data sent by the user to the server

[0649] Output: Dataset of real estate information that matches the criteria

[0650] Step 3:

[0651] Filtering real estate information

[0652] The server executes a filtering algorithm based on the acquired real estate information to select the most suitable property. Filtering is performed based on pre-configured user criteria.

[0653] Input: Dataset of acquired real estate information, user conditions

[0654] Output: Filtered and optimized real estate information

[0655] Step 4:

[0656] Real estate information notification

[0657] The server notifies the user's smartphone of filtered real estate information. The notification includes detailed information about the property (price, location, surrounding environment, etc.). The user's smartphone app receives and displays this information.

[0658] Input: Filtered property information

[0659] Output: Property details displayed on the user's smartphone

[0660] Step 5:

[0661] Automatic generation of drawings

[0662] The server automatically generates design drawings and elevations using design software (AutoCAD API) based on the acquired real estate information. A dedicated script is executed, and detailed drawings are created based on the input data.

[0663] Input: Filtered property information

[0664] Output: Automatically generated design drawings and elevations

[0665] Step 6:

[0666] Request for revision of drawings

[0667] The user enters revision requests based on automatically generated drawings. They specify in detail the areas requiring modification and the elements they wish to add via a smartphone app. The revision requests are then sent to the server.

[0668] Input: User correction request

[0669] Output: Correction request data sent to the server

[0670] Step 7:

[0671] Generation of revised drawings

[0672] The server receives the modification request from the user and generates the modified drawing again using the design software (AutoCAD API). Based on the user's specifications, a new drawing is created that reflects the necessary changes.

[0673] Input: Modification request data, initial design drawings

[0674] Output: Revised blueprints

[0675] Step 8:

[0676] Furniture recommendations

[0677] Based on the final design plans, the server crawls online furniture catalogs and recommends furniture that fits those plans. Considering factors such as furniture type, size, and design, a list of suitable furniture is generated for the user.

[0678] Input: Modified blueprint

[0679] Output: Furniture recommendation information

[0680] Step 9:

[0681] Product information acquisition and notification

[0682] The server crawls multiple product databases on the internet based on the user's desired product criteria and retrieves suitable product information. The retrieved product information is then displayed as a notification on the user's smartphone.

[0683] Input: User's desired product specifications

[0684] Output: Product information displayed on the user's smartphone

[0685] Step 10:

[0686] Emotion recognition and response adjustment

[0687] The smartphone's built-in camera and microphone are used to collect the user's facial expressions and voice. An emotion engine (such as the Azure Emotion API) analyzes this data to identify the user's emotions. If the emotion is positive, additional suggestions are provided; if it is negative, more detailed explanations and other options are offered.

[0688] Input: User's facial expressions and voice data

[0689] Output: Adjusted proposal or additional options

[0690] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0691] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0692] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0693] [Second Embodiment]

[0694] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0695] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0696] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0697] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0698] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0699] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0700] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0701] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0702] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0703] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0704] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0705] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0706] System Configuration

[0707] An embodiment of the present invention consists of a terminal in which the user inputs the desired land conditions, a server that crawls a land database, acquires and filters land information that matches the conditions, and selects the most suitable land, and a server and terminal that automatically generate and modify drawings based on the land information and further recommend furniture.

[0708] System processing flow

[0709] 1. Enter conditions

[0710] Operator: User

[0711] Operation: The user enters the desired land conditions (price, area, location, surrounding environment, etc.) using a form displayed on the terminal, and then presses the submit button to send that information to the server.

[0712] 2. Acquisition of land information

[0713] Operating entity: Server

[0714] Operation: Based on the user's specified conditions, the server periodically crawls the land database and retrieves the latest land information that matches those conditions.

[0715] 3. Filtering land information

[0716] Operating entity: Server

[0717] Operation: The server filters land information acquired based on user criteria and selects suitable land information.

[0718] 4. Notification of land information

[0719] Operating entity: Server

[0720] Operation: The server notifies the user's terminal of information about the selected suitable land. This notification includes detailed information about the land (location, price, area, etc.).

[0721] 5. Automatic generation of recommended drawings

[0722] Operating entity: Server

[0723] Operation: Based on the notified land information, the server automatically generates basic drawings and elevations using dedicated CAD software.

[0724] 6. Revision of drawings

[0725] Operator: User

[0726] Operation: The user reviews the generated drawing via the terminal and enters any necessary revision requests.

[0727] 7. Generation of revised drawings

[0728] Operating entity: Server

[0729] Operation: The server receives a correction request from the user and regenerates the drawing based on the correction. The regenerated drawing is then sent back to the user's terminal.

[0730] 8. Furniture Recommendations

[0731] Operating entity: Server

[0732] Operation: Based on the completed drawings, the server recommends the most suitable furniture and its placement from an online furniture catalog. The recommendation information is sent to the user's device.

[0733] Specific example

[0734] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[0735] 1. Enter the conditions:

[0736] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[0737] 2. Obtaining land information:

[0738] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[0739] 3. Filtering land information:

[0740] Based on the land information acquired by the server, the system recommends suitable land in Shinjuku Ward to the user.

[0741] 4. Notification of land information:

[0742] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[0743] 5. Automatic generation of recommended drawings:

[0744] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward and sends them to the user.

[0745] 6. Revision of drawings:

[0746] The user enters a modification request stating, "I would like the living room to be a little larger."

[0747] 7. Generating revised drawings:

[0748] The server receives the correction request, regenerates the drawing, and resends it to the user.

[0749] 8. Furniture Recommendations:

[0750] The server recommends furniture such as sofas and tables suitable for a living room based on the floor plan, and sends the recommendations to the user's terminal.

[0751] In this way, the system of the present invention can efficiently perform a consistent process from land selection to drawing creation, modification, and furniture recommendation, based on the user's requirements.

[0752] The following describes the processing flow.

[0753] Step 1:

[0754] The user uses the input form displayed on the terminal to enter the desired land conditions (price, area, location, surrounding environment, etc.) and presses the submit button. The terminal then sends these conditions to the server.

[0755] Step 2:

[0756] The server crawls the real estate database based on the user's criteria received. The crawling process is performed periodically to retrieve the latest land information.

[0757] Step 3:

[0758] The server crawls and retrieves land information, which is then filtered based on the user's criteria. This filtering process selects land information that meets the specified conditions.

[0759] Step 4:

[0760] The server selects the most suitable land from the filtered land information. The selection criteria include user conditions as well as evaluation criteria pre-configured on the server.

[0761] Step 5:

[0762] The server notifies the user's terminal of the land information it has selected. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[0763] Step 6:

[0764] The user's device receives and displays a notification from the server. The user then reviews the presented land information.

[0765] Step 7:

[0766] Based on the recommended land information, the server automatically generates basic drawings and elevations using specialized CAD software.

[0767] Step 8:

[0768] The server automatically generates drawings and elevations and sends them to the user's terminal. The terminal then displays the received drawings.

[0769] Step 9:

[0770] The user reviews the provided drawings and enters any necessary revision requests. Examples of revision requests include changes to room size or layout. The user then submits the revision requests.

[0771] Step 10:

[0772] The server receives a modification request from the user and regenerates the drawing using CAD software. The regenerated drawing is based on the modification request.

[0773] Step 11:

[0774] The server sends the regenerated drawing back to the user's terminal. The terminal displays the corrected drawing.

[0775] Step 12:

[0776] Based on the completed drawings, the server crawls online furniture catalogs to retrieve furniture information suitable for those drawings. Factors such as furniture type, size, and design are taken into consideration.

[0777] Step 13:

[0778] The server sends a list of selected furniture and recommended placement suggestions to the user's device. The device then displays the furniture recommendations.

[0779] Step 14:

[0780] Users review the recommended furniture and make final adjustments to purchases and placement as needed.

[0781] (Example 1)

[0782] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0783] When purchasing a modern home, many users spend considerable time and effort finding suitable land, creating optimal blueprints, and then selecting furniture. Traditional methods fragment the process, requiring users to interact with multiple platforms and vendors at each stage, as these tasks—land information gathering and filtering, blueprint creation and revision, and furniture selection—are disconnected. This process is inefficient and often leads to lower overall satisfaction. Furthermore, challenges include the inability to obtain suitable land information in a timely manner and the cumbersome process of revising blueprints.

[0784] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0785] In this invention, the server includes means for the user to input desired land conditions, means for crawling a land database based on the conditions and obtaining land information that matches the conditions, and means for filtering the obtained land information and selecting the optimal land. This allows the user to efficiently obtain desired land information and receive automatically generated blueprints and recommendations for optimal furniture based on that information. This enables the entire process from land selection to blueprint creation and furniture selection to be carried out efficiently in one go, thereby improving user satisfaction.

[0786] A "user" is an entity that uses this system to input desired land conditions and receives selected land information, blueprints, and furniture recommendations.

[0787] "Means for inputting conditions" refers to a device or system that provides an interface for users to input detailed conditions of land they desire (such as price, area, location, and surrounding environment).

[0788] A "land database" is a source of information that stores information on multiple plots of land and is used to retrieve land information that meets specific criteria through crawling.

[0789] "Crawling" refers to a software technology that involves a program or a series of operations for automatically collecting information from land databases on the internet.

[0790] "Filtering methods" refer to software algorithms used to select information that matches the user's input criteria from the acquired land information.

[0791] "Land information" refers to information about a specific piece of land, including details such as location, price, and area.

[0792] "Notification means" refers to communication methods for sending filtered land information to the user's device. This includes methods such as email and push notifications.

[0793] A "design drawing" is a diagram that shows the basic layout and structure of a building to be constructed on a desired plot of land.

[0794] "Means of automatic generation" refers to an algorithm or program that automatically creates building blueprints using specific software (e.g., CAD software) based on input land information.

[0795] A "means for inputting modification requests" refers to a system that provides an interface for users to review generated blueprints and input necessary changes or modifications.

[0796] A "means of regeneration" refers to a software algorithm for recreating the design blueprint to reflect the modification requests.

[0797] "A means of recommending furniture" refers to software that suggests appropriate furniture and its placement based on a completed blueprint.

[0798] The "reporting database" is a database used to temporarily store suitable land information after filtering.

[0799] "Means for generating furniture arrangement plans" refers to algorithms or software for creating the optimal furniture arrangement based on a completed design drawing.

[0800] An embodiment of the present invention consists of a terminal in which the user inputs desired land conditions, a server that crawls a land database to acquire and filter land information that matches the conditions and select the most suitable land, and a server and terminal that automatically generate and modify building blueprints based on the land information and further recommend furniture.

[0801] Hardware and software to be used

[0802] Terminal: A client device used by the user to operate the system (PC, tablet, smartphone, etc.)

[0803] Server: A central server that processes user input and performs tasks such as data retrieval, filtering, notifications, diagram generation, and recommendations.

[0804] Software and libraries to be used:

[0805] Web browser: Provides an interface for users to enter conditions.

[0806] Python: A programming language used for data crawling.

[0807] Beautiful Soup, Selenium: Libraries for crawling land databases

[0808] SQL (MySQL, PostgreSQL, etc.): Database management system

[0809] AutoCAD API: CAD software for automatically generating building blueprints.

[0810] Email sending API, push notification API: Communication methods for notifying users of land information and map URLs.

[0811] IKEA API, Amazon API: Online catalogs for recommending furniture

[0812] Explanation of the processing flow

[0813] 1. Enter conditions

[0814] Operator: User

[0815] Specific operation: The user opens a web page on their device, enters details of the desired land (price, area, location, surrounding environment, etc.) into a form, and clicks the submit button to send it to the server.

[0816] 2. Acquisition of land information

[0817] Operating entity: Server

[0818] Specific operation: The server uses Python to crawl a specified land database using Beautiful Soup or Selenium, retrieves land information that meets the criteria, and stores it in a temporary storage database.

[0819] 3. Filtering land information

[0820] Operating entity: Server

[0821] Specific operation: The server reads data retrieved from a temporary storage database and filters it based on user criteria. The filtered data is then saved to the reporting database as matching land information.

[0822] 4. Notification of land information

[0823] Operating entity: Server

[0824] Specific operation: The server uses email sending APIs and push notification APIs to notify users of filtered land information.

[0825] 5. Automatic generation of recommended drawings

[0826] Operating entity: Server

[0827] Specific operation: The server uses the AutoCAD API to automatically generate basic house drawings and elevations based on the provided land information. The generated drawings are saved on the server, and the URL is notified to the user.

[0828] 6. Revision of drawings

[0829] Operator: User

[0830] Specific operation: The user opens the notified URL and enters a request to review and modify the drawing. The modification request is sent to the server.

[0831] 7. Generation of revised drawings

[0832] Operating entity: Server

[0833] Specific operation: The server receives the correction request, regenerates the drawing using the AutoCAD API, and notifies the user again.

[0834] 8. Furniture Recommendations

[0835] Operating entity: Server

[0836] Specific operation: Based on the completed drawing, the server retrieves information on suitable furniture from the IKEA API and Amazon API, and notifies the user of the recommended furniture.

[0837] Specific example

[0838] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[0839] 1. Enter the conditions:

[0840] The user enters the following conditions on their device: "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Convenient transportation," and sends it to the server.

[0841] 2. Obtaining land information:

[0842] The server uses Python's Beautiful Soup to crawl the land database and finds a 120 square meter plot of land in Shinjuku Ward.

[0843] 3. Filtering land information:

[0844] The server filters the acquired land information, selects land information that meets the specified criteria, and saves it to the reporting database.

[0845] 4. Notification of land information:

[0846] The server uses an email API to notify users of selected land information (e.g., 120 square meters in Shinjuku Ward, priced at 30 million yen).

[0847] 5. Automatic generation of recommended drawings:

[0848] The server uses the AutoCAD API to automatically generate design drawings and elevation drawings based on the acquired land information, and notifies the user of the URL.

[0849] 6. Revision of drawings:

[0850] The user opens the URL they were notified with, enters a modification request such as "I want the living room to be a little bigger," and sends it to the server.

[0851] 7. Generating revised drawings:

[0852] The server receives the correction request, uses the AutoCAD API again to generate the corrected drawing, and notifies the user again.

[0853] 8. Furniture Recommendations:

[0854] The server uses the Amazon API to recommend furniture suitable for the generated drawings to the user.

[0855] Examples of prompts for generative AI models

[0856] The following are examples of prompt statements to input into the generative AI model.

[0857] "For users searching for land in Tokyo with a budget of 30 million yen, over 100 square meters, and convenient transportation access, please acquire, filter, and recommend appropriate land information. Furthermore, generate basic house plans based on the land, update the plans according to user requests, and finally, recommend furniture."

[0858] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0859] Step 1:

[0860] Condition Input

[0861] Operator: User

[0862] Specific actions:

[0863] The user starts up their device and opens the system's webpage in their browser. They enter their desired land conditions (price, area, location, surrounding environment, etc.) into the form. They click the "Submit" button to send the conditions to the server.

[0864] input:

[0865] Desired land conditions (price, area, location, surrounding environment, etc.)

[0866] output:

[0867] The entered conditions are sent to the server.

[0868] Step 2:

[0869] Acquisition of land information

[0870] Operating entity: Server

[0871] Specific actions:

[0872] The server receives the conditions sent by the user. Using Python libraries (such as Beautiful Soup or Selenium), it crawls the specified land database and retrieves the latest land information that matches the conditions. The retrieved land information is stored in a temporary storage database.

[0873] input:

[0874] Land conditions entered by the user

[0875] output:

[0876] Land information stored in a temporary storage database

[0877] Step 3:

[0878] Land information filtering

[0879] Operating entity: Server

[0880] Specific actions:

[0881] The server reads data retrieved from a temporary storage database and filters it using SQL queries based on user criteria. Based on the filtering results, it selects suitable land information and saves it to the reporting database.

[0882] input:

[0883] Land information stored in a temporary storage database

[0884] output:

[0885] Save filtered land information to the reporting database.

[0886] Step 4:

[0887] Land information notification

[0888] Operating entity: Server

[0889] Specific actions:

[0890] The server prepares to send notifications to users based on the filtered land information. It uses email sending APIs and push notification APIs to send the filtered land information to the user's device.

[0891] input:

[0892] Filtered land information stored in the reporting database

[0893] output:

[0894] Notifications to the user's device

[0895] Step 5:

[0896] Automatic generation of recommended drawings

[0897] Operating entity: Server

[0898] Specific actions:

[0899] Based on the provided land information, the server automatically generates basic house plans and elevations using the AutoCAD API. The generated plans are saved as image files on the server, and a URL for the plans is generated. This URL is then notified to the user.

[0900] input:

[0901] Land information stored in the reporting database

[0902] output:

[0903] Notification containing the URL of the generated drawing

[0904] Step 6:

[0905] Drawing revisions

[0906] Operator: User

[0907] Specific actions:

[0908] The user opens the URL of the drawing notified from the server using their device. They review the drawing and enter revision requests using the form or comment function. Revision requests are sent from the device to the server in real time.

[0909] input:

[0910] User correction request

[0911] output:

[0912] Correction request sent to the server

[0913] Step 7:

[0914] Generation of revised drawings

[0915] Operating entity: Server

[0916] Specific actions:

[0917] The server receives the user's modification request and uses the AutoCAD API, etc., again to regenerate the drawing that reflects the modifications. The URL of the regenerated drawing is then sent to the user's device again.

[0918] input:

[0919] User correction request

[0920] output:

[0921] Notification including the URL of the revised drawing

[0922] Step 8:

[0923] Furniture recommendations

[0924] Operating entity: Server

[0925] Specific actions:

[0926] The server crawls online furniture catalogs (such as the IKEA API and Amazon API) based on the completed drawings. It selects furniture suitable for the drawings and generates optimal furniture and layout plans. This recommendation information is then notified to the user's device.

[0927] input:

[0928] Completed drawings

[0929] output:

[0930] Furniture recommendation information sent to the user's device.

[0931] (Application Example 1)

[0932] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0933] Conventional land selection and drawing creation systems made it difficult for users to visually understand the area's layout during the process from inputting desired land conditions to modifying automatically generated drawings. Furthermore, the detailed information provided after land selection, including furniture placement suggestions, was limited, resulting in a poor user experience. To address this issue, there is a need for a more visual and interactive land selection and drawing generation system.

[0934] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0935] In this invention, the server includes means for inputting the land conditions desired by the user, means for crawling a real estate database based on the conditions and obtaining land information that meets the conditions, means for filtering the obtained land information and selecting the optimal land, means for notifying the user of the selected land information, means for automatically generating a drawing based on the land information, means for inputting a request for modification to the drawing, means for regenerating the drawing based on the modification request, means for recommending furniture based on the drawing, and means for providing real estate information as a 3D virtual tour based on the conditions input by the user and the selected land. This enables the user to select land and customize the drawing in a visual and interactive manner, and to receive more detailed information and suggestions for appropriate furniture placement.

[0936] "A means for users to input their desired land conditions" refers to an interface or form that allows users to input their desired conditions regarding land, such as specific price, area, location, and surrounding environment.

[0937] "Methods for crawling real estate databases and obtaining land information that meets the criteria" refers to programs or algorithms that automatically collect land information from the internet or specific databases based on conditions entered by the user.

[0938] "Methods for filtering acquired land information and selecting the most suitable land" refers to the process or algorithm used to narrow down collected land information according to the user's desired conditions and select the land that best meets those conditions.

[0939] "Means of notifying users of selected land information" refers to a system that notifies users of detailed information about selected land via email, in-app messages, or other means.

[0940] "Methods for automatically generating drawings based on land information" refers to the process of automatically creating drawings using specialized design software based on selected land.

[0941] "Means for inputting modification requests for drawings" refers to interfaces or forms that allow users to input changes or modifications to generated drawings.

[0942] "Means for regenerating drawings based on revision requests" refers to programs or algorithms that automatically regenerate drawings, reflecting revision requests entered by the user.

[0943] "Methods for recommending furniture based on drawings" refers to processes and algorithms that automatically suggest the optimal furniture and its placement based on completed drawings.

[0944] "A means of providing real estate information as a 3D virtual tour" refers to a system that allows users to visually tour a property using virtual reality or 3D simulation technology, based on selected land plots and generated blueprints.

[0945] This invention is a system that allows users to input their desired land conditions, crawls a land database based on those conditions, retrieves and filters land information that matches the conditions, and selects the most suitable land. Furthermore, it can automatically generate drawings based on the selected land information, regenerate them according to the user's modification requests, and recommend furniture based on the completed drawings. It also includes a function to provide users with real estate information as a 3D virtual tour.

[0946] The server receives the user's input criteria and crawls information from the internet or specific real estate databases. The crawl results are filtered, and land information that matches the criteria is collected. This allows the server to provide users with accurate and timely detailed information about the land they desire.

[0947] The server automatically generates architectural drawings based on land information. This process utilizes specialized computer-aided design (CAD) software to plan based on the shape and area of ​​the selected land. The CAD software streamlines the drawing generation process and provides highly accurate drawings.

[0948] The user can review the generated drawing and enter any necessary revision requests. The server receives this revision information and regenerates the drawing. In this way, customization according to the user's preferences becomes possible.

[0949] Based on the completed drawings, the server recommends the most suitable furniture. Furniture recommendations are performed using online catalogs and databases, allowing the user to be provided with appropriate furniture options.

[0950] Furthermore, the server provides a 3D virtual tour function, allowing users to virtually tour properties based on selected land information and generated drawings. Visualizing real estate information in 3D makes it easier for users to imagine the actual space, enabling more concrete consideration.

[0951] For example, if a user is looking for "a plot of land in Tokyo with a budget of 30 million yen or less and an area of ​​100 square meters or more," the following process takes place: The user enters their criteria through a smartphone application and sends them to the server. The server crawls and filters land information based on the specified criteria, selects the most suitable plot, and notifies the user. Next, the server automatically generates a 3D drawing based on the selected land information and provides it to the user. The user enters revision requests while viewing the drawing and reviews the regenerated drawing. Finally, the server provides a 3D virtual tour, including furniture placement suggestions, allowing the user to visualize the land and building plan more concretely.

[0952] Example of a prompt:

[0953] "I'm looking for a plot of land in Tokyo that's over 100 square meters and within a budget of 30 million yen. I'd like you to search for the most suitable plot, generate a virtual floor plan, and even suggest furniture placement options."

[0954] Thus, the present invention provides a system that offers total support, from selecting land that meets the user's requirements to creating drawings, conducting virtual tours, and recommending furniture.

[0955] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0956] Step 1:

[0957] The user enters the desired land conditions.

[0958] Users use a smartphone application to enter their desired land conditions (e.g., budget, area, location, surrounding environment, etc.) into an input form and send it to the server.

[0959] Input: Land conditions (price, area, location, surrounding environment, etc.)

[0960] Output: Input conditional data

[0961] Step 2:

[0962] The server crawls the land database and retrieves land information that meets the criteria.

[0963] The server crawls the internet or specific real estate databases based on the conditions entered by the user, and retrieves land information that matches those conditions. For example, it can filter by price, area, and location.

[0964] Input: Conditional data

[0965] Output: Acquired land information (candidate list)

[0966] Step 3:

[0967] The acquired land information is filtered to select the most suitable land.

[0968] The server filters the land information retrieved through crawling based on user criteria and selects the most suitable land information. This filtering process includes comparing price, area, and location.

[0969] Input: Acquired land information (candidate list)

[0970] Output: Optimal land information (selected items)

[0971] Step 4:

[0972] The selected land information will be notified to the user.

[0973] The server notifies the user's terminal of the selected, optimal land information. The notified information includes detailed information about the land (location, price, area, etc.).

[0974] Input: Optimal land information (selected items)

[0975] Output: Notification message sent to the user's terminal

[0976] Step 5:

[0977] Automatically generate drawings based on land information.

[0978] The server automatically generates basic design drawings and elevations using specialized CAD software based on the selected land information. This process automatically takes into account the shape and area of ​​the land.

[0979] Input: Optimal land information (selected items)

[0980] Output: Automatically generated drawing data (basic design drawings and elevation drawings)

[0981] Step 6:

[0982] Enter a request for revisions to the drawing.

[0983] The user reviews the generated drawings and enters any necessary modification requests. For example, they might enter specific requests such as "I want to make the living room larger" or "I want to change the location of the kitchen."

[0984] Input: Automated drawing data

[0985] Output: User correction request

[0986] Step 7:

[0987] Regenerate the drawing based on the revision request.

[0988] The server regenerates the drawing based on the modification request received from the user. It generates a new design drawing that reflects the modification request and provides it to the user.

[0989] Input: User correction request

[0990] Output: Regenerated drawing data (corrected design drawings)

[0991] Step 8:

[0992] Recommend furniture based on the drawings.

[0993] The server recommends the most suitable furniture and its placement from an online furniture catalog based on the completed drawings. The recommendation information is sent to the user's terminal, providing specific furniture options and placement suggestions.

[0994] Input: Regenerated drawing data

[0995] Output: Furniture recommendation information

[0996] Step 9:

[0997] Providing real estate information as a 3D virtual tour.

[0998] The server provides users with a 3D virtual tour based on the selected land and generated drawings. Through this tour, users can virtually view the property and form a concrete image of it.

[0999] Input: Optimal land information, regenerated drawing data

[1000] Output: 3D virtual tour

[1001] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1002] System Configuration

[1003] An embodiment of the present invention consists of a terminal in which the user inputs desired land conditions, a server that crawls a land database to acquire and filter land information that matches the conditions and select the optimal land, a server and terminal that automatically generate and modify drawings based on the land information and further recommend furniture, and an emotion engine that recognizes the user's emotions and responds accordingly.

[1004] System processing flow

[1005] 1. Enter conditions

[1006] Operator: User

[1007] Operation: The user enters their desired land conditions (price, area, location, surrounding environment, etc.) using a form displayed on the terminal and presses the submit button. The terminal then sends these conditions to the server.

[1008] 2. Acquisition of land information

[1009] Operating entity: Server

[1010] Operation: Based on the user's specified conditions, the server periodically crawls the land database and retrieves the latest land information that matches those conditions.

[1011] 3. Filtering land information

[1012] Operating entity: Server

[1013] Operation: The server filters land information acquired based on user criteria. This filtering selects land information that meets the specified criteria.

[1014] 4. Notification of land information

[1015] Operating entity: Server

[1016] Operation: The server selects the most suitable land from the filtered land information and notifies the user's terminal of that information. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[1017] 5. Automatic generation of recommended drawings

[1018] Operating entity: Server

[1019] Operation: Based on the notified land information, the server automatically generates basic drawings and elevation drawings using dedicated CAD software.

[1020] 6. Revision of drawings

[1021] Operator: User

[1022] Operation: The user reviews the generated drawing via the terminal and enters any necessary revision requests.

[1023] 7. Generation of revised drawings

[1024] Operating entity: Server

[1025] Operation: The server receives a modification request from the user and regenerates the drawing using CAD software. The regenerated drawing is based on the modification request.

[1026] 8. Furniture Recommendations

[1027] Operating entity: Server

[1028] Operation: Based on the completed drawings, the server crawls online furniture catalogs and retrieves furniture information suitable for those drawings. Furniture type, size, and design are all taken into consideration.

[1029] 9. Notification of furniture information

[1030] Operating entity: Server

[1031] Operation: The server sends a list of selected furniture and recommended placement suggestions to the user's device. The device then displays the furniture recommendation information.

[1032] Emotion Engine Processing Flow

[1033] 1. Recognition of emotions

[1034] Operating entity: Server

[1035] Operation: The emotion engine installed on the server analyzes the user's emotions from facial expressions, voice, text input, etc. The emotion engine identifies the user's emotions such as joy, surprise, disappointment, and anger.

[1036] 2. Emotion-based adjustment

[1037] Operating entity: Server

[1038] Operation: Based on the user's emotions recognized by the emotion engine, the system adjusts its output (notifications, drawings, furniture recommendations, etc.). For example, if the user is disappointed, the system will provide more detailed explanations or additional options.

[1039] Specific example

[1040] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[1041] 1. Enter the conditions:

[1042] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[1043] 2. Obtaining land information:

[1044] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[1045] 3. Filtering land information:

[1046] Based on the land information acquired by the server, the system recommends suitable land in Shinjuku Ward to the user.

[1047] 4. Notification of land information:

[1048] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[1049] 5. Automatic generation of recommended drawings:

[1050] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward.

[1051] 6. Revision of drawings:

[1052] The user enters a modification request stating, "I would like the living room to be a little larger."

[1053] 7. Generating revised drawings:

[1054] The server receives the correction request, regenerates the drawing, and resends it to the user.

[1055] 8. Furniture Recommendations:

[1056] The server recommends furniture such as sofas and tables suitable for a living room based on the floor plan, and sends the recommendations to the user's terminal.

[1057] If the emotion engine recognizes the emotion of "surprise" from the user's facial expressions or voice, the server will confirm that emotion with the user. If it is positive, it will take action such as suggesting multiple similar properties. Conversely, if a negative emotion is recognized, it can respond quickly and appropriately by suggesting further details or other options.

[1058] In this way, the system of the present invention can efficiently and consistently perform tasks ranging from land selection and drawing creation to revision, furniture recommendations, and even personalized responses based on emotion recognition, all based on the user's requirements.

[1059] The following describes the processing flow.

[1060] Step 1:

[1061] The user uses the input form displayed on the terminal to enter the desired land conditions (price, area, location, surrounding environment, etc.) and presses the submit button. The terminal then sends these conditions to the server.

[1062] Step 2:

[1063] The server crawls the real estate database based on the user's criteria received. The server periodically performs the crawling process to obtain the latest land information.

[1064] Step 3:

[1065] The server crawls and retrieves land information, which is then filtered based on the user's criteria. This filtering process selects land information that meets the specified conditions.

[1066] Step 4:

[1067] The server selects the most suitable land from the filtered land information. The selection criteria include user conditions as well as evaluation criteria pre-configured on the server.

[1068] Step 5:

[1069] The server notifies the user's terminal of the land information it has selected. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[1070] Step 6:

[1071] The user's device receives and displays a notification from the server. The user then reviews the presented land information.

[1072] Step 7:

[1073] Based on the recommended land information, the server automatically generates basic drawings and elevations using specialized CAD software.

[1074] Step 8:

[1075] The server automatically generates drawings and elevations and sends them to the user's terminal. The terminal then displays the received drawings.

[1076] Step 9:

[1077] The user reviews the provided drawings and enters any necessary revision requests. Examples of revision requests include changes to room size or layout. The user then submits the revision requests.

[1078] Step 10:

[1079] The server receives a modification request from the user and regenerates the drawing using CAD software. The regenerated drawing is based on the modification request.

[1080] Step 11:

[1081] The server sends the regenerated drawing back to the user's terminal. The terminal displays the corrected drawing.

[1082] Step 12:

[1083] Based on the completed drawings, the server crawls online furniture catalogs to retrieve furniture information suitable for those drawings. Factors such as furniture type, size, and design are taken into consideration.

[1084] Step 13:

[1085] The server sends a list of selected furniture and recommended placement suggestions to the user's device. The device then displays the furniture recommendations.

[1086] Step 14:

[1087] Users review the recommended furniture and make final adjustments to purchases and placement as needed.

[1088] Step 15:

[1089] The emotion engine installed on the server analyzes the user's emotions from facial expressions, voice, text input, etc. The emotion engine identifies the user's emotions such as joy, surprise, disappointment, and anger.

[1090] Step 16:

[1091] The server adjusts the system's output (notifications, drawings, furniture recommendations, etc.) based on the user's emotions recognized by the emotion engine. For example, if the user is disappointed, the system will provide more detailed explanations or additional options.

[1092] Specific example

[1093] Step 1:

[1094] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[1095] Step 2:

[1096] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[1097] Step 3:

[1098] The server filters the acquired land information based on the user's criteria and recommends land in Shinjuku Ward to the user.

[1099] Step 4:

[1100] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[1101] Step 5:

[1102] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward.

[1103] Step 6:

[1104] The server automatically generates drawings and elevations, which are then sent to the user and displayed on the user's device.

[1105] Step 7:

[1106] The user enters a modification request stating, "I would like the living room to be a little larger."

[1107] Step 8:

[1108] The server receives the correction request, regenerates the drawing, and resends it to the user.

[1109] Step 9:

[1110] The server recommends furniture such as sofas and tables suitable for the living room based on the floor plan, and sends the recommendations to the user's device.

[1111] Step 10:

[1112] The emotion engine recognizes the emotion of "surprise" from the user's facial expressions and voice.

[1113] Step 11:

[1114] The server checks the user's sentiment and, if the response is positive, suggests several similar properties. If the response is negative, it suggests further details or other options.

[1115] In this way, the system of the present invention can efficiently and consistently perform tasks ranging from land selection and drawing creation to revision, furniture recommendations, and even personalized responses based on emotion recognition, all based on the user's requirements.

[1116] (Example 2)

[1117] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1118] The traditional process of acquiring land, designing a residence, and selecting furniture requires considerable effort and time from the user, and there are challenges in providing sufficient support to enhance user satisfaction. In particular, there is a need for a system that efficiently and consistently handles the entire process, from quickly and accurately acquiring land information that matches the user's desired conditions, to automatically generating and modifying drawings based on that information, and recommending furniture. Furthermore, there is a lack of a system that can recognize the user's emotions and respond appropriately based on them.

[1119] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1120] In this invention, the server includes means for crawling a land database based on user-specified conditions and obtaining land information that meets those conditions; means for filtering the obtained land information and selecting the optimal land; means for automatically generating drawings based on the selected land information; and means including an emotion engine that analyzes the user's emotions and adjusts the system's output based on those emotions. This enables efficient execution of a series of processes from land selection based on user conditions to drawing creation, modification, and furniture recommendations, and also allows for flexible responses in accordance with the user's emotions.

[1121] A "user" is an entity that uses the system to input land conditions or request modifications to drawings.

[1122] A "land database" is a collection of data where various types of land information are stored. Information is retrieved through crawling.

[1123] "Crawling" is the act of using automated programs to periodically visit the internet and specific databases to collect information.

[1124] "Filtering" is the process of extracting only those data items that match specific criteria from a set of data.

[1125] "Optimal land" refers to land information that best matches the conditions entered by the user.

[1126] "Notification" refers to the act of sending land information or other information from a system to a user.

[1127] A "drawing" is a design plan for a house or building that is automatically generated based on land information.

[1128] A "revision request" is an instruction from the user to request changes to an automatically generated drawing.

[1129] "Regeneration" is the process of regenerating a drawing based on the user's modification request.

[1130] "Furniture recommendation" is the act of suggesting appropriate furniture types, sizes, and designs based on completed drawings.

[1131] An "emotion engine" is a program that analyzes the user's emotions from facial expressions, voice, text input, etc., and adjusts the system's output based on the results.

[1132] "Computer-aided design software" refers to specialized software used to create and edit design drawings using a computer.

[1133] System Configuration

[1134] The system of this invention consists of the following components.

[1135] 1. A terminal where the user enters their desired land conditions.

[1136] 2. A server that crawls the land database, retrieves and filters land information that matches the criteria, and selects the most suitable land.

[1137] 3. Server for automatically generating and modifying drawings based on land information.

[1138] 4. Terminal for recommending furniture based on drawings.

[1139] 5. An emotion engine that recognizes user emotions and responds accordingly.

[1140] Hardware and software to be used

[1141] Devices: Personal computers and smartphones

[1142] Server: A server computer with high-performance computing capabilities.

[1143] Land database: A database system for storing land information.

[1144] CAD software: Computer-aided design software

[1145] Emotion Engine: An AI program for analyzing user emotions.

[1146] Data processing and data calculation

[1147] Condition Input: The user uses a terminal to input the desired land conditions (price, area, location, surrounding environment, etc.). The entered information is sent to the server.

[1148] Land Information Acquisition and Filtering: The server crawls the land database based on the conditions received from the user. The acquired land information is filtered based on the conditions, and the most suitable land is selected.

[1149] Land Information Notification: Filtered information is sent to the user's device. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[1150] Automatic drawing generation: Based on the notified land information, the server automatically generates basic drawings and elevations using CAD software.

[1151] Drawing modification and regeneration: The user reviews the generated drawing via the terminal and enters any necessary modification requests. The server then regenerates the drawing based on these modification requests.

[1152] Furniture Recommendation: Based on the completed drawings, the server crawls online furniture catalogs to retrieve furniture information suitable for those drawings. Furniture type, size, and design are all taken into consideration.

[1153] Emotional Engine Processing

[1154] Emotion Recognition: The emotion engine analyzes emotions from the user's facial expressions, voice, text input, etc.

[1155] Emotion-based response: The emotion engine adjusts the system's output (notifications, drawings, furniture recommendations, etc.) based on the user's emotions.

[1156] Specific example

[1157] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[1158] 1. Enter the conditions:

[1159] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[1160] 2. Obtaining land information:

[1161] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[1162] 3. Filtering land information:

[1163] Based on the land information acquired by the server, the system recommends suitable land in Shinjuku Ward to the user.

[1164] 4. Notification of land information:

[1165] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[1166] 5. Automatic generation of recommended drawings:

[1167] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward.

[1168] 6. Revision of drawings:

[1169] The user enters a modification request stating, "I would like the living room to be a little larger."

[1170] 7. Generating revised drawings:

[1171] The server receives the correction request, regenerates the drawing, and resends it to the user.

[1172] 8. Furniture Recommendations:

[1173] The server recommends furniture such as sofas and tables suitable for a living room based on the floor plan, and sends the recommendations to the user's terminal.

[1174] Furthermore, if the emotion engine recognizes the emotion of "surprise" from the user's facial expressions or voice, the server will confirm this emotion with the user. If it is positive, it will take action such as suggesting multiple similar properties. Conversely, if a negative emotion is recognized, it can respond quickly and appropriately by suggesting further details or other options.

[1175] In this way, the system of the present invention can efficiently and consistently perform tasks ranging from land selection and drawing creation to revision, furniture recommendations, and even personalized responses based on emotion recognition, all based on the user's requirements.

[1176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1177] Step 1: Enter the conditions

[1178] Operator: User

[1179] Input: The user enters their desired land conditions (price, area, location, surrounding environment, etc.) into the input form.

[1180] Specific actions:

[1181] 1. The user launches a land information search application on their personal computer or smartphone.

[1182] 2. The application's initial screen displays a form where you can enter conditions such as "budget," "area," "location," and "surrounding environment."

[1183] 3. The user enters the respective conditions and presses the submit button.

[1184] Output: The terminal sends the entered condition information to the server.

[1185] Step 2: Obtaining land information

[1186] Operating entity: Server

[1187] Input: Data of desired conditions submitted by the user.

[1188] Specific actions:

[1189] 1. The server generates a query (search request) based on the conditions received from the user.

[1190] 2. The server uses this query to crawl the land database and collect land information that matches the criteria.

[1191] 3. The information obtained from the database covers a wide range of topics, including the location, price, area, and surrounding environment of the land.

[1192] Output: Temporarily save the list of land parcels obtained as search results and proceed to the next step.

[1193] Step 3: Filtering land information

[1194] Operating entity: Server

[1195] Input: List of searched land information

[1196] Specific actions:

[1197] 1. The server begins filtering the stored land information based on the user's criteria.

[1198] 2. The filtering process involves checking for matches against conditions such as price, area, location, and surrounding environment.

[1199] 3. Extract matching land information and create an optimal land information list.

[1200] Output: Generates a filtered list of optimal land information and proceeds to the next step.

[1201] Step 4: Notification of land information

[1202] Operating entity: Server

[1203] Input: Filtered list of optimal land information

[1204] Specific actions:

[1205] 1. The server formats the optimal land information and generates a message to notify the user.

[1206] 2. The message will include detailed information such as the land's location, price, area, and surrounding environment.

[1207] 3. Send the generated message to the user's device.

[1208] Output: A notification of land information is displayed on the user's device.

[1209] Step 5: Automatic generation of recommended drawings

[1210] Operating entity: Server

[1211] Input: Notified land information

[1212] Specific actions:

[1213] 1. The server launches dedicated computer-aided design software based on the selected land information.

[1214] 2. Input the shape and area of ​​the land, as well as the necessary house floor plan data, and issue commands to automatically generate the basic house plans and elevations.

[1215] 3. The drawing is generated within the software, and the result is saved to the server.

[1216] Output: Automatically generated basic drawings and elevations.

[1217] Step 6: Modify the drawing

[1218] Operator: User

[1219] Input: Auto-generated drawing

[1220] Specific actions:

[1221] 1. The user checks the automatically generated drawing displayed on the terminal.

[1222] 2. Enter any requests for modifications to the drawing, such as "I'd like the living room to be a little wider" or "I'd like the entrance to be on the right side," into the input form.

[1223] 3. Enter the correction request and press the submit button.

[1224] Output: The terminal sends a correction request to the server.

[1225] Step 7: Generate revised drawings

[1226] Operating entity: Server

[1227] Input: Correction request submitted by the user

[1228] Specific actions:

[1229] 1. The server analyzes the correction request received from the user.

[1230] 2. Based on the analysis results, restart the computer-aided design software.

[1231] 3. Issue an order to regenerate the drawing in accordance with the revision request, and generate a new drawing.

[1232] 4. Save the regenerated drawing and resend it to the user.

[1233] Output: The modified drawing is sent to the user's terminal.

[1234] Step 8: Furniture Recommendations

[1235] Operating entity: Server

[1236] Input: Completed drawing

[1237] Specific actions:

[1238] 1. The server analyzes the completed drawings and determines the optimal type, size, and design of furniture for each room.

[1239] 2. The server crawls online furniture catalogs and searches for furniture information that matches the determined criteria.

[1240] 3. Generate a furniture list and send it to the user's device along with a recommended layout.

[1241] Output: Furniture recommendations and suggested layouts are displayed on the user's device.

[1242] Step 9: Recognizing Emotions

[1243] Operating entity: Server

[1244] Input: User facial expressions, voice, text input

[1245] Specific actions:

[1246] 1. The emotion engine installed on the server captures the user's facial expressions and voice obtained from the webcam and microphone.

[1247] 2. Include text input as part of the analysis.

[1248] 3. The emotion engine analyzes this information to identify the user's emotions (joy, surprise, disappointment, anger, etc.).

[1249] Output: User sentiment data is generated.

[1250] Step 10: Emotion-based responses

[1251] Operating entity: Server

[1252] Input: Emotional data generated by the emotion engine

[1253] Specific actions:

[1254] 1. The system's output is adjusted based on the emotion type recognized by the emotion engine.

[1255] 2. For example, if the user is disappointed, the server will provide a detailed explanation or additional options.

[1256] 3. If the user is pleased, provide positive feedback, such as suggesting multiple similar properties.

[1257] Output: The output of the adjusted system is notified to the user.

[1258] In this way, the system can consistently and efficiently perform tasks such as land selection based on user conditions, drawing creation and modification, furniture recommendations, and even emotional recognition-based responses.

[1259] (Application Example 2)

[1260] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1261] Traditional real estate selection systems have struggled to efficiently find properties that meet users' desired criteria. Furthermore, post-purchase design and furniture selection can be burdensome for users. Similarly, in shopping, gathering information on desired products and improving customer satisfaction during purchase remain challenges. In particular, there has been a lack of mechanisms to reflect users' emotions in real time and provide appropriate suggestions.

[1262] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1263] In this invention, the server includes means for inputting the land conditions desired by the user; means for crawling a real estate database based on the conditions and obtaining real estate information that matches the conditions; means for filtering the obtained real estate information and selecting the most suitable real estate; means for notifying the user of the selected real estate information; means for automatically generating drawings based on the real estate information; means for inputting requests for modifications to the drawings; means for regenerating the drawings based on the modification requests; means for recommending furniture based on the drawings; means for inputting product conditions desired by the user and obtaining product information that matches the conditions; means for notifying the user of recommended products based on the product information; and means for recognizing the user's emotions and adjusting the suggested content according to those emotions.

[1264] This makes it possible to provide users with an efficient and satisfying experience, from selecting and designing their desired property to recommending furniture and even shopping.

[1265] "A means for users to input their desired land conditions" refers to an interface for users to input their desired real estate conditions (price, area, location, surrounding environment, etc.) and transmit this information to the system.

[1266] "A means of crawling real estate databases and obtaining real estate information that meets the specified conditions" refers to a mechanism for automatically collecting real estate information that matches specified conditions from multiple real estate databases on the internet.

[1267] "Methods for filtering acquired real estate information and selecting the most suitable property" refers to algorithms or software that select the property that best matches the user's criteria from the collected real estate information.

[1268] "Means of notifying users of selected real estate information" refers to a system for displaying, alerting, or otherwise communicating identified real estate information to the user's terminal.

[1269] "Methods for automatically generating drawings based on real estate information" refers to a function that automatically creates design drawings and elevation drawings using specialized design software based on acquired real estate information.

[1270] "Means for inputting modification requests for drawings" refers to an interface for users to input and submit requests for changes or modifications to generated drawings.

[1271] "Means for regenerating drawings based on revision requests" refers to algorithms or software for regenerating and updating design drawings to reflect revision requests from users.

[1272] "A means of recommending furniture based on drawings" refers to a function that considers the layout of the generated design drawings and proposes the most suitable furniture and interior design to the user.

[1273] "A means of inputting desired product conditions and obtaining product information that meets those conditions" refers to an interface and algorithm for inputting desired product conditions (price, features, performance, etc.) and collecting product information that matches those conditions.

[1274] "A means of notifying users of recommended products based on product information" refers to a system that selects the most suitable product for the user based on collected product information and notifies them of it.

[1275] "Means for recognizing user emotions and adjusting suggestions accordingly" refers to an emotion recognition engine and algorithm that analyzes the user's emotional state from their facial expressions and voice, and dynamically changes and adjusts the suggested content based on the results.

[1276] System Configuration

[1277] The system for implementing this invention consists of a terminal for the user to input desired conditions, a server that crawls a real estate database to acquire and filter information that matches the conditions and select the most suitable property, a server and terminal that automatically generate and modify drawings based on the property information and further recommend furniture, and an emotion engine that recognizes the user's emotions and responds accordingly.

[1278] Hardware and software used

[1279] Smartphone: Use an iPhone or Android smartphone as the user's input device.

[1280] Servers: For cloud services, we will use Amazon Web Services (AWS) or Google Cloud Platform.

[1281] Emotion Engine: Emotion recognition uses either the Microsoft Azure Emotion API or the Google Cloud Vision API.

[1282] Artificial intelligence: Generative AI models such as OpenAI's GPT-4 are used.

[1283] Database: MongoDB or Firebase are used for data management.

[1284] Design software: Automatic drawing generation is performed using design software such as AutoCAD API.

[1285] System processing

[1286] At each processing stage of the system, data processing and calculations are performed as follows:

[1287] 1. Enter conditions

[1288] Users use a form in a smartphone app to enter their desired real estate conditions (price, area, location, surrounding environment, etc.) and product conditions (price, features, performance, etc.), and then submit them to the server.

[1289] 2. Acquisition and filtering of real estate information

[1290] The server crawls the specified real estate database and retrieves property information that matches the user's criteria. Then, it uses a filtering algorithm (written in Python) to select the most suitable property.

[1291] 3. Notification of real estate information

[1292] Filtered real estate information is sent to the user's smartphone. Detailed information (price, location, surrounding environment, etc.) is displayed.

[1293] 4. Automatic generation and modification of drawings

[1294] The server automatically generates design drawings and elevations using design software (AutoCAD API) based on the acquired real estate information. If a user requests revisions to the drawings, the server incorporates those changes and regenerates the drawings.

[1295] 5. Furniture Recommendations

[1296] Based on the automatically generated drawings, the server crawls online furniture catalogs and retrieves furniture information suitable for the drawings. It then provides recommendations considering furniture type, size, design, and other factors.

[1297] 6. Acquisition and notification of product information

[1298] Based on product criteria, the system crawls multiple product databases on the internet (such as the Google Shopping API and Amazon Product Advertising API) to retrieve suitable product information. The retrieved product information is then notified to the user, and detailed information is displayed.

[1299] 7. Emotion Recognition and Response Adjustment

[1300] The system uses the smartphone's built-in camera and microphone to collect the user's facial expressions and voice. An emotion engine (such as the Azure Emotion API) analyzes this data and adjusts the system's output according to the emotion. For positive emotions, it suggests additional related products; for negative emotions, it provides detailed explanations or other options.

[1301] Specific example

[1302] For example, if a user enters their desired real estate conditions as "budget of 30 million yen, area of ​​100 square meters or more, location: Tokyo, condition: good transportation access," the server crawls the land database and finds properties that match the conditions. Based on that information, it generates a blueprint and incorporates the user's modification requests. Finally, it recommends furniture that suits the generated blueprint. If the emotion engine recognizes the user's emotion of "surprise," the system will suggest additional similar properties.

[1303] Example of a prompt

[1304] Requirements: A smartwatch with a price under 30 million yen, in red, and featuring waterproof functionality. Please recommend related products and generate layout proposals.

[1305] This allows users to easily obtain real estate and product information that best suits their desired conditions, and furthermore, receive highly satisfying suggestions through emotion recognition.

[1306] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1307] Step 1:

[1308] Condition Input

[1309] Users use a smartphone app to input their desired real estate conditions (price, area, location, surrounding environment, etc.) and product conditions (price, features, performance, etc.). The entered conditions are sent to the server via the smartphone app.

[1310] Input: User's desired conditions (e.g., price 30 million yen, area 100 square meters or more, location: Tokyo, condition: convenient transportation)

[1311] Output: Conditional data sent to the server

[1312] Step 2:

[1313] Acquisition of real estate information

[1314] The server crawls the specified real estate database and retrieves property information that matches the user's criteria. During this process, periodic queries are executed. A crawl script, often using Python, is run to collect the latest property information that meets the specified criteria.

[1315] Input: Conditional data sent by the user to the server

[1316] Output: Dataset of real estate information that matches the criteria

[1317] Step 3:

[1318] Filtering real estate information

[1319] The server executes a filtering algorithm based on the acquired real estate information to select the most suitable property. Filtering is performed based on pre-configured user criteria.

[1320] Input: Dataset of acquired real estate information, user conditions

[1321] Output: Filtered and optimized real estate information

[1322] Step 4:

[1323] Real estate information notification

[1324] The server notifies the user's smartphone of filtered real estate information. The notification includes detailed information about the property (price, location, surrounding environment, etc.). The user's smartphone app receives and displays this information.

[1325] Input: Filtered property information

[1326] Output: Property details displayed on the user's smartphone

[1327] Step 5:

[1328] Automatic generation of drawings

[1329] The server automatically generates design drawings and elevations using design software (AutoCAD API) based on the acquired real estate information. A dedicated script is executed, and detailed drawings are created based on the input data.

[1330] Input: Filtered property information

[1331] Output: Automatically generated design drawings and elevations

[1332] Step 6:

[1333] Request for revision of drawings

[1334] The user enters revision requests based on automatically generated drawings. They specify in detail the areas requiring modification and the elements they wish to add via a smartphone app. The revision requests are then sent to the server.

[1335] Input: User correction request

[1336] Output: Correction request data sent to the server

[1337] Step 7:

[1338] Generation of revised drawings

[1339] The server receives the modification request from the user and generates the modified drawing again using the design software (AutoCAD API). Based on the user's specifications, a new drawing is created that reflects the necessary changes.

[1340] Input: Modification request data, initial design drawings

[1341] Output: Revised blueprints

[1342] Step 8:

[1343] Furniture recommendations

[1344] Based on the final design plans, the server crawls online furniture catalogs and recommends furniture that fits those plans. Considering factors such as furniture type, size, and design, a list of suitable furniture is generated for the user.

[1345] Input: Modified blueprint

[1346] Output: Furniture recommendation information

[1347] Step 9:

[1348] Product information acquisition and notification

[1349] The server crawls multiple product databases on the internet based on the user's desired product criteria and retrieves suitable product information. The retrieved product information is then displayed as a notification on the user's smartphone.

[1350] Input: User's desired product specifications

[1351] Output: Product information displayed on the user's smartphone

[1352] Step 10:

[1353] Emotion recognition and response adjustment

[1354] The smartphone's built-in camera and microphone are used to collect the user's facial expressions and voice. An emotion engine (such as the Azure Emotion API) analyzes this data to identify the user's emotions. If the emotion is positive, additional suggestions are provided; if it is negative, more detailed explanations and other options are offered.

[1355] Input: User's facial expressions and voice data

[1356] Output: Adjusted proposal or additional options

[1357] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1358] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1359] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1360] [Third Embodiment]

[1361] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1362] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1363] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1364] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1365] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1366] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1367] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1368] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1369] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1370] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1371] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1372] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1373] System Configuration

[1374] An embodiment of the present invention consists of a terminal in which the user inputs the desired land conditions, a server that crawls a land database, acquires and filters land information that matches the conditions, and selects the most suitable land, and a server and terminal that automatically generate and modify drawings based on the land information and further recommend furniture.

[1375] System processing flow

[1376] 1. Enter conditions

[1377] Operator: User

[1378] Operation: The user enters the desired land conditions (price, area, location, surrounding environment, etc.) using a form displayed on the terminal, and then presses the submit button to send that information to the server.

[1379] 2. Acquisition of land information

[1380] Operating entity: Server

[1381] Operation: Based on the user's specified conditions, the server periodically crawls the land database and retrieves the latest land information that matches those conditions.

[1382] 3. Filtering land information

[1383] Operating entity: Server

[1384] Operation: The server filters land information acquired based on user criteria and selects suitable land information.

[1385] 4. Notification of land information

[1386] Operating entity: Server

[1387] Operation: The server notifies the user's terminal of information about the selected suitable land. This notification includes detailed information about the land (location, price, area, etc.).

[1388] 5. Automatic generation of recommended drawings

[1389] Operating entity: Server

[1390] Operation: Based on the notified land information, the server automatically generates basic drawings and elevations using dedicated CAD software.

[1391] 6. Revision of drawings

[1392] Operator: User

[1393] Operation: The user reviews the generated drawing via the terminal and enters any necessary revision requests.

[1394] 7. Generation of revised drawings

[1395] Operating entity: Server

[1396] Operation: The server receives a correction request from the user and regenerates the drawing based on the correction. The regenerated drawing is then sent back to the user's terminal.

[1397] 8. Furniture Recommendations

[1398] Operating entity: Server

[1399] Operation: Based on the completed drawings, the server recommends the most suitable furniture and its placement from an online furniture catalog. The recommendation information is sent to the user's device.

[1400] Specific example

[1401] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[1402] 1. Enter the conditions:

[1403] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[1404] 2. Obtaining land information:

[1405] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[1406] 3. Filtering land information:

[1407] Based on the land information acquired by the server, the system recommends suitable land in Shinjuku Ward to the user.

[1408] 4. Notification of land information:

[1409] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[1410] 5. Automatic generation of recommended drawings:

[1411] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward and sends them to the user.

[1412] 6. Revision of drawings:

[1413] The user enters a modification request stating, "I would like the living room to be a little larger."

[1414] 7. Generating revised drawings:

[1415] The server receives the correction request, regenerates the drawing, and resends it to the user.

[1416] 8. Furniture Recommendations:

[1417] The server recommends furniture such as sofas and tables suitable for a living room based on the floor plan, and sends the recommendations to the user's terminal.

[1418] In this way, the system of the present invention can efficiently perform a consistent process from land selection to drawing creation, modification, and furniture recommendation, based on the user's requirements.

[1419] The following describes the processing flow.

[1420] Step 1:

[1421] The user uses the input form displayed on the terminal to enter the desired land conditions (price, area, location, surrounding environment, etc.) and presses the submit button. The terminal then sends these conditions to the server.

[1422] Step 2:

[1423] The server crawls the real estate database based on the user's criteria received. The crawling process is performed periodically to retrieve the latest land information.

[1424] Step 3:

[1425] The server crawls and retrieves land information, which is then filtered based on the user's criteria. This filtering process selects land information that meets the specified conditions.

[1426] Step 4:

[1427] The server selects the most suitable land from the filtered land information. The selection criteria include user conditions as well as evaluation criteria pre-configured on the server.

[1428] Step 5:

[1429] The server notifies the user's terminal of the land information it has selected. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[1430] Step 6:

[1431] The user's device receives and displays a notification from the server. The user then reviews the presented land information.

[1432] Step 7:

[1433] Based on the recommended land information, the server automatically generates basic drawings and elevations using specialized CAD software.

[1434] Step 8:

[1435] The server automatically generates drawings and elevations and sends them to the user's terminal. The terminal then displays the received drawings.

[1436] Step 9:

[1437] The user reviews the provided drawings and enters any necessary revision requests. Examples of revision requests include changes to room size or layout. The user then submits the revision requests.

[1438] Step 10:

[1439] The server receives a modification request from the user and regenerates the drawing using CAD software. The regenerated drawing is based on the modification request.

[1440] Step 11:

[1441] The server sends the regenerated drawing back to the user's terminal. The terminal displays the corrected drawing.

[1442] Step 12:

[1443] Based on the completed drawings, the server crawls online furniture catalogs to retrieve furniture information suitable for those drawings. Factors such as furniture type, size, and design are taken into consideration.

[1444] Step 13:

[1445] The server sends a list of selected furniture and recommended placement suggestions to the user's device. The device then displays the furniture recommendations.

[1446] Step 14:

[1447] Users review the recommended furniture and make final adjustments to purchases and placement as needed.

[1448] (Example 1)

[1449] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1450] When purchasing a modern home, many users spend considerable time and effort finding suitable land, creating optimal blueprints, and then selecting furniture. Traditional methods fragment the process, requiring users to interact with multiple platforms and vendors at each stage, as these tasks—land information gathering and filtering, blueprint creation and revision, and furniture selection—are disconnected. This process is inefficient and often leads to lower overall satisfaction. Furthermore, challenges include the inability to obtain suitable land information in a timely manner and the cumbersome process of revising blueprints.

[1451] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1452] In this invention, the server includes means for the user to input desired land conditions, means for crawling a land database based on the conditions and obtaining land information that matches the conditions, and means for filtering the obtained land information and selecting the optimal land. This allows the user to efficiently obtain desired land information and receive automatically generated blueprints and recommendations for optimal furniture based on that information. This enables the entire process from land selection to blueprint creation and furniture selection to be carried out efficiently in one go, thereby improving user satisfaction.

[1453] A "user" is an entity that uses this system to input desired land conditions and receives selected land information, blueprints, and furniture recommendations.

[1454] "Means for inputting conditions" refers to a device or system that provides an interface for users to input detailed conditions of land they desire (such as price, area, location, and surrounding environment).

[1455] A "land database" is a source of information that stores information on multiple plots of land and is used to retrieve land information that meets specific criteria through crawling.

[1456] "Crawling" refers to a software technology that involves a program or a series of operations for automatically collecting information from land databases on the internet.

[1457] "Filtering methods" refer to software algorithms used to select information that matches the user's input criteria from the acquired land information.

[1458] "Land information" refers to information about a specific piece of land, including details such as location, price, and area.

[1459] "Notification means" refers to communication methods for sending filtered land information to the user's device. This includes methods such as email and push notifications.

[1460] A "design drawing" is a diagram that shows the basic layout and structure of a building to be constructed on a desired plot of land.

[1461] "Means of automatic generation" refers to an algorithm or program that automatically creates building blueprints using specific software (e.g., CAD software) based on input land information.

[1462] A "means for inputting modification requests" refers to a system that provides an interface for users to review generated blueprints and input necessary changes or modifications.

[1463] A "means of regeneration" refers to a software algorithm for recreating the design blueprint to reflect the modification requests.

[1464] "A means of recommending furniture" refers to software that suggests appropriate furniture and its placement based on a completed blueprint.

[1465] The "reporting database" is a database used to temporarily store suitable land information after filtering.

[1466] "Means for generating furniture arrangement plans" refers to algorithms or software for creating the optimal furniture arrangement based on a completed design drawing.

[1467] An embodiment of the present invention consists of a terminal in which the user inputs desired land conditions, a server that crawls a land database to acquire and filter land information that matches the conditions and select the most suitable land, and a server and terminal that automatically generate and modify building blueprints based on the land information and further recommend furniture.

[1468] Hardware and software to be used

[1469] Terminal: A client device used by the user to operate the system (PC, tablet, smartphone, etc.)

[1470] Server: A central server that processes user input and performs tasks such as data retrieval, filtering, notifications, diagram generation, and recommendations.

[1471] Software and libraries to be used:

[1472] Web browser: Provides an interface for users to enter conditions.

[1473] Python: A programming language used for data crawling.

[1474] Beautiful Soup, Selenium: Libraries for crawling land databases

[1475] SQL (MySQL, PostgreSQL, etc.): Database management system

[1476] AutoCAD API: CAD software for automatically generating building blueprints.

[1477] Email sending API, push notification API: Communication methods for notifying users of land information and map URLs.

[1478] IKEA API, Amazon API: Online catalogs for recommending furniture

[1479] Explanation of the processing flow

[1480] 1. Enter conditions

[1481] Operator: User

[1482] Specific operation: The user opens a web page on their device, enters details of the desired land (price, area, location, surrounding environment, etc.) into a form, and clicks the submit button to send it to the server.

[1483] 2. Acquisition of land information

[1484] Operating entity: Server

[1485] Specific operation: The server uses Python to crawl a specified land database using Beautiful Soup or Selenium, retrieves land information that meets the criteria, and stores it in a temporary storage database.

[1486] 3. Filtering land information

[1487] Operating entity: Server

[1488] Specific operation: The server reads data retrieved from a temporary storage database and filters it based on user criteria. The filtered data is then saved to the reporting database as matching land information.

[1489] 4. Notification of land information

[1490] Operating entity: Server

[1491] Specific operation: The server uses email sending APIs and push notification APIs to notify users of filtered land information.

[1492] 5. Automatic generation of recommended drawings

[1493] Operating entity: Server

[1494] Specific operation: The server uses the AutoCAD API to automatically generate basic house drawings and elevations based on the provided land information. The generated drawings are saved on the server, and the URL is notified to the user.

[1495] 6. Revision of drawings

[1496] Operator: User

[1497] Specific operation: The user opens the notified URL and enters a request to review and modify the drawing. The modification request is sent to the server.

[1498] 7. Generation of revised drawings

[1499] Operating entity: Server

[1500] Specific operation: The server receives the correction request, regenerates the drawing using the AutoCAD API, and notifies the user again.

[1501] 8. Furniture Recommendations

[1502] Operating entity: Server

[1503] Specific operation: Based on the completed drawing, the server retrieves information on suitable furniture from the IKEA API and Amazon API, and notifies the user of the recommended furniture.

[1504] Specific example

[1505] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[1506] 1. Enter the conditions:

[1507] The user enters the following conditions on their device: "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Convenient transportation," and sends it to the server.

[1508] 2. Obtaining land information:

[1509] The server uses Python's Beautiful Soup to crawl the land database and finds a 120 square meter plot of land in Shinjuku Ward.

[1510] 3. Filtering land information:

[1511] The server filters the acquired land information, selects land information that meets the specified criteria, and saves it to the reporting database.

[1512] 4. Notification of land information:

[1513] The server uses an email API to notify users of selected land information (e.g., 120 square meters in Shinjuku Ward, priced at 30 million yen).

[1514] 5. Automatic generation of recommended drawings:

[1515] The server uses the AutoCAD API to automatically generate design drawings and elevation drawings based on the acquired land information, and notifies the user of the URL.

[1516] 6. Revision of drawings:

[1517] The user opens the URL they were notified with, enters a modification request such as "I want the living room to be a little bigger," and sends it to the server.

[1518] 7. Generating revised drawings:

[1519] The server receives the correction request, uses the AutoCAD API again to generate the corrected drawing, and notifies the user again.

[1520] 8. Furniture Recommendations:

[1521] The server uses the Amazon API to recommend furniture suitable for the generated drawings to the user.

[1522] Examples of prompts for generative AI models

[1523] The following are examples of prompt statements to input into the generative AI model.

[1524] "For users searching for land in Tokyo with a budget of 30 million yen, over 100 square meters, and convenient transportation access, please acquire, filter, and recommend appropriate land information. Furthermore, generate basic house plans based on the land, update the plans according to user requests, and finally, recommend furniture."

[1525] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1526] Step 1:

[1527] Condition Input

[1528] Operator: User

[1529] Specific actions:

[1530] The user starts up their device and opens the system's webpage in their browser. They enter their desired land conditions (price, area, location, surrounding environment, etc.) into the form. They click the "Submit" button to send the conditions to the server.

[1531] input:

[1532] Desired land conditions (price, area, location, surrounding environment, etc.)

[1533] output:

[1534] The entered conditions are sent to the server.

[1535] Step 2:

[1536] Acquisition of land information

[1537] Operating entity: Server

[1538] Specific actions:

[1539] The server receives the conditions sent by the user. Using Python libraries (such as Beautiful Soup or Selenium), it crawls the specified land database and retrieves the latest land information that matches the conditions. The retrieved land information is stored in a temporary storage database.

[1540] input:

[1541] Land conditions entered by the user

[1542] output:

[1543] Land information stored in a temporary storage database

[1544] Step 3:

[1545] Land information filtering

[1546] Operating entity: Server

[1547] Specific actions:

[1548] The server reads data retrieved from a temporary storage database and filters it using SQL queries based on user criteria. Based on the filtering results, it selects suitable land information and saves it to the reporting database.

[1549] input:

[1550] Land information stored in a temporary storage database

[1551] output:

[1552] Save filtered land information to the reporting database.

[1553] Step 4:

[1554] Land information notification

[1555] Operating entity: Server

[1556] Specific actions:

[1557] The server prepares to send notifications to users based on the filtered land information. It uses email sending APIs and push notification APIs to send the filtered land information to the user's device.

[1558] input:

[1559] Filtered land information stored in the reporting database

[1560] output:

[1561] Notifications to the user's device

[1562] Step 5:

[1563] Automatic generation of recommended drawings

[1564] Operating entity: Server

[1565] Specific actions:

[1566] Based on the provided land information, the server automatically generates basic house plans and elevations using the AutoCAD API. The generated plans are saved as image files on the server, and a URL for the plans is generated. This URL is then notified to the user.

[1567] input:

[1568] Land information stored in the reporting database

[1569] output:

[1570] Notification containing the URL of the generated drawing

[1571] Step 6:

[1572] Drawing revisions

[1573] Operator: User

[1574] Specific actions:

[1575] The user opens the URL of the drawing notified from the server using their device. They review the drawing and enter revision requests using the form or comment function. Revision requests are sent from the device to the server in real time.

[1576] input:

[1577] User correction request

[1578] output:

[1579] Correction request sent to the server

[1580] Step 7:

[1581] Generation of revised drawings

[1582] Operating entity: Server

[1583] Specific actions:

[1584] The server receives the user's modification request and uses the AutoCAD API, etc., again to regenerate the drawing that reflects the modifications. The URL of the regenerated drawing is then sent to the user's device again.

[1585] input:

[1586] User correction request

[1587] output:

[1588] Notification including the URL of the revised drawing

[1589] Step 8:

[1590] Furniture recommendations

[1591] Operating entity: Server

[1592] Specific actions:

[1593] The server crawls online furniture catalogs (such as the IKEA API and Amazon API) based on the completed drawings. It selects furniture suitable for the drawings and generates optimal furniture and layout plans. This recommendation information is then notified to the user's device.

[1594] input:

[1595] Completed drawings

[1596] output:

[1597] Furniture recommendation information sent to the user's device.

[1598] (Application Example 1)

[1599] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1600] Conventional land selection and drawing creation systems made it difficult for users to visually understand the area's layout during the process from inputting desired land conditions to modifying automatically generated drawings. Furthermore, the detailed information provided after land selection, including furniture placement suggestions, was limited, resulting in a poor user experience. To address this issue, there is a need for a more visual and interactive land selection and drawing generation system.

[1601] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1602] In this invention, the server includes means for inputting the land conditions desired by the user, means for crawling a real estate database based on the conditions and obtaining land information that meets the conditions, means for filtering the obtained land information and selecting the optimal land, means for notifying the user of the selected land information, means for automatically generating a drawing based on the land information, means for inputting a request for modification to the drawing, means for regenerating the drawing based on the modification request, means for recommending furniture based on the drawing, and means for providing real estate information as a 3D virtual tour based on the conditions input by the user and the selected land. This enables the user to select land and customize the drawing in a visual and interactive manner, and to receive more detailed information and suggestions for appropriate furniture placement.

[1603] "A means for users to input their desired land conditions" refers to an interface or form that allows users to input their desired conditions regarding land, such as specific price, area, location, and surrounding environment.

[1604] "Methods for crawling real estate databases and obtaining land information that meets the criteria" refers to programs or algorithms that automatically collect land information from the internet or specific databases based on conditions entered by the user.

[1605] "Methods for filtering acquired land information and selecting the most suitable land" refers to the process or algorithm used to narrow down collected land information according to the user's desired conditions and select the land that best meets those conditions.

[1606] "Means of notifying users of selected land information" refers to a system that notifies users of detailed information about selected land via email, in-app messages, or other means.

[1607] "Methods for automatically generating drawings based on land information" refers to the process of automatically creating drawings using specialized design software based on selected land.

[1608] "Means for inputting modification requests for drawings" refers to interfaces or forms that allow users to input changes or modifications to generated drawings.

[1609] "Means for regenerating drawings based on revision requests" refers to programs or algorithms that automatically regenerate drawings, reflecting revision requests entered by the user.

[1610] "Methods for recommending furniture based on drawings" refers to processes and algorithms that automatically suggest the optimal furniture and its placement based on completed drawings.

[1611] "A means of providing real estate information as a 3D virtual tour" refers to a system that allows users to visually tour a property using virtual reality or 3D simulation technology, based on selected land plots and generated blueprints.

[1612] This invention is a system that allows users to input their desired land conditions, crawls a land database based on those conditions, retrieves and filters land information that matches the conditions, and selects the most suitable land. Furthermore, it can automatically generate drawings based on the selected land information, regenerate them according to the user's modification requests, and recommend furniture based on the completed drawings. It also includes a function to provide users with real estate information as a 3D virtual tour.

[1613] The server receives the user's input criteria and crawls information from the internet or specific real estate databases. The crawl results are filtered, and land information that matches the criteria is collected. This allows the server to provide users with accurate and timely detailed information about the land they desire.

[1614] The server automatically generates architectural drawings based on land information. This process utilizes specialized computer-aided design (CAD) software to plan based on the shape and area of ​​the selected land. The CAD software streamlines the drawing generation process and provides highly accurate drawings.

[1615] The user can review the generated drawing and enter any necessary revision requests. The server receives this revision information and regenerates the drawing. In this way, customization according to the user's preferences becomes possible.

[1616] Based on the completed drawings, the server recommends the most suitable furniture. Furniture recommendations are performed using online catalogs and databases, allowing the user to be provided with appropriate furniture options.

[1617] Furthermore, the server provides a 3D virtual tour function, allowing users to virtually tour properties based on selected land information and generated drawings. Visualizing real estate information in 3D makes it easier for users to imagine the actual space, enabling more concrete consideration.

[1618] For example, if a user is looking for "a plot of land in Tokyo with a budget of 30 million yen or less and an area of ​​100 square meters or more," the following process takes place: The user enters their criteria through a smartphone application and sends them to the server. The server crawls and filters land information based on the specified criteria, selects the most suitable plot, and notifies the user. Next, the server automatically generates a 3D drawing based on the selected land information and provides it to the user. The user enters revision requests while viewing the drawing and reviews the regenerated drawing. Finally, the server provides a 3D virtual tour, including furniture placement suggestions, allowing the user to visualize the land and building plan more concretely.

[1619] Example of a prompt:

[1620] "I'm looking for a plot of land in Tokyo that's over 100 square meters and within a budget of 30 million yen. I'd like you to search for the most suitable plot, generate a virtual floor plan, and even suggest furniture placement options."

[1621] Thus, the present invention provides a system that offers total support, from selecting land that meets the user's requirements to creating drawings, conducting virtual tours, and recommending furniture.

[1622] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1623] Step 1:

[1624] The user enters the desired land conditions.

[1625] Users use a smartphone application to enter their desired land conditions (e.g., budget, area, location, surrounding environment, etc.) into an input form and send it to the server.

[1626] Input: Land conditions (price, area, location, surrounding environment, etc.)

[1627] Output: Input conditional data

[1628] Step 2:

[1629] The server crawls the land database and retrieves land information that meets the criteria.

[1630] The server crawls the internet or specific real estate databases based on the conditions entered by the user, and retrieves land information that matches those conditions. For example, it can filter by price, area, and location.

[1631] Input: Conditional data

[1632] Output: Acquired land information (candidate list)

[1633] Step 3:

[1634] The acquired land information is filtered to select the most suitable land.

[1635] The server filters the land information retrieved through crawling based on user criteria and selects the most suitable land information. This filtering process includes comparing price, area, and location.

[1636] Input: Acquired land information (candidate list)

[1637] Output: Optimal land information (selected items)

[1638] Step 4:

[1639] The selected land information will be notified to the user.

[1640] The server notifies the user's terminal of the selected, optimal land information. The notified information includes detailed information about the land (location, price, area, etc.).

[1641] Input: Optimal land information (selected items)

[1642] Output: Notification message sent to the user's terminal

[1643] Step 5:

[1644] Automatically generate drawings based on land information.

[1645] The server automatically generates basic design drawings and elevations using specialized CAD software based on the selected land information. This process automatically takes into account the shape and area of ​​the land.

[1646] Input: Optimal land information (selected items)

[1647] Output: Automatically generated drawing data (basic design drawings and elevation drawings)

[1648] Step 6:

[1649] Enter a request for revisions to the drawing.

[1650] The user reviews the generated drawings and enters any necessary modification requests. For example, they might enter specific requests such as "I want to make the living room larger" or "I want to change the location of the kitchen."

[1651] Input: Automated drawing data

[1652] Output: User correction request

[1653] Step 7:

[1654] Regenerate the drawing based on the revision request.

[1655] The server regenerates the drawing based on the modification request received from the user. It generates a new design drawing that reflects the modification request and provides it to the user.

[1656] Input: User correction request

[1657] Output: Regenerated drawing data (corrected design drawings)

[1658] Step 8:

[1659] Recommend furniture based on the drawings.

[1660] The server recommends the most suitable furniture and its placement from an online furniture catalog based on the completed drawings. The recommendation information is sent to the user's terminal, providing specific furniture options and placement suggestions.

[1661] Input: Regenerated drawing data

[1662] Output: Furniture recommendation information

[1663] Step 9:

[1664] Providing real estate information as a 3D virtual tour.

[1665] The server provides users with a 3D virtual tour based on the selected land and generated drawings. Through this tour, users can virtually view the property and form a concrete image of it.

[1666] Input: Optimal land information, regenerated drawing data

[1667] Output: 3D virtual tour

[1668] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1669] System Configuration

[1670] An embodiment of the present invention consists of a terminal in which the user inputs desired land conditions, a server that crawls a land database to acquire and filter land information that matches the conditions and select the optimal land, a server and terminal that automatically generate and modify drawings based on the land information and further recommend furniture, and an emotion engine that recognizes the user's emotions and responds accordingly.

[1671] System processing flow

[1672] 1. Enter conditions

[1673] Operator: User

[1674] Operation: The user enters their desired land conditions (price, area, location, surrounding environment, etc.) using a form displayed on the terminal and presses the submit button. The terminal then sends these conditions to the server.

[1675] 2. Acquisition of land information

[1676] Operating entity: Server

[1677] Operation: Based on the user's specified conditions, the server periodically crawls the land database and retrieves the latest land information that matches those conditions.

[1678] 3. Filtering land information

[1679] Operating entity: Server

[1680] Operation: The server filters land information acquired based on user criteria. This filtering selects land information that meets the specified criteria.

[1681] 4. Notification of land information

[1682] Operating entity: Server

[1683] Operation: The server selects the most suitable land from the filtered land information and notifies the user's terminal of that information. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[1684] 5. Automatic generation of recommended drawings

[1685] Operating entity: Server

[1686] Operation: Based on the notified land information, the server automatically generates basic drawings and elevation drawings using dedicated CAD software.

[1687] 6. Revision of drawings

[1688] Operator: User

[1689] Operation: The user reviews the generated drawing via the terminal and enters any necessary revision requests.

[1690] 7. Generation of revised drawings

[1691] Operating entity: Server

[1692] Operation: The server receives a modification request from the user and regenerates the drawing using CAD software. The regenerated drawing is based on the modification request.

[1693] 8. Furniture Recommendations

[1694] Operating entity: Server

[1695] Operation: Based on the completed drawings, the server crawls online furniture catalogs and retrieves furniture information suitable for those drawings. Furniture type, size, and design are all taken into consideration.

[1696] 9. Notification of furniture information

[1697] Operating entity: Server

[1698] Operation: The server sends a list of selected furniture and recommended placement suggestions to the user's device. The device then displays the furniture recommendation information.

[1699] Emotion Engine Processing Flow

[1700] 1. Recognition of emotions

[1701] Operating entity: Server

[1702] Operation: The emotion engine installed on the server analyzes the user's emotions from facial expressions, voice, text input, etc. The emotion engine identifies the user's emotions such as joy, surprise, disappointment, and anger.

[1703] 2. Emotion-based adjustment

[1704] Operating entity: Server

[1705] Operation: Based on the user's emotions recognized by the emotion engine, the system adjusts its output (notifications, drawings, furniture recommendations, etc.). For example, if the user is disappointed, the system will provide more detailed explanations or additional options.

[1706] Specific example

[1707] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[1708] 1. Enter the conditions:

[1709] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[1710] 2. Obtaining land information:

[1711] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[1712] 3. Filtering land information:

[1713] Based on the land information acquired by the server, the system recommends suitable land in Shinjuku Ward to the user.

[1714] 4. Notification of land information:

[1715] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[1716] 5. Automatic generation of recommended drawings:

[1717] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward.

[1718] 6. Revision of drawings:

[1719] The user enters a modification request stating, "I would like the living room to be a little larger."

[1720] 7. Generating revised drawings:

[1721] The server receives the correction request, regenerates the drawing, and resends it to the user.

[1722] 8. Furniture Recommendations:

[1723] The server recommends furniture such as sofas and tables suitable for a living room based on the floor plan, and sends the recommendations to the user's terminal.

[1724] If the emotion engine recognizes the emotion of "surprise" from the user's facial expressions or voice, the server will confirm that emotion with the user. If it is positive, it will take action such as suggesting multiple similar properties. Conversely, if a negative emotion is recognized, it can respond quickly and appropriately by suggesting further details or other options.

[1725] In this way, the system of the present invention can efficiently and consistently perform tasks ranging from land selection and drawing creation to revision, furniture recommendations, and even personalized responses based on emotion recognition, all based on the user's requirements.

[1726] The following describes the processing flow.

[1727] Step 1:

[1728] The user uses the input form displayed on the terminal to enter the desired land conditions (price, area, location, surrounding environment, etc.) and presses the submit button. The terminal then sends these conditions to the server.

[1729] Step 2:

[1730] The server crawls the real estate database based on the user's criteria received. The server periodically performs the crawling process to obtain the latest land information.

[1731] Step 3:

[1732] The server crawls and retrieves land information, which is then filtered based on the user's criteria. This filtering process selects land information that meets the specified conditions.

[1733] Step 4:

[1734] The server selects the most suitable land from the filtered land information. The selection criteria include user conditions as well as evaluation criteria pre-configured on the server.

[1735] Step 5:

[1736] The server notifies the user's terminal of the land information it has selected. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[1737] Step 6:

[1738] The user's device receives and displays a notification from the server. The user then reviews the presented land information.

[1739] Step 7:

[1740] Based on the recommended land information, the server automatically generates basic drawings and elevations using specialized CAD software.

[1741] Step 8:

[1742] The server automatically generates drawings and elevations and sends them to the user's terminal. The terminal then displays the received drawings.

[1743] Step 9:

[1744] The user reviews the provided drawings and enters any necessary revision requests. Examples of revision requests include changes to room size or layout. The user then submits the revision requests.

[1745] Step 10:

[1746] The server receives a modification request from the user and regenerates the drawing using CAD software. The regenerated drawing is based on the modification request.

[1747] Step 11:

[1748] The server sends the regenerated drawing back to the user's terminal. The terminal displays the corrected drawing.

[1749] Step 12:

[1750] Based on the completed drawings, the server crawls online furniture catalogs to retrieve furniture information suitable for those drawings. Factors such as furniture type, size, and design are taken into consideration.

[1751] Step 13:

[1752] The server sends a list of selected furniture and recommended placement suggestions to the user's device. The device then displays the furniture recommendations.

[1753] Step 14:

[1754] Users review the recommended furniture and make final adjustments to purchases and placement as needed.

[1755] Step 15:

[1756] The emotion engine installed on the server analyzes the user's emotions from facial expressions, voice, text input, etc. The emotion engine identifies the user's emotions such as joy, surprise, disappointment, and anger.

[1757] Step 16:

[1758] The server adjusts the system's output (notifications, drawings, furniture recommendations, etc.) based on the user's emotions recognized by the emotion engine. For example, if the user is disappointed, the system will provide more detailed explanations or additional options.

[1759] Specific example

[1760] Step 1:

[1761] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[1762] Step 2:

[1763] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[1764] Step 3:

[1765] The server filters the acquired land information based on the user's criteria and recommends land in Shinjuku Ward to the user.

[1766] Step 4:

[1767] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[1768] Step 5:

[1769] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward.

[1770] Step 6:

[1771] The server automatically generates drawings and elevations, which are then sent to the user and displayed on the user's device.

[1772] Step 7:

[1773] The user enters a modification request stating, "I would like the living room to be a little larger."

[1774] Step 8:

[1775] The server receives the correction request, regenerates the drawing, and resends it to the user.

[1776] Step 9:

[1777] The server recommends furniture such as sofas and tables suitable for the living room based on the floor plan, and sends the recommendations to the user's device.

[1778] Step 10:

[1779] The emotion engine recognizes the emotion of "surprise" from the user's facial expressions and voice.

[1780] Step 11:

[1781] The server checks the user's sentiment and, if the response is positive, suggests several similar properties. If the response is negative, it suggests further details or other options.

[1782] In this way, the system of the present invention can efficiently and consistently perform tasks ranging from land selection and drawing creation to revision, furniture recommendations, and even personalized responses based on emotion recognition, all based on the user's requirements.

[1783] (Example 2)

[1784] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1785] The traditional process of acquiring land, designing a residence, and selecting furniture requires considerable effort and time from the user, and there are challenges in providing sufficient support to enhance user satisfaction. In particular, there is a need for a system that efficiently and consistently handles the entire process, from quickly and accurately acquiring land information that matches the user's desired conditions, to automatically generating and modifying drawings based on that information, and recommending furniture. Furthermore, there is a lack of a system that can recognize the user's emotions and respond appropriately based on them.

[1786] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1787] In this invention, the server includes means for crawling a land database based on user-specified conditions and obtaining land information that meets those conditions; means for filtering the obtained land information and selecting the optimal land; means for automatically generating drawings based on the selected land information; and means including an emotion engine that analyzes the user's emotions and adjusts the system's output based on those emotions. This enables efficient execution of a series of processes from land selection based on user conditions to drawing creation, modification, and furniture recommendations, and also allows for flexible responses in accordance with the user's emotions.

[1788] A "user" is an entity that uses the system to input land conditions or request modifications to drawings.

[1789] A "land database" is a collection of data where various types of land information are stored. Information is retrieved through crawling.

[1790] "Crawling" is the act of using automated programs to periodically visit the internet and specific databases to collect information.

[1791] "Filtering" is the process of extracting only those data items that match specific criteria from a set of data.

[1792] "Optimal land" refers to land information that best matches the conditions entered by the user.

[1793] "Notification" refers to the act of sending land information or other information from a system to a user.

[1794] A "drawing" is a design plan for a house or building that is automatically generated based on land information.

[1795] A "revision request" is an instruction from the user to request changes to an automatically generated drawing.

[1796] "Regeneration" is the process of regenerating a drawing based on the user's modification request.

[1797] "Furniture recommendation" is the act of suggesting appropriate furniture types, sizes, and designs based on completed drawings.

[1798] An "emotion engine" is a program that analyzes the user's emotions from facial expressions, voice, text input, etc., and adjusts the system's output based on the results.

[1799] "Computer-aided design software" refers to specialized software used to create and edit design drawings using a computer.

[1800] System Configuration

[1801] The system of this invention consists of the following components.

[1802] 1. A terminal where the user enters their desired land conditions.

[1803] 2. A server that crawls the land database, retrieves and filters land information that matches the criteria, and selects the most suitable land.

[1804] 3. Server for automatically generating and modifying drawings based on land information.

[1805] 4. Terminal for recommending furniture based on drawings.

[1806] 5. An emotion engine that recognizes user emotions and responds accordingly.

[1807] Hardware and software to be used

[1808] Devices: Personal computers and smartphones

[1809] Server: A server computer with high-performance computing capabilities.

[1810] Land database: A database system for storing land information.

[1811] CAD software: Computer-aided design software

[1812] Emotion Engine: An AI program for analyzing user emotions.

[1813] Data processing and data calculation

[1814] Condition Input: The user uses a terminal to input the desired land conditions (price, area, location, surrounding environment, etc.). The entered information is sent to the server.

[1815] Land Information Acquisition and Filtering: The server crawls the land database based on the conditions received from the user. The acquired land information is filtered based on the conditions, and the most suitable land is selected.

[1816] Land Information Notification: Filtered information is sent to the user's device. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[1817] Automatic drawing generation: Based on the notified land information, the server automatically generates basic drawings and elevations using CAD software.

[1818] Drawing modification and regeneration: The user reviews the generated drawing via the terminal and enters any necessary modification requests. The server then regenerates the drawing based on these modification requests.

[1819] Furniture Recommendation: Based on the completed drawings, the server crawls online furniture catalogs to retrieve furniture information suitable for those drawings. Furniture type, size, and design are all taken into consideration.

[1820] Emotional Engine Processing

[1821] Emotion Recognition: The emotion engine analyzes emotions from the user's facial expressions, voice, text input, etc.

[1822] Emotion-based response: The emotion engine adjusts the system's output (notifications, drawings, furniture recommendations, etc.) based on the user's emotions.

[1823] Specific example

[1824] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[1825] 1. Enter the conditions:

[1826] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[1827] 2. Obtaining land information:

[1828] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[1829] 3. Filtering land information:

[1830] Based on the land information acquired by the server, the system recommends suitable land in Shinjuku Ward to the user.

[1831] 4. Notification of land information:

[1832] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[1833] 5. Automatic generation of recommended drawings:

[1834] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward.

[1835] 6. Revision of drawings:

[1836] The user enters a modification request stating, "I would like the living room to be a little larger."

[1837] 7. Generating revised drawings:

[1838] The server receives the correction request, regenerates the drawing, and resends it to the user.

[1839] 8. Furniture Recommendations:

[1840] The server recommends furniture such as sofas and tables suitable for a living room based on the floor plan, and sends the recommendations to the user's terminal.

[1841] Furthermore, if the emotion engine recognizes the emotion of "surprise" from the user's facial expressions or voice, the server will confirm this emotion with the user. If it is positive, it will take action such as suggesting multiple similar properties. Conversely, if a negative emotion is recognized, it can respond quickly and appropriately by suggesting further details or other options.

[1842] In this way, the system of the present invention can efficiently and consistently perform tasks ranging from land selection and drawing creation to revision, furniture recommendations, and even personalized responses based on emotion recognition, all based on the user's requirements.

[1843] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1844] Step 1: Enter the conditions

[1845] Operator: User

[1846] Input: The user enters their desired land conditions (price, area, location, surrounding environment, etc.) into the input form.

[1847] Specific actions:

[1848] 1. The user launches a land information search application on their personal computer or smartphone.

[1849] 2. The application's initial screen displays a form where you can enter conditions such as "budget," "area," "location," and "surrounding environment."

[1850] 3. The user enters the respective conditions and presses the submit button.

[1851] Output: The terminal sends the entered condition information to the server.

[1852] Step 2: Obtaining land information

[1853] Operating entity: Server

[1854] Input: Data of desired conditions submitted by the user.

[1855] Specific actions:

[1856] 1. The server generates a query (search request) based on the conditions received from the user.

[1857] 2. The server uses this query to crawl the land database and collect land information that matches the criteria.

[1858] 3. The information obtained from the database covers a wide range of topics, including the location, price, area, and surrounding environment of the land.

[1859] Output: Temporarily save the list of land parcels obtained as search results and proceed to the next step.

[1860] Step 3: Filtering land information

[1861] Operating entity: Server

[1862] Input: List of searched land information

[1863] Specific actions:

[1864] 1. The server begins filtering the stored land information based on the user's criteria.

[1865] 2. The filtering process involves checking for matches against conditions such as price, area, location, and surrounding environment.

[1866] 3. Extract matching land information and create an optimal land information list.

[1867] Output: Generates a filtered list of optimal land information and proceeds to the next step.

[1868] Step 4: Notification of land information

[1869] Operating entity: Server

[1870] Input: Filtered list of optimal land information

[1871] Specific actions:

[1872] 1. The server formats the optimal land information and generates a message to notify the user.

[1873] 2. The message will include detailed information such as the land's location, price, area, and surrounding environment.

[1874] 3. Send the generated message to the user's device.

[1875] Output: A notification of land information is displayed on the user's device.

[1876] Step 5: Automatic generation of recommended drawings

[1877] Operating entity: Server

[1878] Input: Notified land information

[1879] Specific actions:

[1880] 1. The server launches dedicated computer-aided design software based on the selected land information.

[1881] 2. Input the shape and area of ​​the land, as well as the necessary house floor plan data, and issue commands to automatically generate the basic house plans and elevations.

[1882] 3. The drawing is generated within the software, and the result is saved to the server.

[1883] Output: Automatically generated basic drawings and elevations.

[1884] Step 6: Modify the drawing

[1885] Operator: User

[1886] Input: Auto-generated drawing

[1887] Specific actions:

[1888] 1. The user checks the automatically generated drawing displayed on the terminal.

[1889] 2. Enter any requests for modifications to the drawing, such as "I'd like the living room to be a little wider" or "I'd like the entrance to be on the right side," into the input form.

[1890] 3. Enter the correction request and press the submit button.

[1891] Output: The terminal sends a correction request to the server.

[1892] Step 7: Generate revised drawings

[1893] Operating entity: Server

[1894] Input: Correction request submitted by the user

[1895] Specific actions:

[1896] 1. The server analyzes the correction request received from the user.

[1897] 2. Based on the analysis results, restart the computer-aided design software.

[1898] 3. Issue an order to regenerate the drawing in accordance with the revision request, and generate a new drawing.

[1899] 4. Save the regenerated drawing and resend it to the user.

[1900] Output: The modified drawing is sent to the user's terminal.

[1901] Step 8: Furniture Recommendations

[1902] Operating entity: Server

[1903] Input: Completed drawing

[1904] Specific actions:

[1905] 1. The server analyzes the completed drawings and determines the optimal type, size, and design of furniture for each room.

[1906] 2. The server crawls online furniture catalogs and searches for furniture information that matches the determined criteria.

[1907] 3. Generate a furniture list and send it to the user's device along with a recommended layout.

[1908] Output: Furniture recommendations and suggested layouts are displayed on the user's device.

[1909] Step 9: Recognizing Emotions

[1910] Operating entity: Server

[1911] Input: User facial expressions, voice, text input

[1912] Specific actions:

[1913] 1. The emotion engine installed on the server captures the user's facial expressions and voice obtained from the webcam and microphone.

[1914] 2. Include text input as part of the analysis.

[1915] 3. The emotion engine analyzes this information to identify the user's emotions (joy, surprise, disappointment, anger, etc.).

[1916] Output: User sentiment data is generated.

[1917] Step 10: Emotion-based responses

[1918] Operating entity: Server

[1919] Input: Emotional data generated by the emotion engine

[1920] Specific actions:

[1921] 1. The system's output is adjusted based on the emotion type recognized by the emotion engine.

[1922] 2. For example, if the user is disappointed, the server will provide a detailed explanation or additional options.

[1923] 3. If the user is pleased, provide positive feedback, such as suggesting multiple similar properties.

[1924] Output: The output of the adjusted system is notified to the user.

[1925] In this way, the system can consistently and efficiently perform tasks such as land selection based on user conditions, drawing creation and modification, furniture recommendations, and even emotional recognition-based responses.

[1926] (Application Example 2)

[1927] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1928] Traditional real estate selection systems have struggled to efficiently find properties that meet users' desired criteria. Furthermore, post-purchase design and furniture selection can be burdensome for users. Similarly, in shopping, gathering information on desired products and improving customer satisfaction during purchase remain challenges. In particular, there has been a lack of mechanisms to reflect users' emotions in real time and provide appropriate suggestions.

[1929] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1930] In this invention, the server includes means for inputting the land conditions desired by the user; means for crawling a real estate database based on the conditions and obtaining real estate information that matches the conditions; means for filtering the obtained real estate information and selecting the most suitable real estate; means for notifying the user of the selected real estate information; means for automatically generating drawings based on the real estate information; means for inputting requests for modifications to the drawings; means for regenerating the drawings based on the modification requests; means for recommending furniture based on the drawings; means for inputting product conditions desired by the user and obtaining product information that matches the conditions; means for notifying the user of recommended products based on the product information; and means for recognizing the user's emotions and adjusting the suggested content according to those emotions.

[1931] This makes it possible to provide users with an efficient and satisfying experience, from selecting and designing their desired property to recommending furniture and even shopping.

[1932] "A means for users to input their desired land conditions" refers to an interface for users to input their desired real estate conditions (price, area, location, surrounding environment, etc.) and transmit this information to the system.

[1933] "A means of crawling real estate databases and obtaining real estate information that meets the specified conditions" refers to a mechanism for automatically collecting real estate information that matches specified conditions from multiple real estate databases on the internet.

[1934] "Methods for filtering acquired real estate information and selecting the most suitable property" refers to algorithms or software that select the property that best matches the user's criteria from the collected real estate information.

[1935] "Means of notifying users of selected real estate information" refers to a system for displaying, alerting, or otherwise communicating identified real estate information to the user's terminal.

[1936] "Methods for automatically generating drawings based on real estate information" refers to a function that automatically creates design drawings and elevation drawings using specialized design software based on acquired real estate information.

[1937] "Means for inputting modification requests for drawings" refers to an interface for users to input and submit requests for changes or modifications to generated drawings.

[1938] "Means for regenerating drawings based on revision requests" refers to algorithms or software for regenerating and updating design drawings to reflect revision requests from users.

[1939] "A means of recommending furniture based on drawings" refers to a function that considers the layout of the generated design drawings and proposes the most suitable furniture and interior design to the user.

[1940] "A means of inputting desired product conditions and obtaining product information that meets those conditions" refers to an interface and algorithm for inputting desired product conditions (price, features, performance, etc.) and collecting product information that matches those conditions.

[1941] "A means of notifying users of recommended products based on product information" refers to a system that selects the most suitable product for the user based on collected product information and notifies them of it.

[1942] "Means for recognizing user emotions and adjusting suggestions accordingly" refers to an emotion recognition engine and algorithm that analyzes the user's emotional state from their facial expressions and voice, and dynamically changes and adjusts the suggested content based on the results.

[1943] System Configuration

[1944] The system for implementing this invention consists of a terminal for the user to input desired conditions, a server that crawls a real estate database to acquire and filter information that matches the conditions and select the most suitable property, a server and terminal that automatically generate and modify drawings based on the property information and further recommend furniture, and an emotion engine that recognizes the user's emotions and responds accordingly.

[1945] Hardware and software used

[1946] Smartphone: Use an iPhone or Android smartphone as the user's input device.

[1947] Servers: For cloud services, we will use Amazon Web Services (AWS) or Google Cloud Platform.

[1948] Emotion Engine: Emotion recognition uses either the Microsoft Azure Emotion API or the Google Cloud Vision API.

[1949] Artificial intelligence: Generative AI models such as OpenAI's GPT-4 are used.

[1950] Database: MongoDB or Firebase are used for data management.

[1951] Design software: Automatic drawing generation is performed using design software such as AutoCAD API.

[1952] System processing

[1953] At each processing stage of the system, data processing and calculations are performed as follows:

[1954] 1. Enter conditions

[1955] Users use a form in a smartphone app to enter their desired real estate conditions (price, area, location, surrounding environment, etc.) and product conditions (price, features, performance, etc.), and then submit them to the server.

[1956] 2. Acquisition and filtering of real estate information

[1957] The server crawls the specified real estate database and retrieves property information that matches the user's criteria. Then, it uses a filtering algorithm (written in Python) to select the most suitable property.

[1958] 3. Notification of real estate information

[1959] Filtered real estate information is sent to the user's smartphone. Detailed information (price, location, surrounding environment, etc.) is displayed.

[1960] 4. Automatic generation and modification of drawings

[1961] The server automatically generates design drawings and elevations using design software (AutoCAD API) based on the acquired real estate information. If a user requests revisions to the drawings, the server incorporates those changes and regenerates the drawings.

[1962] 5. Furniture Recommendations

[1963] Based on the automatically generated drawings, the server crawls online furniture catalogs and retrieves furniture information suitable for the drawings. It then provides recommendations considering furniture type, size, design, and other factors.

[1964] 6. Acquisition and notification of product information

[1965] Based on product criteria, the system crawls multiple product databases on the internet (such as the Google Shopping API and Amazon Product Advertising API) to retrieve suitable product information. The retrieved product information is then notified to the user, and detailed information is displayed.

[1966] 7. Emotion Recognition and Response Adjustment

[1967] The system uses the smartphone's built-in camera and microphone to collect the user's facial expressions and voice. An emotion engine (such as the Azure Emotion API) analyzes this data and adjusts the system's output according to the emotion. For positive emotions, it suggests additional related products; for negative emotions, it provides detailed explanations or other options.

[1968] Specific example

[1969] For example, if a user enters their desired real estate conditions as "budget of 30 million yen, area of ​​100 square meters or more, location: Tokyo, condition: good transportation access," the server crawls the land database and finds properties that match the conditions. Based on that information, it generates a blueprint and incorporates the user's modification requests. Finally, it recommends furniture that suits the generated blueprint. If the emotion engine recognizes the user's emotion of "surprise," the system will suggest additional similar properties.

[1970] Example of a prompt

[1971] Requirements: A smartwatch with a price under 30 million yen, in red, and featuring waterproof functionality. Please recommend related products and generate layout proposals.

[1972] This allows users to easily obtain real estate and product information that best suits their desired conditions, and furthermore, receive highly satisfying suggestions through emotion recognition.

[1973] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1974] Step 1:

[1975] Condition Input

[1976] Users use a smartphone app to input their desired real estate conditions (price, area, location, surrounding environment, etc.) and product conditions (price, features, performance, etc.). The entered conditions are sent to the server via the smartphone app.

[1977] Input: User's desired conditions (e.g., price 30 million yen, area 100 square meters or more, location: Tokyo, condition: convenient transportation)

[1978] Output: Conditional data sent to the server

[1979] Step 2:

[1980] Acquisition of real estate information

[1981] The server crawls the specified real estate database and retrieves property information that matches the user's criteria. During this process, periodic queries are executed. A crawl script, often using Python, is run to collect the latest property information that meets the specified criteria.

[1982] Input: Conditional data sent by the user to the server

[1983] Output: Dataset of real estate information that matches the criteria

[1984] Step 3:

[1985] Filtering real estate information

[1986] The server executes a filtering algorithm based on the acquired real estate information to select the most suitable property. Filtering is performed based on pre-configured user criteria.

[1987] Input: Dataset of acquired real estate information, user conditions

[1988] Output: Filtered and optimized real estate information

[1989] Step 4:

[1990] Real estate information notification

[1991] The server notifies the user's smartphone of filtered real estate information. The notification includes detailed information about the property (price, location, surrounding environment, etc.). The user's smartphone app receives and displays this information.

[1992] Input: Filtered property information

[1993] Output: Property details displayed on the user's smartphone

[1994] Step 5:

[1995] Automatic generation of drawings

[1996] The server automatically generates design drawings and elevations using design software (AutoCAD API) based on the acquired real estate information. A dedicated script is executed, and detailed drawings are created based on the input data.

[1997] Input: Filtered property information

[1998] Output: Automatically generated design drawings and elevations

[1999] Step 6:

[2000] Request for revision of drawings

[2001] The user enters revision requests based on automatically generated drawings. They specify in detail the areas requiring modification and the elements they wish to add via a smartphone app. The revision requests are then sent to the server.

[2002] Input: User correction request

[2003] Output: Correction request data sent to the server

[2004] Step 7:

[2005] Generation of revised drawings

[2006] The server receives the modification request from the user and generates the modified drawing again using the design software (AutoCAD API). Based on the user's specifications, a new drawing is created that reflects the necessary changes.

[2007] Input: Modification request data, initial design drawings

[2008] Output: Revised blueprints

[2009] Step 8:

[2010] Furniture recommendations

[2011] Based on the final design plans, the server crawls online furniture catalogs and recommends furniture that fits those plans. Considering factors such as furniture type, size, and design, a list of suitable furniture is generated for the user.

[2012] Input: Modified blueprint

[2013] Output: Furniture recommendation information

[2014] Step 9:

[2015] Product information acquisition and notification

[2016] The server crawls multiple product databases on the internet based on the user's desired product criteria and retrieves suitable product information. The retrieved product information is then displayed as a notification on the user's smartphone.

[2017] Input: User's desired product specifications

[2018] Output: Product information displayed on the user's smartphone

[2019] Step 10:

[2020] Emotion recognition and response adjustment

[2021] The smartphone's built-in camera and microphone are used to collect the user's facial expressions and voice. An emotion engine (such as the Azure Emotion API) analyzes this data to identify the user's emotions. If the emotion is positive, additional suggestions are provided; if it is negative, more detailed explanations and other options are offered.

[2022] Input: User's facial expressions and voice data

[2023] Output: Adjusted proposal or additional options

[2024] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2025] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2026] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[2027] [Fourth Embodiment]

[2028] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[2029] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[2030] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[2031] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[2032] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[2033] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[2034] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[2035] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[2036] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[2037] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[2038] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[2039] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[2040] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2041] System Configuration

[2042] An embodiment of the present invention consists of a terminal in which the user inputs the desired land conditions, a server that crawls a land database, acquires and filters land information that matches the conditions, and selects the most suitable land, and a server and terminal that automatically generate and modify drawings based on the land information and further recommend furniture.

[2043] System processing flow

[2044] 1. Enter conditions

[2045] Operator: User

[2046] Operation: The user enters the desired land conditions (price, area, location, surrounding environment, etc.) using a form displayed on the terminal, and then presses the submit button to send that information to the server.

[2047] 2. Acquisition of land information

[2048] Operating entity: Server

[2049] Operation: Based on the user's specified conditions, the server periodically crawls the land database and retrieves the latest land information that matches those conditions.

[2050] 3. Filtering land information

[2051] Operating entity: Server

[2052] Operation: The server filters land information acquired based on user criteria and selects suitable land information.

[2053] 4. Notification of land information

[2054] Operating entity: Server

[2055] Operation: The server notifies the user's terminal of information about the selected suitable land. This notification includes detailed information about the land (location, price, area, etc.).

[2056] 5. Automatic generation of recommended drawings

[2057] Operating entity: Server

[2058] Operation: Based on the notified land information, the server automatically generates basic drawings and elevations using dedicated CAD software.

[2059] 6. Revision of drawings

[2060] Operator: User

[2061] Operation: The user reviews the generated drawing via the terminal and enters any necessary revision requests.

[2062] 7. Generation of revised drawings

[2063] Operating entity: Server

[2064] Operation: The server receives a correction request from the user and regenerates the drawing based on the correction. The regenerated drawing is then sent back to the user's terminal.

[2065] 8. Furniture Recommendations

[2066] Operating entity: Server

[2067] Operation: Based on the completed drawings, the server recommends the most suitable furniture and its placement from an online furniture catalog. The recommendation information is sent to the user's device.

[2068] Specific example

[2069] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[2070] 1. Enter the conditions:

[2071] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[2072] 2. Obtaining land information:

[2073] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[2074] 3. Filtering land information:

[2075] Based on the land information acquired by the server, the system recommends suitable land in Shinjuku Ward to the user.

[2076] 4. Notification of land information:

[2077] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[2078] 5. Automatic generation of recommended drawings:

[2079] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward and sends them to the user.

[2080] 6. Revision of drawings:

[2081] The user enters a modification request stating, "I would like the living room to be a little larger."

[2082] 7. Generating revised drawings:

[2083] The server receives the correction request, regenerates the drawing, and resends it to the user.

[2084] 8. Furniture Recommendations:

[2085] The server recommends furniture such as sofas and tables suitable for a living room based on the floor plan, and sends the recommendations to the user's terminal.

[2086] In this way, the system of the present invention can efficiently perform a consistent process from land selection to drawing creation, modification, and furniture recommendation, based on the user's requirements.

[2087] The following describes the processing flow.

[2088] Step 1:

[2089] The user uses the input form displayed on the terminal to enter the desired land conditions (price, area, location, surrounding environment, etc.) and presses the submit button. The terminal then sends these conditions to the server.

[2090] Step 2:

[2091] The server crawls the real estate database based on the user's criteria received. The crawling process is performed periodically to retrieve the latest land information.

[2092] Step 3:

[2093] The server crawls and retrieves land information, which is then filtered based on the user's criteria. This filtering process selects land information that meets the specified conditions.

[2094] Step 4:

[2095] The server selects the most suitable land from the filtered land information. The selection criteria include user conditions as well as evaluation criteria pre-configured on the server.

[2096] Step 5:

[2097] The server notifies the user's terminal of the land information it has selected. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[2098] Step 6:

[2099] The user's device receives and displays a notification from the server. The user then reviews the presented land information.

[2100] Step 7:

[2101] Based on the recommended land information, the server automatically generates basic drawings and elevations using specialized CAD software.

[2102] Step 8:

[2103] The server automatically generates drawings and elevations and sends them to the user's terminal. The terminal then displays the received drawings.

[2104] Step 9:

[2105] The user reviews the provided drawings and enters any necessary revision requests. Examples of revision requests include changes to room size or layout. The user then submits the revision requests.

[2106] Step 10:

[2107] The server receives a modification request from the user and regenerates the drawing using CAD software. The regenerated drawing is based on the modification request.

[2108] Step 11:

[2109] The server sends the regenerated drawing back to the user's terminal. The terminal displays the corrected drawing.

[2110] Step 12:

[2111] Based on the completed drawings, the server crawls online furniture catalogs to retrieve furniture information suitable for those drawings. Factors such as furniture type, size, and design are taken into consideration.

[2112] Step 13:

[2113] The server sends a list of selected furniture and recommended placement suggestions to the user's device. The device then displays the furniture recommendations.

[2114] Step 14:

[2115] Users review the recommended furniture and make final adjustments to purchases and placement as needed.

[2116] (Example 1)

[2117] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2118] When purchasing a modern home, many users spend considerable time and effort finding suitable land, creating optimal blueprints, and then selecting furniture. Traditional methods fragment the process, requiring users to interact with multiple platforms and vendors at each stage, as these tasks—land information gathering and filtering, blueprint creation and revision, and furniture selection—are disconnected. This process is inefficient and often leads to lower overall satisfaction. Furthermore, challenges include the inability to obtain suitable land information in a timely manner and the cumbersome process of revising blueprints.

[2119] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[2120] In this invention, the server includes means for the user to input desired land conditions, means for crawling a land database based on the conditions and obtaining land information that matches the conditions, and means for filtering the obtained land information and selecting the optimal land. This allows the user to efficiently obtain desired land information and receive automatically generated blueprints and recommendations for optimal furniture based on that information. This enables the entire process from land selection to blueprint creation and furniture selection to be carried out efficiently in one go, thereby improving user satisfaction.

[2121] A "user" is an entity that uses this system to input desired land conditions and receives selected land information, blueprints, and furniture recommendations.

[2122] "Means for inputting conditions" refers to a device or system that provides an interface for users to input detailed conditions of land they desire (such as price, area, location, and surrounding environment).

[2123] A "land database" is a source of information that stores information on multiple plots of land and is used to retrieve land information that meets specific criteria through crawling.

[2124] "Crawling" refers to a software technology that involves a program or a series of operations for automatically collecting information from land databases on the internet.

[2125] "Filtering methods" refer to software algorithms used to select information that matches the user's input criteria from the acquired land information.

[2126] "Land information" refers to information about a specific piece of land, including details such as location, price, and area.

[2127] "Notification means" refers to communication methods for sending filtered land information to the user's device. This includes methods such as email and push notifications.

[2128] A "design drawing" is a diagram that shows the basic layout and structure of a building to be constructed on a desired plot of land.

[2129] "Means of automatic generation" refers to an algorithm or program that automatically creates building blueprints using specific software (e.g., CAD software) based on input land information.

[2130] A "means for inputting modification requests" refers to a system that provides an interface for users to review generated blueprints and input necessary changes or modifications.

[2131] A "means of regeneration" refers to a software algorithm for recreating the design blueprint to reflect the modification requests.

[2132] "A means of recommending furniture" refers to software that suggests appropriate furniture and its placement based on a completed blueprint.

[2133] The "reporting database" is a database used to temporarily store suitable land information after filtering.

[2134] "Means for generating furniture arrangement plans" refers to algorithms or software for creating the optimal furniture arrangement based on a completed design drawing.

[2135] An embodiment of the present invention consists of a terminal in which the user inputs desired land conditions, a server that crawls a land database to acquire and filter land information that matches the conditions and select the most suitable land, and a server and terminal that automatically generate and modify building blueprints based on the land information and further recommend furniture.

[2136] Hardware and software to be used

[2137] Terminal: A client device used by the user to operate the system (PC, tablet, smartphone, etc.)

[2138] Server: A central server that processes user input and performs tasks such as data retrieval, filtering, notifications, diagram generation, and recommendations.

[2139] Software and libraries to be used:

[2140] Web browser: Provides an interface for users to enter conditions.

[2141] Python: A programming language used for data crawling.

[2142] Beautiful Soup, Selenium: Libraries for crawling land databases

[2143] SQL (MySQL, PostgreSQL, etc.): Database management system

[2144] AutoCAD API: CAD software for automatically generating building blueprints.

[2145] Email sending API, push notification API: Communication methods for notifying users of land information and map URLs.

[2146] IKEA API, Amazon API: Online catalogs for recommending furniture

[2147] Explanation of the processing flow

[2148] 1. Enter conditions

[2149] Operator: User

[2150] Specific operation: The user opens a web page on their device, enters details of the desired land (price, area, location, surrounding environment, etc.) into a form, and clicks the submit button to send it to the server.

[2151] 2. Acquisition of land information

[2152] Operating entity: Server

[2153] Specific operation: The server uses Python to crawl a specified land database using Beautiful Soup or Selenium, retrieves land information that meets the criteria, and stores it in a temporary storage database.

[2154] 3. Filtering land information

[2155] Operating entity: Server

[2156] Specific operation: The server reads data retrieved from a temporary storage database and filters it based on user criteria. The filtered data is then saved to the reporting database as matching land information.

[2157] 4. Notification of land information

[2158] Operating entity: Server

[2159] Specific operation: The server uses email sending APIs and push notification APIs to notify users of filtered land information.

[2160] 5. Automatic generation of recommended drawings

[2161] Operating entity: Server

[2162] Specific operation: The server uses the AutoCAD API to automatically generate basic house drawings and elevations based on the provided land information. The generated drawings are saved on the server, and the URL is notified to the user.

[2163] 6. Revision of drawings

[2164] Operator: User

[2165] Specific operation: The user opens the notified URL and enters a request to review and modify the drawing. The modification request is sent to the server.

[2166] 7. Generation of revised drawings

[2167] Operating entity: Server

[2168] Specific operation: The server receives the correction request, regenerates the drawing using the AutoCAD API, and notifies the user again.

[2169] 8. Furniture Recommendations

[2170] Operating entity: Server

[2171] Specific operation: Based on the completed drawing, the server retrieves information on suitable furniture from the IKEA API and Amazon API, and notifies the user of the recommended furniture.

[2172] Specific example

[2173] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[2174] 1. Enter the conditions:

[2175] The user enters the following conditions on their device: "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Convenient transportation," and sends it to the server.

[2176] 2. Obtaining land information:

[2177] The server uses Python's Beautiful Soup to crawl the land database and finds a 120 square meter plot of land in Shinjuku Ward.

[2178] 3. Filtering land information:

[2179] The server filters the acquired land information, selects land information that meets the specified criteria, and saves it to the reporting database.

[2180] 4. Notification of land information:

[2181] The server uses an email API to notify users of selected land information (e.g., 120 square meters in Shinjuku Ward, priced at 30 million yen).

[2182] 5. Automatic generation of recommended drawings:

[2183] The server uses the AutoCAD API to automatically generate design drawings and elevation drawings based on the acquired land information, and notifies the user of the URL.

[2184] 6. Revision of drawings:

[2185] The user opens the URL they were notified with, enters a modification request such as "I want the living room to be a little bigger," and sends it to the server.

[2186] 7. Generating revised drawings:

[2187] The server receives the correction request, uses the AutoCAD API again to generate the corrected drawing, and notifies the user again.

[2188] 8. Furniture Recommendations:

[2189] The server uses the Amazon API to recommend furniture suitable for the generated drawings to the user.

[2190] Examples of prompts for generative AI models

[2191] The following are examples of prompt statements to input into the generative AI model.

[2192] "For users searching for land in Tokyo with a budget of 30 million yen, over 100 square meters, and convenient transportation access, please acquire, filter, and recommend appropriate land information. Furthermore, generate basic house plans based on the land, update the plans according to user requests, and finally, recommend furniture."

[2193] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2194] Step 1:

[2195] Condition Input

[2196] Operator: User

[2197] Specific actions:

[2198] The user starts up their device and opens the system's webpage in their browser. They enter their desired land conditions (price, area, location, surrounding environment, etc.) into the form. They click the "Submit" button to send the conditions to the server.

[2199] input:

[2200] Desired land conditions (price, area, location, surrounding environment, etc.)

[2201] output:

[2202] The entered conditions are sent to the server.

[2203] Step 2:

[2204] Acquisition of land information

[2205] Operating entity: Server

[2206] Specific actions:

[2207] The server receives the conditions sent by the user. Using Python libraries (such as Beautiful Soup or Selenium), it crawls the specified land database and retrieves the latest land information that matches the conditions. The retrieved land information is stored in a temporary storage database.

[2208] input:

[2209] Land conditions entered by the user

[2210] output:

[2211] Land information stored in a temporary storage database

[2212] Step 3:

[2213] Land information filtering

[2214] Operating entity: Server

[2215] Specific actions:

[2216] The server reads data retrieved from a temporary storage database and filters it using SQL queries based on user criteria. Based on the filtering results, it selects suitable land information and saves it to the reporting database.

[2217] input:

[2218] Land information stored in a temporary storage database

[2219] output:

[2220] Save filtered land information to the reporting database.

[2221] Step 4:

[2222] Land information notification

[2223] Operating entity: Server

[2224] Specific actions:

[2225] The server prepares to send notifications to users based on the filtered land information. It uses email sending APIs and push notification APIs to send the filtered land information to the user's device.

[2226] input:

[2227] Filtered land information stored in the reporting database

[2228] output:

[2229] Notifications to the user's device

[2230] Step 5:

[2231] Automatic generation of recommended drawings

[2232] Operating entity: Server

[2233] Specific actions:

[2234] Based on the provided land information, the server automatically generates basic house plans and elevations using the AutoCAD API. The generated plans are saved as image files on the server, and a URL for the plans is generated. This URL is then notified to the user.

[2235] input:

[2236] Land information stored in the reporting database

[2237] output:

[2238] Notification containing the URL of the generated drawing

[2239] Step 6:

[2240] Drawing revisions

[2241] Operator: User

[2242] Specific actions:

[2243] The user opens the URL of the drawing notified from the server using their device. They review the drawing and enter revision requests using the form or comment function. Revision requests are sent from the device to the server in real time.

[2244] input:

[2245] User correction request

[2246] output:

[2247] Correction request sent to the server

[2248] Step 7:

[2249] Generation of revised drawings

[2250] Operating entity: Server

[2251] Specific actions:

[2252] The server receives the user's modification request and uses the AutoCAD API, etc., again to regenerate the drawing that reflects the modifications. The URL of the regenerated drawing is then sent to the user's device again.

[2253] input:

[2254] User correction request

[2255] output:

[2256] Notification including the URL of the revised drawing

[2257] Step 8:

[2258] Furniture recommendations

[2259] Operating entity: Server

[2260] Specific actions:

[2261] The server crawls online furniture catalogs (such as the IKEA API and Amazon API) based on the completed drawings. It selects furniture suitable for the drawings and generates optimal furniture and layout plans. This recommendation information is then notified to the user's device.

[2262] input:

[2263] Completed drawings

[2264] output:

[2265] Furniture recommendation information sent to the user's device.

[2266] (Application Example 1)

[2267] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2268] Conventional land selection and drawing creation systems made it difficult for users to visually understand the area's layout during the process from inputting desired land conditions to modifying automatically generated drawings. Furthermore, the detailed information provided after land selection, including furniture placement suggestions, was limited, resulting in a poor user experience. To address this issue, there is a need for a more visual and interactive land selection and drawing generation system.

[2269] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[2270] In this invention, the server includes means for inputting the land conditions desired by the user, means for crawling a real estate database based on the conditions and obtaining land information that meets the conditions, means for filtering the obtained land information and selecting the optimal land, means for notifying the user of the selected land information, means for automatically generating a drawing based on the land information, means for inputting a request for modification to the drawing, means for regenerating the drawing based on the modification request, means for recommending furniture based on the drawing, and means for providing real estate information as a 3D virtual tour based on the conditions input by the user and the selected land. This enables the user to select land and customize the drawing in a visual and interactive manner, and to receive more detailed information and suggestions for appropriate furniture placement.

[2271] "A means for users to input their desired land conditions" refers to an interface or form that allows users to input their desired conditions regarding land, such as specific price, area, location, and surrounding environment.

[2272] "Methods for crawling real estate databases and obtaining land information that meets the criteria" refers to programs or algorithms that automatically collect land information from the internet or specific databases based on conditions entered by the user.

[2273] "Methods for filtering acquired land information and selecting the most suitable land" refers to the process or algorithm used to narrow down collected land information according to the user's desired conditions and select the land that best meets those conditions.

[2274] "Means of notifying users of selected land information" refers to a system that notifies users of detailed information about selected land via email, in-app messages, or other means.

[2275] "Methods for automatically generating drawings based on land information" refers to the process of automatically creating drawings using specialized design software based on selected land.

[2276] "Means for inputting modification requests for drawings" refers to interfaces or forms that allow users to input changes or modifications to generated drawings.

[2277] "Means for regenerating drawings based on revision requests" refers to programs or algorithms that automatically regenerate drawings, reflecting revision requests entered by the user.

[2278] "Methods for recommending furniture based on drawings" refers to processes and algorithms that automatically suggest the optimal furniture and its placement based on completed drawings.

[2279] "A means of providing real estate information as a 3D virtual tour" refers to a system that allows users to visually tour a property using virtual reality or 3D simulation technology, based on selected land plots and generated blueprints.

[2280] This invention is a system that allows users to input their desired land conditions, crawls a land database based on those conditions, retrieves and filters land information that matches the conditions, and selects the most suitable land. Furthermore, it can automatically generate drawings based on the selected land information, regenerate them according to the user's modification requests, and recommend furniture based on the completed drawings. It also includes a function to provide users with real estate information as a 3D virtual tour.

[2281] The server receives the user's input criteria and crawls information from the internet or specific real estate databases. The crawl results are filtered, and land information that matches the criteria is collected. This allows the server to provide users with accurate and timely detailed information about the land they desire.

[2282] The server automatically generates architectural drawings based on land information. This process utilizes specialized computer-aided design (CAD) software to plan based on the shape and area of ​​the selected land. The CAD software streamlines the drawing generation process and provides highly accurate drawings.

[2283] The user can review the generated drawing and enter any necessary revision requests. The server receives this revision information and regenerates the drawing. In this way, customization according to the user's preferences becomes possible.

[2284] Based on the completed drawings, the server recommends the most suitable furniture. Furniture recommendations are performed using online catalogs and databases, allowing the user to be provided with appropriate furniture options.

[2285] Furthermore, the server provides a 3D virtual tour function, allowing users to virtually tour properties based on selected land information and generated drawings. Visualizing real estate information in 3D makes it easier for users to imagine the actual space, enabling more concrete consideration.

[2286] For example, if a user is looking for "a plot of land in Tokyo with a budget of 30 million yen or less and an area of ​​100 square meters or more," the following process takes place: The user enters their criteria through a smartphone application and sends them to the server. The server crawls and filters land information based on the specified criteria, selects the most suitable plot, and notifies the user. Next, the server automatically generates a 3D drawing based on the selected land information and provides it to the user. The user enters revision requests while viewing the drawing and reviews the regenerated drawing. Finally, the server provides a 3D virtual tour, including furniture placement suggestions, allowing the user to visualize the land and building plan more concretely.

[2287] Example of a prompt:

[2288] "I'm looking for a plot of land in Tokyo that's over 100 square meters and within a budget of 30 million yen. I'd like you to search for the most suitable plot, generate a virtual floor plan, and even suggest furniture placement options."

[2289] Thus, the present invention provides a system that offers total support, from selecting land that meets the user's requirements to creating drawings, conducting virtual tours, and recommending furniture.

[2290] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2291] Step 1:

[2292] The user enters the desired land conditions.

[2293] Users use a smartphone application to enter their desired land conditions (e.g., budget, area, location, surrounding environment, etc.) into an input form and send it to the server.

[2294] Input: Land conditions (price, area, location, surrounding environment, etc.)

[2295] Output: Input conditional data

[2296] Step 2:

[2297] The server crawls the land database and retrieves land information that meets the criteria.

[2298] The server crawls the internet or specific real estate databases based on the conditions entered by the user, and retrieves land information that matches those conditions. For example, it can filter by price, area, and location.

[2299] Input: Conditional data

[2300] Output: Acquired land information (candidate list)

[2301] Step 3:

[2302] The acquired land information is filtered to select the most suitable land.

[2303] The server filters the land information retrieved through crawling based on user criteria and selects the most suitable land information. This filtering process includes comparing price, area, and location.

[2304] Input: Acquired land information (candidate list)

[2305] Output: Optimal land information (selected items)

[2306] Step 4:

[2307] The selected land information will be notified to the user.

[2308] The server notifies the user's terminal of the selected, optimal land information. The notified information includes detailed information about the land (location, price, area, etc.).

[2309] Input: Optimal land information (selected items)

[2310] Output: Notification message sent to the user's terminal

[2311] Step 5:

[2312] Automatically generate drawings based on land information.

[2313] The server automatically generates basic design drawings and elevations using specialized CAD software based on the selected land information. This process automatically takes into account the shape and area of ​​the land.

[2314] Input: Optimal land information (selected items)

[2315] Output: Automatically generated drawing data (basic design drawings and elevation drawings)

[2316] Step 6:

[2317] Enter a request for revisions to the drawing.

[2318] The user reviews the generated drawings and enters any necessary modification requests. For example, they might enter specific requests such as "I want to make the living room larger" or "I want to change the location of the kitchen."

[2319] Input: Automated drawing data

[2320] Output: User correction request

[2321] Step 7:

[2322] Regenerate the drawing based on the revision request.

[2323] The server regenerates the drawing based on the modification request received from the user. It generates a new design drawing that reflects the modification request and provides it to the user.

[2324] Input: User correction request

[2325] Output: Regenerated drawing data (corrected design drawings)

[2326] Step 8:

[2327] Recommend furniture based on the drawings.

[2328] The server recommends the most suitable furniture and its placement from an online furniture catalog based on the completed drawings. The recommendation information is sent to the user's terminal, providing specific furniture options and placement suggestions.

[2329] Input: Regenerated drawing data

[2330] Output: Furniture recommendation information

[2331] Step 9:

[2332] Providing real estate information as a 3D virtual tour.

[2333] The server provides users with a 3D virtual tour based on the selected land and generated drawings. Through this tour, users can virtually view the property and form a concrete image of it.

[2334] Input: Optimal land information, regenerated drawing data

[2335] Output: 3D virtual tour

[2336] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[2337] System Configuration

[2338] An embodiment of the present invention consists of a terminal in which the user inputs desired land conditions, a server that crawls a land database to acquire and filter land information that matches the conditions and select the optimal land, a server and terminal that automatically generate and modify drawings based on the land information and further recommend furniture, and an emotion engine that recognizes the user's emotions and responds accordingly.

[2339] System processing flow

[2340] 1. Enter conditions

[2341] Operator: User

[2342] Operation: The user enters their desired land conditions (price, area, location, surrounding environment, etc.) using a form displayed on the terminal and presses the submit button. The terminal then sends these conditions to the server.

[2343] 2. Acquisition of land information

[2344] Operating entity: Server

[2345] Operation: Based on the user's specified conditions, the server periodically crawls the land database and retrieves the latest land information that matches those conditions.

[2346] 3. Filtering land information

[2347] Operating entity: Server

[2348] Operation: The server filters land information acquired based on user criteria. This filtering selects land information that meets the specified criteria.

[2349] 4. Notification of land information

[2350] Operating entity: Server

[2351] Operation: The server selects the most suitable land from the filtered land information and notifies the user's terminal of that information. The notification includes detailed information about the land (location, price, area, surrounding environment, etc.).

[2352] 5. Automatic generation of recommended drawings

[2353] Operating entity: Server

[2354] Operation: Based on the notified land information, the server automatically generates basic drawings and elevation drawings using dedicated CAD software.

[2355] 6. Revision of drawings

[2356] Operator: User

[2357] Operation: The user reviews the generated drawing via the terminal and enters any necessary revision requests.

[2358] 7. Generation of revised drawings

[2359] Operating entity: Server

[2360] Operation: The server receives a modification request from the user and regenerates the drawing using CAD software. The regenerated drawing is based on the modification request.

[2361] 8. Furniture Recommendations

[2362] Operating entity: Server

[2363] Operation: Based on the completed drawings, the server crawls online furniture catalogs and retrieves furniture information suitable for those drawings. Furniture type, size, and design are all taken into consideration.

[2364] 9. Notification of furniture information

[2365] Operating entity: Server

[2366] Operation: The server sends a list of selected furniture and recommended placement suggestions to the user's device. The device then displays the furniture recommendation information.

[2367] Emotion Engine Processing Flow

[2368] 1. Recognition of emotions

[2369] Operating entity: Server

[2370] Operation: The emotion engine installed on the server analyzes the user's emotions from facial expressions, voice, text input, etc. The emotion engine identifies the user's emotions such as joy, surprise, disappointment, and anger.

[2371] 2. Emotion-based adjustment

[2372] Operating entity: Server

[2373] Operation: Based on the user's emotions recognized by the emotion engine, the system adjusts its output (notifications, drawings, furniture recommendations, etc.). For example, if the user is disappointed, the system will provide more detailed explanations or additional options.

[2374] Specific example

[2375] For example, if a user is looking for land in Tokyo with a budget of 30 million yen, an area of ​​100 square meters or more, and convenient transportation access, the following process will be performed.

[2376] 1. Enter the conditions:

[2377] The user enters "Budget: 30 million yen, Area: 100 square meters or more, Location: Tokyo, Condition: Good transportation access" into their device and sends it to the server.

[2378] 2. Obtaining land information:

[2379] The server crawls the land database and finds, for example, a 120 square meter plot of land in Shinjuku Ward.

[2380] 3. Filtering land information:

[2381] Based on the land information acquired by the server, the system recommends suitable land in Shinjuku Ward to the user.

[2382] 4. Notification of land information:

[2383] The server notifies the user's terminal of "land information in Shinjuku Ward, area 120 square meters, price 30 million yen."

[2384] 5. Automatic generation of recommended drawings:

[2385] The server automatically generates basic house plans and elevations based on land information in Shinjuku Ward.

[2386] 6. Revision of drawings:

[2387] The user enters a modification request stating, "I would like the living room to be a little larger."

[2388] 7. Generating revised drawings:

[2389] The server receives the correction request, regenerates the drawing, and resends it to the user.

[2390] 8. Furniture Recommendations:

[2391] The server recommends furniture such as sofas and tables suitable for a living room based on the floor plan, and sends the recommendations to the user's terminal.

[2392] If the emotion engine recognizes the emotion of "surprise" from the user's facial expressions or voice, the server will confirm that emotion with the user. If it is positive, it will take action such as suggesting multiple similar properties. Conversely, if a negative emotion is recognized, it can respond quickly and appropriately by suggesting further details or other options.

[2393] In this way, the system of the present invention can efficiently and consistently perform tasks ranging from land selection and drawing creation to revision, furniture recommendations, and even personalized responses based on emotion recognition, all based on the user's requirements.

[2394] The following describes the processing flow.

[2395] Step 1:

[2396] The user uses the input form displayed on the terminal to enter the desired land conditions (price, area, location, surrounding environment, etc.) and presses the submit button. The terminal then sends these conditions to the server.

[2397] Step 2:

[2398] The server crawls the real estate database based on the user's criteria received. The server periodically performs the crawling process to obtain the latest land information.

[2399] Step 3:

[2400] The server crawls and retrieves land information, which is then filtered based on the user's criteria. This filtering process selects land information that meets the specified conditions.

[2401] Step 4:

[2402] The server selects the most suitable land from the filtered land information. The selection criteria include user conditions as well as evaluation criteria pre-configured on the server.

[2403] Step 5:

[2404] The server notifies the user's terminal of the land information it has selected. The notification includes detailed information about the land (location, price, area...

Claims

1. A means for the user to input the desired land conditions, A means for crawling a land database based on the aforementioned conditions and obtaining land information that meets the conditions, A means for filtering the acquired land information and selecting the most suitable land, A means of notifying the user of the selected land information, A means for automatically generating drawings based on the aforementioned land information, Means for inputting a request for modification to the aforementioned drawing, Means for regenerating the drawing based on the aforementioned modification request, A means for recommending furniture based on the aforementioned drawings, A system that includes this.

2. The system according to claim 1, comprising means for periodically crawling the aforementioned land information.

3. The system according to claim 1, wherein the means for automatically generating the drawings uses CAD software to generate the drawings.

Images