System

Abstract

To provide a system.SOLUTION: A system includes: means for gathering user's needs; means for comprehensively gathering information on running costs and environment including social security; artificial intelligence means for generating an ideal residence based upon the gathered information; means for generating a prompt sentence based upon the user's needs and the gathered information; AI means for inputting the generated prompt sentence to an artificial intelligence model to generate suggestions related to the ideal residence; and means for transmitting the suggestions generated by the AI means and related to the ideal residence to the user.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including a description and related instruction sentence regarding the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] When purchasing a home, it is necessary to consider the running costs and environment of the area, including social security, but it is difficult to comprehensively collect and understand such information. [Means for solving the problem]

[0005] We provide a system that combines a means of gathering user needs, a means of comprehensively gathering information on running costs including social security and the environment, and an AI means of generating the ideal home based on the collected information. This system allows us to propose the ideal home by collecting and considering scattered information, so that users can truly find their ideal home. [Brief description of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a process flow of the data processing system in the first embodiment of the first form example. [Figure 12] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the application example 1 of the first embodiment. [Figure 13] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the second embodiment of the second embodiment. [Figure 14] FIG. 13 is a sequence diagram showing a process flow of the data processing system in application example 2 of embodiment 2. [Figure 15] FIG. 13 is a sequence diagram showing a process flow of a data processing system in a third embodiment of the present invention. [Figure 16]FIG. 13 is a sequence diagram showing a process flow of the data processing system in the third application example of the third embodiment. [Figure 17] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] 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.

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

[0009] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0014] [First embodiment]

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

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (e.g., voice 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 voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

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

[0023] As shown in Fig. 2, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific process program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out 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 the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0027] "Example 1"

[0028] The system of the present invention includes a means for collecting user needs, a means for comprehensively collecting information on running costs and the environment, including social security, and an AI means for generating an ideal home based on the collected information. As a means for collecting user needs, it is possible to use information input by the user or a user's behavior history. In addition, as a means for comprehensively collecting information on running costs and the environment, including social security, it is possible to use a system that automatically collects information from public databases and the Internet. And, as an AI means for generating an ideal home based on this information, it is possible to use a system that uses a machine learning algorithm to comprehensively consider the user needs and the collected information and propose an ideal home.

[0029] "Example 2"

[0030] As a specific example, information that the user is of child-rearing age is collected as a user need, and comprehensive information such as the child-rearing support system, educational environment, and number of parks in the area where the user lives is collected. Then, based on this information, AI generates homes with an environment suitable for raising children and suggests them to the user. In this way, users are suggested homes that are optimized for their needs, allowing them to find their truly ideal home.

[0031] The process flow of each embodiment will be described below.

[0032] "Example 1"

[0033] Step 1: Collect user needs using information input by the user and user behavioral history, etc.

[0034] Step 2: Using a system that automatically collects information from public databases and the internet, comprehensively collect information on running costs, including social security, and the environment. Step 3: Using a machine learning algorithm, the system will comprehensively consider user needs and the collected information to propose an ideal home.

[0035] "Example 2"

[0036] Step 1: Collect information about the user's child-rearing generation as a user need. Step 2: Collect comprehensive information about the child-rearing support system, educational environment, number of parks, etc. in the area where the user lives.

[0037] Step 3: Based on this information, the AI ​​will generate homes with an environment suitable for raising children and make suggestions to the user.

[0038] Example 1

[0039] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0040] Conventional housing proposal systems have difficulty in integrating user needs with running costs and environmental information, including social security, making it difficult to propose optimal housing to users. In addition, there was a lack of means to accurately grasp needs by utilizing the user's behavioral history, which led to a problem of reduced proposal accuracy.

[0041] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0042] In this invention, the server includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the like and the environment, artificial intelligence means for generating an ideal home based on the collected information, means for generating a prompt sentence based on the user needs and the collected information, means for inputting the generated prompt sentence into an artificial intelligence model and generating a proposal for the ideal home, and means for transmitting the generated proposal to the user. This makes it possible to comprehensively consider the user needs, running costs including social security and the like, and environmental information, and to propose an optimal home to the user with high accuracy.

[0043] "User needs" refers to the conditions and requests that users have regarding their desired home.

[0044] "Running costs" refer to ongoing expenses related to housing, such as social security fees, taxes, and utility bills.

[0045] "Environmental information" refers to information about the surrounding environment of the home, including transportation access and the presence and distance of facilities such as schools, hospitals, and supermarkets.

[0046] "Artificial intelligence means" refers to means that use machine learning algorithms and generative AI models to generate an ideal home based on user needs and collected information.

[0047] A "prompt" is a document that is used as input to a generative AI model and is a written description that integrates user needs and collected information.

[0048] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to generate suggestions for ideal homes based on input prompt sentences.

[0049] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0050] This invention is a system that collects user needs, comprehensively collects running costs and environmental information, including social security, and creates an ideal home based on this information. A specific embodiment of this system will be described below.

[0051] Gathering user needs

[0052] Users input their housing needs through the terminal. For example, they input information such as the desired layout, budget, and location. The terminal transmits the input information to the server in real time. The transmission uses the HTTPS protocol to ensure data security. The user's behavioral history (previously viewed property information and search history) is also collected and stored in a database.

[0053] Collection of running costs and environmental information

[0054] The server automatically collects information from public databases and the Internet. Specifically, it collects information on social security fees, taxes, utility charges, transportation access, and the surrounding environment (schools, hospitals, supermarkets, etc.). To do this, it uses web scraping technologies such as Python's BeautifulSoup and Scrapy, as well as RESTful APIs. The collected information is stored in a database.

[0055] Creating the ideal home

[0056] The server generates a prompt based on the user's needs and the information it has collected. For example, it might generate a prompt like this:

[0057] User needs:

[0058] Desired layout: 3LDK

[0059] Budget: 30 million yen

[0060] Location: Within 10 minutes walk from the station

[0061] Information collected:

[0062] Social security costs: 200,000 yen per year

[0063] Utility bills: 10,000 yen per month

[0064] Access: 8 minutes walk to the nearest station

[0065] Neighborhood: Near supermarkets, hospitals, and schools

[0066] Use this information to suggest your ideal home.

[0067] The server inputs this prompt sentence into a generative AI model (e.g., GPT-4 (registered trademark)). The generative AI model generates suggestions for ideal housing based on the input prompt sentence. For example, it generates a specific suggestion such as, "I found a 3LDK property within my budget. It's an 8-minute walk from the nearest station, and there are supermarkets, hospitals, and schools in the surrounding area."

[0068] Submit a proposal

[0069] The server sends the generated proposal to the user, who can then review the proposal through the terminal and decide on the next action to take.

[0070] In this way, the system of the present invention is able to comprehensively consider user needs, running costs including social security, and environmental information, and to propose the most suitable home for the user with a high degree of accuracy.

[0071] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0072] Step 1: Gather user needs

[0073] 1.1 The user inputs their housing needs through the device. Specifically, they input information such as the desired layout, budget, location, etc. The input information is saved in a dedicated application on the device.

[0074] 1.2 The terminal transmits the input information to the server in real time using the HTTPS protocol to ensure data security.

[0075] 1.3 The server stores the received user needs in a database, so that the user's desired conditions are accumulated in the system.

[0076] Step 2: Collect user behavior history

[0077] 2.1 The server collects the user's behavioral history, specifically, the property information viewed in the past and search history.

[0078] 2.2 The server stores the collected behavioral history in a database, which allows the server to understand the user's preferences more accurately.

[0079] Step 3: Collect running costs and environmental information

[0080] 3.1 The server automatically collects information from public databases and the Internet, such as information on social security fees, taxes, utility fees, transportation access, and the surrounding environment (schools, hospitals, supermarkets, etc.).

[0081] 3.2 The server retrieves the required information using a web scraping technique such as Python's BeautifulSoup or Scrapy, or, if an API is provided, retrieves the data using a RESTful API.

[0082] 3.3 The server stores the collected information in a database, so that the latest running costs and environmental information are accumulated in the system.

[0083] Step 4: Generate a prompt

[0084] 4.1 The server generates a prompt based on the user's needs and the collected information. Specifically, the server combines the user's desired conditions with the collected running costs and environmental information to generate a prompt like the following:

[0085] User needs:

[0086] Desired layout: 3LDK

[0087] Budget: 30 million yen

[0088] Location: Within 10 minutes walk from the station

[0089] Information collected:

[0090] Social security costs: 200,000 yen per year

[0091] Utility bills: 10,000 yen per month

[0092] Access: 8 minutes walk to the nearest station

[0093] Neighborhood: Near supermarkets, hospitals, and schools

[0094] Use this information to suggest your ideal home.

[0095] 4.2 The server prepares the generated prompt sentence to be input to the generative AI model.

[0096] Step 5: Create your dream home

[0097] 5.1 The server inputs a prompt to a generative AI model (e.g., GPT-4). The generative AI model generates a proposal for an ideal home based on the input prompt.

[0098] 5.2 The generative AI model generates housing proposals that best fit the user's criteria. For example, it generates specific proposals such as, "I found a 3LDK property within my budget. It's an 8-minute walk from the nearest station, and there are supermarkets, hospitals, and schools nearby."

[0099] 5.3 The server stores the generated suggestions in a database.

[0100] Step 6: Submit your proposal

[0101] 6.1 The server sends the generated proposal to the user, either via email or via the notification feature of the application.

[0102] 6.2 The user confirms the proposal through the terminal and can decide the next action based on the proposal.

[0103] (Application example 1)

[0104] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0105] In today's housing selection process, users need to gather and compare a lot of information, but this process takes a lot of time and effort. It is not easy to find a home that is optimized for the user's needs. Furthermore, it is difficult to take into account important factors such as running costs and environmental information, making it difficult to find the ideal home. To solve these problems, a system is needed that can accurately gather the user's needs and propose the ideal home based on comprehensive information.

[0106] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0107] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information on running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means for collecting user needs based on user input information and behavior history, a means for automatically collecting running cost and environmental information from the Internet and public databases, a means for comprehensively considering user needs and the collected information using a machine learning algorithm and proposing an ideal home, and an application installed on a smartphone. This enables users to efficiently find an ideal home that is optimized for their needs.

[0108] "User needs" refer to the hopes and demands that users have regarding their homes.

[0109] "Running costs" are the ongoing expenses required to maintain a home.

[0110] "Environmental information" refers to information about the surrounding environment of a home, including, for example, transportation access, public safety, and the presence or absence of educational facilities.

[0111] "AI means" refers to a means that uses artificial intelligence to analyze data and make optimal suggestions.

[0112] A "machine learning algorithm" is an algorithm that learns patterns from data and makes predictions and classifications.

[0113] A "smartphone" is a type of mobile phone, a multi-function device that can connect to the Internet and install applications.

[0114] An "application" is software designed to provide a specific function or service.

[0115] A "public database" is a database provided by a government or public institution that contains highly reliable information.

[0116] "Behavioral history" is a record of a user's past actions and choices.

[0117] The "Internet" is a huge information and communications network that interconnects computer networks all over the world.

[0118] A system for implementing this invention includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the environment, AI means for generating an ideal home based on the collected information, means for collecting user needs based on user input information and behavioral history, means for automatically collecting running cost and environmental information from the Internet or public databases, means for comprehensively considering user needs and the collected information using a machine learning algorithm to propose an ideal home, and an application installed on a smartphone.

[0119] Program processing explanation

[0120] The server collects the needs and desired conditions entered by the user via their smartphone. These include the desired location, budget, size, and facilities. The server then automatically collects information about the running costs and environment of the specified location from the Internet and public databases. This information includes transportation access, public safety, and the availability of educational facilities.

[0121] The collected data is analyzed using a machine learning algorithm. Specifically, the data is preprocessed and the ideal home is predicted by comprehensively considering the user's needs and environmental information. For example, the machine learning algorithm used is Random Forest Regressor.

[0122] The application installed on the user's smartphone receives suggestions from the server and presents the user with their ideal home. The application makes optimized suggestions based on the information entered by the user and their behavioral history.

[0123] Examples

[0124] For example, if a user inputs, "I would like to live in Tokyo with a budget of 30 million yen, a space of 70 square meters, and facilities such as air conditioning and a balcony," the server will collect environmental information about Tokyo and suggest the ideal home based on the user's desired conditions.

[0125] Example prompt:

[0126] Please enter your desired location: Tokyo

[0127] Enter your budget: 3000

[0128] Enter your desired size: 70

[0129] Please enter the desired amenities (separated by commas): air conditioning, balcony

[0130] After entering this prompt, the application receives suggestions from the server and presents ideal homes to the user, allowing the user to efficiently find the ideal home that best suits their needs.

[0131] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0132] Step 1:

[0133] Users use their smartphones to input their needs, such as desired location, budget, size, and facilities.

[0134] Input: User needs (desired location, budget, size, facilities)

[0135] Output: User needs data

[0136] Specific operation: The user enters the desired conditions into the application's input form and presses the submit button.

[0137] Step 2:

[0138] The server receives user needs data and collects running costs and environmental information for the specified location from the Internet and public databases.

[0139] Input: User needs data

[0140] Output: Environmental information data

[0141] Specific operation: The server uses the API to obtain running costs and environmental information for the specified location.

[0142] Step 3:

[0143] The server preprocesses the collected user needs data and environmental information data.

[0144] Input: User needs data, environmental information data

[0145] Output: Preprocessed data

[0146] Specific operation: The server performs data cleaning, normalization, and feature engineering.

[0147] Step 4:

[0148] The server feeds the preprocessed data into a machine learning algorithm to predict the ideal home.

[0149] Input: Preprocessed data

[0150] Output: Proposal data for an ideal home

[0151] How it works: The server uses a machine learning model such as RandomForestRegressor to predict the ideal home.

[0152] Step 5:

[0153] The server sends suggested data for the ideal home to the smartphone.

[0154] Input: Ideal home proposal data

[0155] Output: Sending proposal data to a smartphone

[0156] Specific operation: The server sends the proposal data to the user's smartphone via the network.

[0157] Step 6:

[0158] The smartphone displays the received proposal data to the user.

[0159] Input: Proposal data

[0160] Output: What is displayed to the user

[0161] Specific operation: The smartphone application analyzes the proposal data and displays the ideal home for the user.

[0162] Example 2

[0163] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0164] Conventional housing proposal systems have difficulty in making proposals that are fully optimized to meet the needs of users. In particular, for users of child-rearing age, there is a demand for proposals based on comprehensive collection of information such as the local child-rearing support system, educational environment, and number of parks, but no system that can achieve this exists. Therefore, a new system that can propose housing that is optimized to the needs of users is needed.

[0165] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0166] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as the local childcare support system, the educational environment, and the number of parks, a means for analyzing the collected information using a data analysis tool and extracting the conditions for a home that best suits the user's needs, a means for proposing a home that best suits the user's needs using a generative AI model, and a means for presenting the proposed content to the user. This makes it possible to propose a home that is optimized for the user's needs.

[0167] "User needs" refers to information that indicates the conditions and desires required by users.

[0168] The "local child-rearing support system" is a general term for public support and services related to child-rearing provided in a specific area.

[0169] "Educational environment" refers to the condition of schools, educational facilities, education-related services and infrastructure in a particular area.

[0170] "Number of parks" refers to the total number of parks that exist within a particular area.

[0171] "Data analysis tools" is a general term for software and programs used to organize and analyze collected data and extract meaningful information.

[0172] A "generative AI model" is a general term for algorithms and programs that use artificial intelligence to generate an appropriate output for a specific input.

[0173] "Proposal Content" refers to specific proposed information about a home created by the generative AI model based on the user's needs.

[0174] The present invention is a system for proposing an optimal residence based on the needs of a user. A specific embodiment of this system is described below.

[0175] First, the user inputs their needs using the terminal. For example, the user inputs, "I'm in the child-rearing generation and want to live in Tokyo." This information is sent from the terminal to the server.

[0176] Next, the server collects information about the child-rearing support system, educational environment, number of parks, etc., in the area desired by the user. To do this, a web scraping tool (e.g. BeautifulSoup) or an API (e.g. Google (registered trademark) Places API) is used. For example, the server uses BeautifulSoup to scrape information about the child-rearing support system from the official Tokyo Metropolitan Government website, and obtains the number of parks using Google Places API.

[0177] The collected information is analyzed by the server using data analysis tools (e.g., Pandas, NumPy). The server converts the collected data into a data frame and scores it based on the level of support for childcare and the number of parks.

[0178] The server then uses a generative AI model (e.g. GPT-4) to suggest the best home for the user’s needs. It does this by inputting a prompt into the generative AI model. For example, the following prompt can be used:

[0179] Please suggest a suitable home in Tokyo for a child-rearing generation. Please consider the following conditions:

[0180] Childcare support system is well established

[0181] Good educational environment

[0182] There are many parks

[0183] The generative AI model generates suggestions based on this prompt.

[0184] Finally, the server sends the generated housing proposal to the device, and the device displays the proposal to the user. For example, the device may display on the user's screen, "The best area for raising children in Tokyo is ____ ward. There are many parks here, and the childcare support system is also well developed."

[0185] In this way, the user can receive proposals for homes that are optimized to their needs. This system performs a series of processes to propose the optimal home based on the user's needs, making it possible to provide the ideal home for the user.

[0186] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0187] Step 1:

[0188] Entering user information

[0189] The user uses the terminal to input his / her needs. For example, the user may input "I am of child-rearing age and would like to live in Tokyo."

[0190] Input: User needs (e.g. "child-rearing generation", "Tokyo area")

[0191] Output: User needs information is sent from the terminal to the server.

[0192] Specific operation: The user enters information on the screen of a smartphone or PC and presses the send button.

[0193] Step 2:

[0194] Gathering local information

[0195] The server collects information such as the child-rearing support system, educational environment, and number of parks in the user's desired area.

[0196] Input: User's needs information (e.g. "Tokyo")

[0197] Output: Information on local childcare support systems, educational environment, number of parks, etc.

[0198] Specific operation: The server uses a web scraping tool (e.g. BeautifulSoup) to scrape information about child-rearing support systems from the Tokyo Metropolitan Government's official website, and uses an API (e.g. Google Places API) to obtain the number of parks.

[0199] Step 3:

[0200] Data analysis and processing

[0201] The server analyzes the collected regional information using data analysis tools (e.g., Pandas, NumPy).

[0202] Input: Collected local information (e.g. childcare support system, educational environment, number of parks)

[0203] Output: The best living conditions for your needs

[0204] Specific operation: The server uses Pandas to convert the collected data into a data frame, and then performs scoring based on the comprehensiveness of the child-rearing support system and the number of parks.

[0205] Step 4:

[0206] Home proposal generation

[0207] The server uses a generative AI model (e.g. GPT-4) to suggest homes that best fit the user's needs.

[0208] Input: User needs information, analyzed regional information

[0209] Output: Housing proposals based on generative AI models

[0210] Specific operation: The server inputs the following prompt sentence into the generative AI model:

[0211] Please suggest a suitable home in Tokyo for a child-rearing generation. Please consider the following conditions:

[0212] Childcare support system is well established

[0213] Good educational environment

[0214] There are many parks

[0215] A generative AI model generates the suggestions.

[0216] Step 5:

[0217] Presenting the results

[0218] The server transmits the generated housing proposal to the terminal.

[0219] Input: Home proposals based on generative AI models

[0220] Output: Housing proposals presented to the user

[0221] Specific operation: The server sends the suggestions obtained from the generative AI model to the device, and the device displays on the user's screen, "The best area in Tokyo for raising children is Ward XX. There are many parks here, and there is an extensive child-rearing support system."

[0222] (Application example 2)

[0223] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0224] Conventional housing suggestion systems often do not provide suggestions that are fully optimized to meet the needs of users. In particular, for users of child-rearing age, there is a lack of housing suggestions that take into account information such as the local child-rearing support system, educational environment, and number of parks. This makes it difficult for users to find the home that is truly ideal for them.

[0225] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0226] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means for inputting that the user is of child-rearing age, a means for collecting information such as the local child-rearing support system, the educational environment, and the number of parks, a means for generating a home suitable for raising children based on the collected information, and a means for proposing the generated home to the user. This makes it possible to propose a home optimized to the user's needs.

[0227] "User needs" refers to the requirements and demands of users.

[0228] "Social security" refers to systems such as welfare, medical care, and pensions provided by the government and public institutions.

[0229] "Running costs" are the ongoing expenses required to maintain a home.

[0230] "Environment" refers to the natural and social conditions surrounding the home.

[0231] An "AI means" is a method or device that uses artificial intelligence to process information and achieve a specific purpose.

[0232] The "child-rearing generation" refers to people of the age group who are raising children.

[0233] A "childcare support system" refers to public services and systems provided to support childcare.

[0234] The "educational environment" refers to the facilities and surrounding conditions in which children learn.

[0235] "Number of parks" refers to the number of parks that exist within a particular area.

[0236] "Housing" refers to the house where people live and the surrounding environment.

[0237] A "suggestion" is the act of presenting the best option based on a specific purpose or condition.

[0238] A system for implementing this invention includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the environment, etc., AI means for generating an ideal home based on the collected information, means for inputting that the user is of child-rearing age, means for collecting information such as the local child-rearing support system, educational environment, and number of parks, means for generating a home suitable for raising children based on the collected information, and means for proposing the generated home to the user.

[0239] Hardware and Software Used

[0240] Hardware: Smartphone (iOS or ANDROID (registered trademark))

[0241] Software: Python, TENSORFLOW (registered trademark) (generating AI models), Google Maps API (collecting local information), Firebase (database)

[0242] Data processing and calculation

[0243] Entering user information

[0244] Users log in to a smartphone application and enter information about themselves as parents. For example, they might enter, "I have two children, ages 3 and 5."

[0245] Gathering local information

[0246] The server uses the Google Maps API to collect information such as the childcare support system, educational environment, and number of parks in the area where the user lives. For example, "collect childcare support system, educational environment, and number of parks in Shibuya Ward, Tokyo."

[0247] Creating homes using AI models

[0248] The server uses TensorFlow to generate housing suitable for raising children based on the collected local information. For example, it identifies areas in Shibuya Ward with a robust childcare support system and suggests optimal housing.

[0249] Suggestions for users

[0250] The server uses the data stored in Firebase to suggest the best place to live for the user. For example, it might suggest, "The Yoyogi area of ​​Shibuya Ward is a good place to raise children. We recommend the following properties."

[0251] Examples and prompts

[0252] Examples

[0253] A user logs into the app and enters, "I have two children, ages 3 and 5."

[0254] The app uses the Google Maps API to collect information on child-rearing support systems, educational environments, and the number of parks in Shibuya Ward, Tokyo.

[0255] Use TensorFlow to determine whether the Yoyogi area of ​​Shibuya Ward is suitable for raising children.

[0256] Based on the data stored in Firebase, properties in the Yoyogi area are suggested to users.

[0257] Examples of prompt statements

[0258] Please enter that you are of child-rearing age. Next, we will collect information about the area you live in and let the AI ​​generate the best home for you. For example, please enter "I have two children, ages 3 and 5."

[0259] In this way, users are presented with homes that are optimized to their needs, allowing them to truly find their ideal home.

[0260] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0261] Step 1:

[0262] Users log into a smartphone application and enter that they are of child-rearing age.

[0263] Input: User information (e.g. "I have two children. They are 3 and 5 years old.")

[0264] Output: The user information is sent to the server.

[0265] Specific actions: The user enters information about the parenting generation into the app's input form and presses the submit button.

[0266] Step 2:

[0267] The server uses the Google Maps API to collect information such as child care support systems, educational environments, and the number of parks in the user's area.

[0268] Input: Area information where the user lives (e.g. Shibuya-ku, Tokyo)

[0269] Output: Information such as the local childcare support system, educational environment, and number of parks is stored on the server.

[0270] Specific operation: The server sends a request to the Google Maps API to obtain information such as the child care support system, educational environment, and number of parks in the specified area.

[0271] Step 3:

[0272] The server uses TensorFlow to generate housing suitable for raising children based on the collected local information.

[0273] Input: Local information (childcare support system, educational environment, number of parks, etc.)

[0274] Output: Proposal data for housing suitable for raising children

[0275] Specific operation: The server runs the TensorFlow model and uses the collected local information as input to generate housing suitable for raising children.

[0276] Step 4:

[0277] The server uses the data stored in Firebase to suggest the most suitable home for the user.

[0278] Input: Generated housing proposal data

[0279] Output: Home information suggested to the user

[0280] What it does: The server retrieves the recommendation data from Firebase and displays the best homes for the user through the application.

[0281] Step 5:

[0282] The user reviews the proposed home information and views detailed information.

[0283] Input: Proposed Home Information

[0284] Output: Show detailed information

[0285] Specific operation: The user taps on the suggested home information within the application and is redirected to a screen where they can view more detailed information.

[0286] In this way, users are presented with homes that are optimized to their needs, allowing them to truly find their ideal home.

[0287] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0288] "Example 1"

[0289] In one embodiment of the present invention, a system is provided in which the means for collecting user needs includes an emotion engine that recognizes the user's emotions. This system is capable of grasping user needs more precisely by taking into account not only the user's behavior history and input information, but also the user's emotions. The emotion engine analyzes the user's emotions from facial expressions, tone of voice, and text input, and treats the information as part of the user's needs.

[0290] "Example 2"

[0291] As a concrete example, let's say a user is looking for a newly built detached house. The user inputs information into the system, such as their family composition, budget, and desired area. Furthermore, the emotion engine can sense from the user's tone of voice, facial expressions, and text input that the user places importance on a sense of security. Based on this information, the AI ​​will suggest properties in areas with good safety and educational environments. This makes it possible to suggest properties that meet not only the user's explicit needs, but also their emotional needs.

[0292] The process flow of each embodiment will be described below.

[0293] "Example 1"

[0294] Step 1: The user accesses the system and enters the necessary information (family composition, budget, desired area, etc.).

[0295] Step 2: The emotion engine analyzes the user's emotions from their tone of voice, facial expressions, and text input.

[0296] Step 3: Treat the analyzed emotional information as part of user needs.

[0297] Step 4: Based on the information and emotional information collected by the AI, the ideal home is suggested to the user.

[0298] "Example 2"

[0299] Step 1: The user enters information into the system that they are looking for a new home. Step 2: The emotion engine senses from the user's tone of voice, facial expression, and text input that the user values ​​a sense of security.

[0300] Step 3: Based on the information collected by the AI ​​and the emotional information it senses, it recommends properties in areas with good safety and educational environments.

[0301] Example 1

[0302] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0303] Conventional housing recommendation systems did not adequately collect user needs, making it difficult to make precise recommendations that took into account the user's emotions and behavioral history. In addition, they were unable to comprehensively collect information on social security, running costs, and the environment and consider them in an integrated manner, making it difficult to recommend the optimal home for the user. This led to issues such as low user satisfaction and the time and effort required to find the ideal home.

[0304] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0305] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means including an emotion engine for recognizing the user's emotions, a means for comprehensively considering the collected user needs, behavioral history, emotion data, running costs and environmental information, and a means for proposing an optimal home using a generative AI model. This makes it possible to grasp precise user needs taking into account the user's emotions and behavioral history, and to propose an optimal home that comprehensively takes into account social security, running costs and environmental information.

[0306] "User needs" refers to the hopes, requests, and conditions that users have regarding their home.

[0307] "Running costs" refers to ongoing expenses related to housing, such as social security, taxes, utility bills, etc.

[0308] "Environmental information" refers to information about the surrounding environment of a home, such as transportation access, surrounding facilities, public safety, and the natural environment.

[0309] "AI means" refers to a system that uses artificial intelligence technology to analyze data and generate the optimal home.

[0310] An "emotion engine" is a system that analyzes emotions from a user's facial expressions, tone of voice, and text input, and treats that information as part of the user's needs.

[0311] "Behavioral history" refers to data such as a user's past search history and browsing history.

[0312] A "generative AI model" is a model that uses machine learning algorithms to comprehensively consider user needs and collected information to propose the most suitable home.

[0313] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0314] This invention is a system that collects user needs, comprehensively collects running costs and environmental information, including social security, and creates an ideal home based on the collected information. A specific embodiment of this system will be described below.

[0315] Gathering user needs

[0316] A user logs into the system and inputs their housing requirements, including specific requirements such as rent, location, layout, and whether pets are allowed. The terminal transmits the user's input information to the server in real time. In addition, the server retrieves the user's past search and browsing history from a database and stores them together with the current requirements. Using an emotion engine, the system analyzes emotions from the user's facial expressions, tone of voice, and text input, and treats them as part of the user's needs.

[0317] Collection of running costs and environmental information

[0318] The server accesses public databases and automatically collects information on social security, taxes, utility fees, etc. for each region. It also scrapes and collects property information from real estate sites on the Internet. This makes it possible to comprehensively collect property information that matches the user's desired conditions.

[0319] Creating the ideal home

[0320] The server comprehensively considers the collected user needs, behavioral history, emotional data, running costs, and environmental information. Using a generative AI model, this data is input to generate the optimal home. For example, if the user prioritizes "a quiet environment and a park nearby," properties that meet these conditions will be selected as a priority. The generated home proposals are presented to the user by the server.

[0321] Examples

[0322] For example, let's say a user wants a property in Tokyo with a rent of less than 100,000 yen, pets allowed, and within a 10-minute walk from the station. In this case, the system will process as follows:

[0323] 1. The user enters the desired conditions into the system.

[0324] 2. The server collects property information for Tokyo from government statistical databases and real estate websites.

[0325] 3. The emotion engine analyzes the user's facial expressions and tone of voice when typing to identify the conditions that the user particularly values.

[0326] 4. Based on the collected information, the generative AI model suggests the most suitable properties.

[0327] Examples of prompt statements

[0328] "I am looking for a property in Tokyo that is under 100,000 yen in rent, allows pets, and is within a 10-minute walk from the station. I am particularly looking for a quiet environment and a park nearby."

[0329] By inputting this prompt into the generative AI model, properties that match the user's preferences are suggested.

[0330] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0331] Step 1:

[0332] A user logs into the system and inputs the desired conditions for a home.

[0333] Input: User's desired conditions (e.g. rent, location, layout, pets allowed, etc.)

[0334] Output: User's desired conditions data

[0335] Specific operation: The user enters the user name and password on the login screen and clicks the Login button. After that, the user enters the desired conditions in the input form and clicks the Send button.

[0336] Step 2:

[0337] The terminal transmits the user's input information to the server in real time.

[0338] Input: User's desired conditions data

[0339] Output: The desired conditions data sent to the server

[0340] Specific operation: The terminal transmits the desired conditions entered by the user to the server in real time. For example, conditions such as "rent less than 100,000 yen, in Tokyo, pets allowed, within 10 minutes' walk from the station" are transmitted.

[0341] Step 3:

[0342] The server retrieves the user's past search history and browsing history from a database and stores them together with the user's current desired conditions.

[0343] Input: User's desired conditions data, past search history and browsing history

[0344] Output: Consolidated user needs data

[0345] Specific operation: The server retrieves the user's past search history and browsing history from the database, integrates it with the current desired conditions, and saves it. For example, it retrieves information about properties searched for in the past and compares it with the current desired conditions.

[0346] Step 4:

[0347] The device uses an emotion engine to analyze the user's facial expressions and tone of voice, and transmits the emotion data to the server.

[0348] Input: User facial expressions, tone of voice, text input

[0349] Output: Emotion data

[0350] Specific operation: The device analyzes the user's facial expressions and tone of voice using an emotion engine, and sends emotional data to the server to identify the conditions that the user places special importance on. For example, if the user places importance on a "quiet environment," the device sends that information.

[0351] Step 5:

[0352] The server accesses public databases and automatically collects information such as social security, taxes, and utility fees for each region.

[0353] Input: Public database

[0354] Output: Social security, tax, utility fee information by region

[0355] Specific operation: The server accesses a government statistical database and collects information on social security, taxes, utility fees, etc. by region. For example, it obtains the average rent and living expenses in Tokyo.

[0356] Step 6:

[0357] The server scrapes and collects property information from real estate sites on the Internet.

[0358] Input: Real estate website on the Internet

[0359] Output:Property information

[0360] Specific operation: The server scrapes and collects property information from real estate sites on the Internet. For example, it obtains property information within Tokyo.

[0361] Step 7:

[0362] The server stores the collected information in a database and compares it with the user's desired conditions.

[0363] Input: Collected social security, taxes, utilities, property information

[0364] Output: Matched property information

[0365] Specific operation: The server saves the collected information in a database and compares it with the user's desired conditions. For example, it filters properties with rent of less than 100,000 yen, pet-friendly properties, and properties within a 10-minute walk from the station.

[0366] Step 8:

[0367] The server comprehensively considers collected user needs, behavioral history, emotional data, running costs, and environmental information.

[0368] Input: User needs, behavioral history, emotional data, running costs, environmental information

[0369] Output: Consolidated data

[0370] Specific operation: The server comprehensively considers the collected user needs, behavioral history, emotional data, running costs, and environmental information, and integrates the data.

[0371] Step 9:

[0372] The server inputs this data into a generative AI model to generate the optimal home.

[0373] Input: Consolidated data

[0374] Output: Optimal home proposal

[0375] Specific operation: The server inputs the integrated data into the generative AI model and generates the optimal home. For example, if the user prioritizes "a quiet environment and a park nearby," the server will prioritize properties that meet those conditions.

[0376] Step 10:

[0377] The server presents the generated housing proposals to the user.

[0378] Input: Best Home Proposal

[0379] Output: Home proposals presented to the user

[0380] Specific operation: The server presents the generated housing proposals to the user. The user can check the detailed information of the proposed properties and select the property they like.

[0381] (Application example 1)

[0382] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0383] Conventional housing proposal systems were unable to fully reflect the needs of users, and it was difficult to comprehensively collect information on social security, running costs, and the environment. As a result, it was difficult to propose the optimal home for the user. In addition, there was a problem of low user satisfaction because proposals could not be made that took the user's feelings into account.

[0384] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0385] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means including an emotion engine for analyzing user emotions, a means for automatically collecting information from public databases and the Internet, a means for comprehensively considering user needs and the collected information using a machine learning algorithm and proposing the most suitable property, and a means including a smartphone application. This makes it possible to propose the most suitable home considering the user's needs and emotions.

[0386] "Means of collecting user needs" refers to means for collecting the user's desired conditions and requests, and includes the user's input information and behavioral history.

[0387] "Means of comprehensively collecting information on running costs, including social security, and the environment" refers to means for comprehensively collecting information on social security, running costs, the environment, etc. related to housing, and includes systems that automatically collect information from public databases and the Internet.

[0388] An "AI method for generating an ideal home" is a method that uses artificial intelligence technology to generate the optimal home for the user based on collected information.

[0389] "Means including an emotion engine for analyzing user emotions" refers to means for analyzing emotions from a user's facial expressions, tone of voice, and text input, and treating the information as part of the user's needs.

[0390] "Means of automatically collecting information from public databases and the Internet" refers to means of automatically collecting information on social security, running costs, environmental information, etc. from public databases and the Internet.

[0391] "A means for comprehensively considering user needs and collected information using a machine learning algorithm to suggest the most suitable property" refers to a means for comprehensively analyzing user needs and collected information using machine learning technology to suggest the most suitable property to the user.

[0392] "Means including smartphone applications" refer to means including applications that users use to search for their ideal home via their smartphones.

[0393] This invention is a system that collects user needs, comprehensively collects information on social security, running costs, environmental information, etc., and creates an ideal home based on that information. A specific embodiment of this system is described below.

[0394] System Configuration

[0395] The system consists of the following main components:

[0396] 1. How to gather user needs:

[0397] Users input their desired conditions (e.g. budget, floor plan, location, etc.) through a smartphone application.

[0398] Record user activity (e.g. properties viewed, properties saved, etc.).

[0399] The emotion engine analyzes emotions from the user's facial expressions, tone of voice, and text input.

[0400] 2. Comprehensive collection of information:

[0401] Use a system that automatically collects information from public databases and the Internet.

[0402] The information to be collected includes social security, running costs, environmental information, etc.

[0403] 3. AI methods to generate ideal homes:

[0404] Using machine learning algorithms, the system comprehensively considers user needs and collected information to suggest the most suitable properties.

[0405] Program processing explanation

[0406] The server collects user input information, behavioral history, and emotion analysis results from an emotion engine. This allows the system to understand the user's needs in detail. It then automatically collects information from public databases and the Internet to comprehensively obtain information on social security, running costs, the environment, and more.

[0407] Based on this information, a machine learning algorithm is used to comprehensively analyze the user's needs and the collected information, and the system proposes the most suitable property. Specifically, the system considers the user's desired conditions and the results of sentiment analysis to generate the most suitable home.

[0408] Hardware and Software Used

[0409] Hardware:

[0410] Smartphone: A device that allows users to input desired conditions and perform sentiment analysis.

[0411] Server: A central processing unit for collecting, analyzing, and storing data.

[0412] software:

[0413] Emotion engine: Software for analyzing emotions from a user's facial expressions, tone of voice, and text input.

[0414] Machine learning algorithm: An algorithm that comprehensively analyzes user needs and collected information to suggest the most suitable properties.

[0415] Public database access system: A system for collecting information on social security, running costs, and the environment.

[0416] Examples

[0417] For example, if a user types in, "I'm looking for a quiet location with good schools nearby," the emotion engine will analyze the "sense of security" from the user's text and suggest the most suitable property along with budget and location information.

[0418] Examples of prompt statements

[0419] Design an application that, when searching for an ideal home, inputs the desired conditions (budget, layout, location, etc.), analyzes the user's emotions using an emotion engine, and suggests the most suitable property. Collect running costs and environmental information from public databases, and use a machine learning model to make suggestions by taking into consideration the user's needs and the collected information in an integrated manner.

[0420] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0421] Step 1:

[0422] The user inputs the desired conditions through a smartphone application.

[0423] Input: User's desired conditions (e.g. budget, layout, location, etc.)

[0424] Output: User's desired conditions data

[0425] Specific operation: The user enters the desired conditions into the application's input form and presses the submit button. The application sends the entered data to the server.

[0426] Step 2:

[0427] The server records the user's behavior.

[0428] Input: User behavior history (e.g. properties viewed, properties saved, etc.)

[0429] Output: User behavior history data

[0430] How it works: The application monitors user actions and sends information about viewed and saved properties to the server, which then stores the data in a database.

[0431] Step 3:

[0432] The server uses an emotion engine to analyze the user's emotions.

[0433] Input: User facial expressions, tone of voice, text input

[0434] Output: User sentiment data

[0435] How it works: The application captures the user's facial expressions and tone of voice with a camera and microphone, analyzes the text input, and sends this data to the emotion engine, which returns the analysis results to the server.

[0436] Step 4:

[0437] The server automatically collects information from public databases and the Internet.

[0438] Input: Public databases and information from the internet

[0439] Output: Social security, running costs, environmental information data

[0440] Specific operation: The server periodically crawls public databases and information on the Internet, collects the necessary data, and stores it in a database.

[0441] Step 5:

[0442] The server uses machine learning algorithms to comprehensively analyze user needs and collected information.

[0443] Input: User desired conditions data, behavioral history data, emotion data, social security, running costs, environmental information data

[0444] Output: Optimal property proposal data

[0445] How it works: The server runs a machine learning algorithm to comprehensively analyze the input data. The algorithm takes into account the user's needs and the collected information to suggest the best properties.

[0446] Step 6:

[0447] The server notifies the user of the best property suggestions.

[0448] Input: Data for optimal property proposals

[0449] Output:Notification to the user

[0450] Specific operation: The server sends the optimal property recommendation data to the smartphone application, and the application displays a notification to the user.

[0451] Example 2

[0452] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0453] Conventional housing recommendation systems mainly make suggestions based on the explicit needs of users, and do not take into account the emotional needs of users or detailed information about the area. This makes it difficult for users to find the ideal home.

[0454] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0455] In this invention, the server includes a means for collecting user needs, a means for performing emotion analysis, a means for collecting information such as the local childcare support system, the educational environment, and the number of parks, an artificial intelligence means for generating an ideal home based on the collected information, and a means for proposing the generated home to the user. This makes it possible to propose an optimal home that takes into account not only the explicit needs of the user but also emotional needs and detailed information about the area.

[0456] "User needs" refers to information that indicates the conditions and desires required by users.

[0457] "Emotion analysis" is a technology that analyzes emotions from a user's tone of voice, facial expressions, text input, etc.

[0458] The "local child-rearing support system" is a general term for child-rearing support and services provided in a specific area.

[0459] "Educational environment" is a general term for educational facilities and education-related environments in a particular area.

[0460] "Number of parks" is the total number of parks in a particular area.

[0461] "Artificial intelligence means" refers to artificial intelligence technology for generating an ideal home based on collected information.

[0462] "Means of proposing a home" refers to technology for presenting the generated ideal home to the user.

[0463] The present invention is a system for proposing an optimal residence based on the needs of a user. A specific embodiment of this system will be described below.

[0464] First, the user uses the terminal to input information such as family composition, budget, desired area, etc. For example, the user inputs information such as "Family composition is four people, budget is within 50 million yen, and desired area is within Tokyo."

[0465] Next, the device performs emotion analysis. While the user is entering information into the input form, the camera and microphone are used to record the user's facial expressions and tone of voice. For emotion analysis, a common emotion analysis API is used. For example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API is used to analyze the importance of the user's sense of security.

[0466] The server then stores the information entered by the user and the results of the sentiment analysis in a database, allowing the necessary information to be efficiently retrieved for subsequent processing.

[0467] Next, the server collects related information from the Internet. Specifically, it uses Google Maps API and the government's open data API to collect information such as the childcare support system, educational environment, and number of parks in the area where the user lives. For example, it obtains information such as "Number of parks in Tokyo: 50, number of public schools: 30, number of childcare support centers: 10."

[0468] The server uses a generative AI model based on the collected data and the results of sentiment analysis to generate properties that are optimal for the user. For example, OpenAI's (registered trademark) GPT-4 is used as the generative AI model. This generative AI model proposes properties that meet the user's explicit and emotional needs.

[0469] Finally, the server proposes the generated property information to the user, who can then check the details of "a newly built detached house in a safe area of ​​Tokyo with a good educational environment" on his / her terminal.

[0470] As a concrete example, consider the case where a user is looking for a newly built detached house. The user inputs information into the system, such as family composition, budget, and desired area. Furthermore, the emotion engine senses from the user's tone of voice, facial expression, and text input that the user places importance on a sense of security. Based on this information, the AI ​​suggests properties in areas with good safety and educational environments. This makes it possible to suggest properties that meet not only the user's explicit needs, but also their emotional needs.

[0471] Examples of prompts include:

[0472] "We have a family of four and our budget is within 50 million yen. We would like to live in a location within Tokyo. We value a sense of security. We are looking for a newly built detached house in an area with a good childcare support system and educational environment."

[0473] In this way, the present invention can propose optimal housing that meets the diverse needs of users.

[0474] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0475] Step 1:

[0476] The user enters information

[0477] The user inputs information such as family composition, budget, and desired area into the input form on the terminal. For example, the user inputs "Family composition is 4 people, budget is 50 million yen or less, and desired area is within Tokyo." The input information is sent from the terminal to the server. The input data is text data such as family composition, budget, and desired area.

[0478] Step 2:

[0479] The device performs emotion analysis

[0480] The device uses a camera and microphone to record the user's facial expressions and tone of voice while the user is entering information into an input form. A common emotion analysis API is used for emotion analysis. For example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API is used to analyze whether the user values ​​a sense of security. The input data is the user's facial expressions and tone of voice, and the output data is the user's emotional state (e.g., emphasis on a sense of security).

[0481] Step 3:

[0482] The server stores the user's input in a database

[0483] The server stores the information entered by the user and the results of the emotion analysis in a database. This allows the necessary information to be efficiently retrieved for subsequent processing. The input data is text data such as family composition, budget, desired area, and emotional state, and the output data is the information stored in the database.

[0484] Step 4:

[0485] The server collects relevant information from the Internet.

[0486] The server uses Google Maps API and the government's open data API to collect information such as the child-rearing support system, educational environment, and number of parks in the area where the user lives. For example, it obtains information such as "Number of parks in Tokyo: 50, number of public schools: 30, number of child-rearing support centers: 10." The input data is the user's desired area, and the output data is information such as the local child-rearing support system, educational environment, and number of parks.

[0487] Step 5:

[0488] The server generates properties using generative AI models

[0489] The server uses a generative AI model (e.g., OpenAI's GPT-4) based on the collected data and the results of sentiment analysis to generate the best property for the user. The generative AI model proposes properties that meet the user's explicit and emotional needs. The input data are the user's needs, emotional state, and area information, and the output data is the proposed property information.

[0490] Step 6:

[0491] Propose server-generated properties to users

[0492] The server proposes the property information generated by the generative AI model to the user. The user can check detailed information on "a newly built detached house in a safe area of ​​Tokyo with a good educational environment" on the terminal. The input data is the generated property information, and the output data is the property information presented to the user.

[0493] (Application example 2)

[0494] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0495] Conventional real estate property recommendation systems were able to make suggestions based on the user's explicit needs, but were unable to make suggestions that took into account the user's emotional needs. This made it difficult for users to find properties that truly satisfied them. In addition, there was a lack of systems that comprehensively collected information such as the local childcare support system, educational environment, and number of parks, and suggested the most suitable home for users. This made it difficult for users, especially those of child-rearing age, to find the ideal home.

[0496] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0497] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information on running costs including social security and the like, the environment, and the like, an AI means for generating an ideal home based on the collected information, a means for analyzing the user's emotions, a means for proposing properties based on the user's emotional needs, and a means for displaying detailed information on the proposed properties. This makes it possible to propose properties that simultaneously satisfy the user's explicit needs and emotional needs.

[0498] "Means of collecting user needs" refers to the interface and data collection functions that allow users to input their desired conditions and requests.

[0499] "Means of comprehensively collecting information on running costs, including social security, and the environment" refers to a data collection system for comprehensively collecting information on the local social security system, living expenses, educational environment, number of parks, etc.

[0500] "AI means for generating an ideal home" refers to an artificial intelligence algorithm that uses collected information to generate a home that best suits the user's needs.

[0501] "Means of analyzing user emotions" refers to an emotion analysis engine for analyzing emotions from the user's tone of voice, facial expressions, text input, etc.

[0502] "Means for suggesting properties based on a user's emotional needs" refers to a system for suggesting properties that meet a user's emotional needs based on the results of sentiment analysis.

[0503] "Means for displaying detailed information about the proposed property" means a display or interface for visually providing detailed information about the proposed property to a user.

[0504] An embodiment of the present invention will be described below. The system described below includes AI means for collecting user needs, comprehensively collecting information on running costs including social security and the environment, and generating an ideal home based on the collected information. It also includes means for analyzing the user's emotions, proposing properties based on the emotional needs, and displaying detailed information on the proposed properties.

[0505] System Configuration

[0506] 1. Hardware and Software Use

[0507] Hardware: Smartphones, smart glasses

[0508] Software: Sentiment analysis engines (e.g. Affectiva), data collection APIs (e.g. Google Places API), generative AI models (e.g. GPT-4)

[0509] Data processing and calculation

[0510] 1. Gathering user needs

[0511] Users input information such as their family composition, budget, and desired area via their smartphone or smart glasses.

[0512] The emotion analysis engine analyzes emotions from the user's tone of voice, facial expressions, and text input.

[0513] 2. Collecting local information

[0514] Using the Google Places API, we collect information such as child care support systems, educational environments, and the number of parks in the area where the user lives.

[0515] 3. Creating the ideal home

[0516] Based on the collected data, a generative AI model (GPT-4) is used to generate a home that is suitable for raising children.

[0517] 4. Property proposal

[0518] Suggest properties that meet users' explicit and emotional needs.

[0519] Detailed information about the proposed property will be displayed on the display of a smartphone or smart glasses.

[0520] Examples

[0521] Example prompt:

[0522] User information: Family size = 4, Budget = 50 million yen, Preferred area = Tokyo

[0523] Sentiment analysis results: Emphasis on feeling safe

[0524] Local information: Childcare support system = comprehensive, educational environment = good, number of parks = many

[0525] Inputs to the generative AI model:

[0526] A user with a family of four and a budget of 50 million yen is looking for a property in Tokyo that prioritizes peace of mind. Please suggest a property in an area with a good child-rearing support system, a good educational environment, and many parks.

[0527] In this way, it becomes possible to propose properties that meet the user's explicit and emotional needs at the same time.

[0528] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0529] Step 1:

[0530] Users input information such as family composition, budget, and desired area through their smartphone or smart glasses. The input information is sent to the server, which then stores the information in a database.

[0531] Input: User information such as family composition, budget, desired area, etc.

[0532] Output: User information stored in the database

[0533] Step 2:

[0534] The server uses an emotion analysis engine to analyze the user's tone of voice, facial expressions, and text input to determine their emotions. The analysis results are stored in a database as the user's emotional needs.

[0535] Input: User tone of voice, facial expressions, text input

[0536] Output: Sentiment analysis results (e.g., emphasis on feeling safe)

[0537] Step 3:

[0538] The server uses the Google Places API to collect information about the childcare support system, educational environment, number of parks, etc. in the area where the user lives. The collected information is stored in a database.

[0539] Input: The user's preferred region

[0540] Output: Information on local childcare support systems, educational environment, number of parks, etc.

[0541] Step 4:

[0542] The server uses a generative AI model (GPT-4) based on collected user information, emotion analysis results, and regional information to generate homes that are suitable for raising children. The generated home information is stored in a database.

[0543] Input: User information, sentiment analysis results, region information

[0544] Output: Generated ideal home information

[0545] Step 5:

[0546] Based on the generated home information, the server suggests properties that meet the user's explicit and emotional needs, and the details of the suggested properties are displayed on the display of the smartphone or smart glasses.

[0547] Input: Generated ideal home information

[0548] Output: Details of the proposed property

[0549] Step 6:

[0550] Users check detailed property information displayed on their smartphone or smart glasses displays and select the property they are interested in. The information on the selected property is sent to the server and stored in a database.

[0551] Input: Proposed property details

[0552] Output: Information about the selected property

[0553] In this way, it becomes possible to propose properties that meet the user's explicit and emotional needs at the same time.

[0554] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0555] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0556] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0557] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0558] [Second embodiment]

[0559] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0560] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0561] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0562] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0563] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0564] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0565] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0566] Fig. 4 shows an example of main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0567] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0568] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0569] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0570] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0571] "Example 1"

[0572] The system of the present invention includes a means for collecting user needs, a means for comprehensively collecting information on running costs and the environment, including social security, and an AI means for generating an ideal home based on the collected information. As a means for collecting user needs, it is possible to use information input by the user or a user's behavior history. In addition, as a means for comprehensively collecting information on running costs and the environment, including social security, it is possible to use a system that automatically collects information from public databases and the Internet. And, as an AI means for generating an ideal home based on this information, it is possible to use a system that uses a machine learning algorithm to comprehensively consider the user needs and the collected information and propose an ideal home.

[0573] "Example 2"

[0574] As a specific example, information that the user is of child-rearing age is collected as a user need, and comprehensive information such as the child-rearing support system, educational environment, and number of parks in the area where the user lives is collected. Then, based on this information, AI generates homes with an environment suitable for raising children and suggests them to the user. In this way, users are suggested homes that are optimized for their needs, allowing them to find their truly ideal home.

[0575] The process flow of each embodiment will be described below.

[0576] "Example 1"

[0577] Step 1: Collect user needs using information input by the user and user behavioral history, etc.

[0578] Step 2: Using a system that automatically collects information from public databases and the internet, comprehensively collect information on running costs, including social security, and the environment. Step 3: Using a machine learning algorithm, the system will comprehensively consider user needs and the collected information to propose an ideal home.

[0579] "Example 2"

[0580] Step 1: Collect information about the user's child-rearing generation as a user need. Step 2: Collect comprehensive information about the child-rearing support system, educational environment, number of parks, etc. in the area where the user lives.

[0581] Step 3: Based on this information, the AI ​​will generate homes with an environment suitable for raising children and make suggestions to the user.

[0582] Example 1

[0583] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0584] Conventional housing proposal systems have difficulty in integrating user needs with running costs and environmental information, including social security, making it difficult to propose optimal housing to users. In addition, there was a lack of means to accurately grasp needs by utilizing the user's behavioral history, which led to a problem of reduced proposal accuracy.

[0585] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0586] In this invention, the server includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the like and the environment, artificial intelligence means for generating an ideal home based on the collected information, means for generating a prompt sentence based on the user needs and the collected information, means for inputting the generated prompt sentence into an artificial intelligence model and generating a proposal for the ideal home, and means for transmitting the generated proposal to the user. This makes it possible to comprehensively consider the user needs, running costs including social security and the like, and environmental information, and to propose an optimal home to the user with high accuracy.

[0587] "User needs" refers to the conditions and requests that users have regarding their desired home.

[0588] "Running costs" refer to ongoing expenses related to housing, such as social security fees, taxes, and utility bills.

[0589] "Environmental information" refers to information about the surrounding environment of the home, including transportation access and the presence and distance of facilities such as schools, hospitals, and supermarkets.

[0590] "Artificial intelligence means" refers to means that use machine learning algorithms and generative AI models to generate an ideal home based on user needs and collected information.

[0591] A "prompt" is a document that is used as input to a generative AI model and is a written description that integrates user needs and collected information.

[0592] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to generate suggestions for ideal homes based on input prompt sentences.

[0593] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0594] This invention is a system that collects user needs, comprehensively collects running costs and environmental information, including social security, and creates an ideal home based on this information. A specific embodiment of this system will be described below.

[0595] Gathering user needs

[0596] Users input their housing needs through the terminal. For example, they input information such as the desired layout, budget, and location. The terminal transmits the input information to the server in real time. The transmission uses the HTTPS protocol to ensure data security. The user's behavioral history (previously viewed property information and search history) is also collected and stored in a database.

[0597] Collection of running costs and environmental information

[0598] The server automatically collects information from public databases and the Internet. Specifically, it collects information on social security fees, taxes, utility charges, transportation access, and the surrounding environment (schools, hospitals, supermarkets, etc.). To do this, it uses web scraping technologies such as Python's BeautifulSoup and Scrapy, as well as RESTful APIs. The collected information is stored in a database.

[0599] Creating the ideal home

[0600] The server generates a prompt based on the user's needs and the information it has collected. For example, it might generate a prompt like this:

[0601] User needs:

[0602] Desired layout: 3LDK

[0603] Budget: 30 million yen

[0604] Location: Within 10 minutes walk from the station

[0605] Information collected:

[0606] Social security costs: 200,000 yen per year

[0607] Utility bills: 10,000 yen per month

[0608] Access: 8 minutes walk to the nearest station

[0609] Neighborhood: Near supermarkets, hospitals, and schools

[0610] Use this information to suggest your ideal home.

[0611] The server inputs this prompt into a generative AI model (e.g. GPT-4). The generative AI model generates suggestions for ideal housing based on the input prompt. For example, it generates specific suggestions such as, "I found a 3LDK property within my budget. It's an 8-minute walk from the nearest station, and there are supermarkets, hospitals, and schools in the surrounding area."

[0612] Submit a proposal

[0613] The server sends the generated proposal to the user, who can then review the proposal through the terminal and decide on the next action to take.

[0614] In this way, the system of the present invention is able to comprehensively consider user needs, running costs including social security, and environmental information, and to propose the most suitable home for the user with a high degree of accuracy.

[0615] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0616] Step 1: Gather user needs

[0617] 1.1 The user inputs their housing needs through the device. Specifically, they input information such as the desired layout, budget, location, etc. The input information is saved in a dedicated application on the device.

[0618] 1.2 The terminal transmits the input information to the server in real time using the HTTPS protocol to ensure data security.

[0619] 1.3 The server stores the received user needs in a database, so that the user's desired conditions are accumulated in the system.

[0620] Step 2: Collect user behavior history

[0621] 2.1 The server collects the user's behavioral history, specifically, the property information viewed in the past and search history.

[0622] 2.2 The server stores the collected behavioral history in a database, which allows the server to understand the user's preferences more accurately.

[0623] Step 3: Collect running costs and environmental information

[0624] 3.1 The server automatically collects information from public databases and the Internet, such as information on social security fees, taxes, utility fees, transportation access, and the surrounding environment (schools, hospitals, supermarkets, etc.).

[0625] 3.2 The server retrieves the required information using a web scraping technique such as Python's BeautifulSoup or Scrapy, or, if an API is provided, retrieves the data using a RESTful API.

[0626] 3.3 The server stores the collected information in a database, so that the latest running costs and environmental information are accumulated in the system.

[0627] Step 4: Generate a prompt

[0628] 4.1 The server generates a prompt based on the user's needs and the collected information. Specifically, the server combines the user's desired conditions with the collected running costs and environmental information to generate a prompt like the following:

[0629] User needs:

[0630] Desired layout: 3LDK

[0631] Budget: 30 million yen

[0632] Location: Within 10 minutes walk from the station

[0633] Information collected:

[0634] Social security costs: 200,000 yen per year

[0635] Utility bills: 10,000 yen per month

[0636] Access: 8 minutes walk to the nearest station

[0637] Neighborhood: Near supermarkets, hospitals, and schools

[0638] Use this information to suggest your ideal home.

[0639] 4.2 The server prepares the generated prompt sentence to be input to the generative AI model.

[0640] Step 5: Create your dream home

[0641] 5.1 The server inputs a prompt to a generative AI model (e.g., GPT-4). The generative AI model generates a proposal for an ideal home based on the input prompt.

[0642] 5.2 The generative AI model generates housing proposals that best fit the user's criteria. For example, it generates specific proposals such as, "I found a 3LDK property within my budget. It's an 8-minute walk from the nearest station, and there are supermarkets, hospitals, and schools nearby."

[0643] 5.3 The server stores the generated suggestions in a database.

[0644] Step 6: Submit your proposal

[0645] 6.1 The server sends the generated proposal to the user, either via email or via the notification feature of the application.

[0646] 6.2 The user confirms the proposal through the terminal and can decide the next action based on the proposal.

[0647] (Application example 1)

[0648] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0649] In today's housing selection process, users need to gather and compare a lot of information, but this process takes a lot of time and effort. It is not easy to find a home that is optimized for the user's needs. Furthermore, it is difficult to take into account important factors such as running costs and environmental information, making it difficult to find the ideal home. To solve these problems, a system is needed that can accurately gather the user's needs and propose the ideal home based on comprehensive information.

[0650] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0651] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information on running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means for collecting user needs based on user input information and behavior history, a means for automatically collecting running cost and environmental information from the Internet and public databases, a means for comprehensively considering user needs and the collected information using a machine learning algorithm and proposing an ideal home, and an application installed on a smartphone. This enables users to efficiently find an ideal home that is optimized for their needs.

[0652] "User needs" refer to the hopes and demands that users have regarding their homes.

[0653] "Running costs" are the ongoing expenses required to maintain a home.

[0654] "Environmental information" refers to information about the surrounding environment of a home, including, for example, transportation access, public safety, and the presence or absence of educational facilities.

[0655] "AI means" refers to a means that uses artificial intelligence to analyze data and make optimal suggestions.

[0656] A "machine learning algorithm" is an algorithm that learns patterns from data and makes predictions and classifications.

[0657] A "smartphone" is a type of mobile phone, a multi-function device that can connect to the Internet and install applications.

[0658] An "application" is software designed to provide a specific function or service.

[0659] A "public database" is a database provided by a government or public institution that contains highly reliable information.

[0660] "Behavioral history" is a record of a user's past actions and choices.

[0661] The "Internet" is a huge information and communications network that interconnects computer networks all over the world.

[0662] A system for implementing this invention includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the environment, AI means for generating an ideal home based on the collected information, means for collecting user needs based on user input information and behavioral history, means for automatically collecting running cost and environmental information from the Internet or public databases, means for comprehensively considering user needs and the collected information using a machine learning algorithm to propose an ideal home, and an application installed on a smartphone.

[0663] Program processing explanation

[0664] The server collects the needs and desired conditions entered by the user via their smartphone. These include the desired location, budget, size, and facilities. The server then automatically collects information about the running costs and environment of the specified location from the Internet and public databases. This information includes transportation access, public safety, and the availability of educational facilities.

[0665] The collected data is analyzed using a machine learning algorithm. Specifically, the data is preprocessed and the ideal home is predicted by comprehensively considering the user's needs and environmental information. For example, the machine learning algorithm used is Random Forest Regressor.

[0666] The application installed on the user's smartphone receives suggestions from the server and presents the user with their ideal home. The application makes optimized suggestions based on the information entered by the user and their behavioral history.

[0667] Examples

[0668] For example, if a user inputs, "I would like to live in Tokyo with a budget of 30 million yen, a space of 70 square meters, and facilities such as air conditioning and a balcony," the server will collect environmental information about Tokyo and suggest the ideal home based on the user's desired conditions.

[0669] Example prompt:

[0670] Please enter your desired location: Tokyo

[0671] Enter your budget: 3000

[0672] Enter your desired size: 70

[0673] Please enter the desired amenities (separated by commas): air conditioning, balcony

[0674] After entering this prompt, the application receives suggestions from the server and presents ideal homes to the user, allowing the user to efficiently find the ideal home that best suits their needs.

[0675] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0676] Step 1:

[0677] Users use their smartphones to input their needs, such as desired location, budget, size, and facilities.

[0678] Input: User needs (desired location, budget, size, facilities)

[0679] Output: User needs data

[0680] Specific operation: The user enters the desired conditions into the application's input form and presses the submit button.

[0681] Step 2:

[0682] The server receives user needs data and collects running costs and environmental information for the specified location from the Internet and public databases.

[0683] Input: User needs data

[0684] Output: Environmental information data

[0685] Specific operation: The server uses the API to obtain running costs and environmental information for the specified location.

[0686] Step 3:

[0687] The server preprocesses the collected user needs data and environmental information data.

[0688] Input: User needs data, environmental information data

[0689] Output: Preprocessed data

[0690] Specific operation: The server performs data cleaning, normalization, and feature engineering.

[0691] Step 4:

[0692] The server feeds the preprocessed data into a machine learning algorithm to predict the ideal home.

[0693] Input: Preprocessed data

[0694] Output: Proposal data for an ideal home

[0695] How it works: The server uses a machine learning model such as RandomForestRegressor to predict the ideal home.

[0696] Step 5:

[0697] The server sends suggested data for the ideal home to the smartphone.

[0698] Input: Ideal home proposal data

[0699] Output: Sending proposal data to a smartphone

[0700] Specific operation: The server sends the proposal data to the user's smartphone via the network.

[0701] Step 6:

[0702] The smartphone displays the received proposal data to the user.

[0703] Input: Proposal data

[0704] Output: What is displayed to the user

[0705] Specific operation: The smartphone application analyzes the proposal data and displays the ideal home for the user.

[0706] Example 2

[0707] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0708] Conventional housing proposal systems have difficulty in making proposals that are fully optimized to meet the needs of users. In particular, for users of child-rearing age, there is a demand for proposals based on comprehensive collection of information such as the local child-rearing support system, educational environment, and number of parks, but no system that can achieve this exists. Therefore, a new system that can propose housing that is optimized to the needs of users is needed.

[0709] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0710] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as the local childcare support system, the educational environment, and the number of parks, a means for analyzing the collected information using a data analysis tool and extracting the conditions for a home that best suits the user's needs, a means for proposing a home that best suits the user's needs using a generative AI model, and a means for presenting the proposed content to the user. This makes it possible to propose a home that is optimized for the user's needs.

[0711] "User needs" refers to information that indicates the conditions and desires required by users.

[0712] The "local child-rearing support system" is a general term for public support and services related to child-rearing provided in a specific area.

[0713] "Educational environment" refers to the condition of schools, educational facilities, education-related services and infrastructure in a particular area.

[0714] "Number of parks" refers to the total number of parks that exist within a particular area.

[0715] "Data analysis tools" is a general term for software and programs used to organize and analyze collected data and extract meaningful information.

[0716] A "generative AI model" is a general term for algorithms and programs that use artificial intelligence to generate an appropriate output for a specific input.

[0717] "Proposal Content" refers to specific proposed information about a home created by the generative AI model based on the user's needs.

[0718] The present invention is a system for proposing an optimal residence based on the needs of a user. A specific embodiment of this system is described below.

[0719] First, the user inputs their needs using the terminal. For example, the user inputs, "I'm in the child-rearing generation and want to live in Tokyo." This information is sent from the terminal to the server.

[0720] Next, the server collects information about the childcare support system, educational environment, number of parks, etc., in the area desired by the user. To do this, a web scraping tool (e.g. BeautifulSoup) or an API (e.g. Google Places API) is used. For example, the server uses BeautifulSoup to scrape information about the childcare support system from the official Tokyo Metropolitan Government website, and obtains the number of parks using Google Places API.

[0721] The collected information is analyzed by the server using data analysis tools (e.g., Pandas, NumPy). The server converts the collected data into a data frame and scores it based on the level of support for childcare and the number of parks.

[0722] The server then uses a generative AI model (e.g. GPT-4) to suggest the best home for the user’s needs. It does this by inputting a prompt into the generative AI model. For example, the following prompt can be used:

[0723] Please suggest a suitable home in Tokyo for a child-rearing generation. Please consider the following conditions:

[0724] Childcare support system is well established

[0725] Good educational environment

[0726] There are many parks

[0727] The generative AI model generates suggestions based on this prompt.

[0728] Finally, the server sends the generated housing proposal to the device, and the device displays the proposal to the user. For example, the device may display on the user's screen, "The best area for raising children in Tokyo is ____ ward. There are many parks here, and the childcare support system is also well developed."

[0729] In this way, the user can receive proposals for homes that are optimized to their needs. This system performs a series of processes to propose the optimal home based on the user's needs, making it possible to provide the ideal home for the user.

[0730] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0731] Step 1:

[0732] Entering user information

[0733] The user uses the terminal to input his / her needs. For example, the user may input "I am of child-rearing age and would like to live in Tokyo."

[0734] Input: User needs (e.g. "child-rearing generation", "Tokyo area")

[0735] Output: User needs information is sent from the terminal to the server.

[0736] Specific operation: The user enters information on the screen of a smartphone or PC and presses the send button.

[0737] Step 2:

[0738] Gathering local information

[0739] The server collects information such as the child-rearing support system, educational environment, and number of parks in the user's desired area.

[0740] Input: User's needs information (e.g. "Tokyo")

[0741] Output: Information on local childcare support systems, educational environment, number of parks, etc.

[0742] Specific operation: The server uses a web scraping tool (e.g. BeautifulSoup) to scrape information about child-rearing support systems from the Tokyo Metropolitan Government's official website, and uses an API (e.g. Google Places API) to obtain the number of parks.

[0743] Step 3:

[0744] Data analysis and processing

[0745] The server analyzes the collected regional information using data analysis tools (e.g., Pandas, NumPy).

[0746] Input: Collected local information (e.g. childcare support system, educational environment, number of parks)

[0747] Output: The best living conditions for your needs

[0748] Specific operation: The server uses Pandas to convert the collected data into a data frame, and then performs scoring based on the comprehensiveness of the child-rearing support system and the number of parks.

[0749] Step 4:

[0750] Home proposal generation

[0751] The server uses a generative AI model (e.g. GPT-4) to suggest homes that best fit the user's needs.

[0752] Input: User needs information, analyzed regional information

[0753] Output: Housing proposals based on generative AI models

[0754] Specific operation: The server inputs the following prompt sentence into the generative AI model:

[0755] Please suggest a suitable home in Tokyo for a child-rearing generation. Please consider the following conditions:

[0756] Childcare support system is well established

[0757] Good educational environment

[0758] There are many parks

[0759] A generative AI model generates the suggestions.

[0760] Step 5:

[0761] Presenting the results

[0762] The server transmits the generated housing proposal to the terminal.

[0763] Input: Home proposals based on generative AI models

[0764] Output: Housing proposals presented to the user

[0765] Specific operation: The server sends the suggestions obtained from the generative AI model to the device, and the device displays on the user's screen, "The best area in Tokyo for raising children is Ward XX. There are many parks here, and there is an extensive child-rearing support system."

[0766] (Application example 2)

[0767] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[0768] Conventional housing suggestion systems often do not provide suggestions that are fully optimized to meet the needs of users. In particular, for users of child-rearing age, there is a lack of housing suggestions that take into account information such as the local child-rearing support system, educational environment, and number of parks. This makes it difficult for users to find the home that is truly ideal for them.

[0769] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0770] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means for inputting that the user is of child-rearing age, a means for collecting information such as the local child-rearing support system, the educational environment, and the number of parks, a means for generating a home suitable for raising children based on the collected information, and a means for proposing the generated home to the user. This makes it possible to propose a home optimized to the user's needs.

[0771] "User needs" refers to the requirements and demands of users.

[0772] "Social security" refers to systems such as welfare, medical care, and pensions provided by the government and public institutions.

[0773] "Running costs" are the ongoing expenses required to maintain a home.

[0774] "Environment" refers to the natural and social conditions surrounding the home.

[0775] An "AI means" is a method or device that uses artificial intelligence to process information and achieve a specific purpose.

[0776] The "child-rearing generation" refers to people of the age group who are raising children.

[0777] A "childcare support system" refers to public services and systems provided to support childcare.

[0778] The "educational environment" refers to the facilities and surrounding conditions in which children learn.

[0779] "Number of parks" refers to the number of parks that exist within a particular area.

[0780] "Housing" refers to the house where people live and the surrounding environment.

[0781] A "suggestion" is the act of presenting the best option based on a specific purpose or condition.

[0782] A system for implementing this invention includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the environment, etc., AI means for generating an ideal home based on the collected information, means for inputting that the user is of child-rearing age, means for collecting information such as the local child-rearing support system, educational environment, and number of parks, means for generating a home suitable for raising children based on the collected information, and means for proposing the generated home to the user.

[0783] Hardware and Software Used

[0784] Hardware: Smartphone (iOS or Android)

[0785] Software: Python, TensorFlow (to generate AI models), Google Maps API (to collect local information), Firebase (database)

[0786] Data processing and calculation

[0787] Entering user information

[0788] Users log in to a smartphone application and enter information about themselves as parents. For example, they might enter, "I have two children, ages 3 and 5."

[0789] Gathering local information

[0790] The server uses the Google Maps API to collect information such as the childcare support system, educational environment, and number of parks in the area where the user lives. For example, "collect childcare support system, educational environment, and number of parks in Shibuya Ward, Tokyo."

[0791] Creating homes using AI models

[0792] The server uses TensorFlow to generate housing suitable for raising children based on the collected local information. For example, it identifies areas in Shibuya Ward with a robust childcare support system and suggests optimal housing.

[0793] Suggestions for users

[0794] The server uses the data stored in Firebase to suggest the best place to live for the user. For example, it might suggest, "The Yoyogi area of ​​Shibuya Ward is a good place to raise children. We recommend the following properties."

[0795] Examples and prompts

[0796] Examples

[0797] A user logs into the app and enters, "I have two children, ages 3 and 5."

[0798] The app uses the Google Maps API to collect information on child-rearing support systems, educational environments, and the number of parks in Shibuya Ward, Tokyo.

[0799] Use TensorFlow to determine whether the Yoyogi area of ​​Shibuya Ward is suitable for raising children.

[0800] Based on the data stored in Firebase, properties in the Yoyogi area are suggested to users.

[0801] Examples of prompt statements

[0802] Please enter that you are of child-rearing age. Next, we will collect information about the area you live in and let the AI ​​generate the best home for you. For example, please enter "I have two children, ages 3 and 5."

[0803] In this way, users are presented with homes that are optimized to their needs, allowing them to truly find their ideal home.

[0804] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0805] Step 1:

[0806] Users log into a smartphone application and enter that they are of child-rearing age.

[0807] Input: User information (e.g. "I have two children. They are 3 and 5 years old.")

[0808] Output: The user information is sent to the server.

[0809] Specific actions: The user enters information about the parenting generation into the app's input form and presses the submit button.

[0810] Step 2:

[0811] The server uses the Google Maps API to collect information such as child care support systems, educational environments, and the number of parks in the user's area.

[0812] Input: Area information where the user lives (e.g. Shibuya-ku, Tokyo)

[0813] Output: Information such as the local childcare support system, educational environment, and number of parks is stored on the server.

[0814] Specific operation: The server sends a request to the Google Maps API to obtain information such as the child care support system, educational environment, and number of parks in the specified area.

[0815] Step 3:

[0816] The server uses TensorFlow to generate housing suitable for raising children based on the collected local information.

[0817] Input: Local information (childcare support system, educational environment, number of parks, etc.)

[0818] Output: Proposal data for housing suitable for raising children

[0819] Specific operation: The server runs the TensorFlow model and uses the collected local information as input to generate housing suitable for raising children.

[0820] Step 4:

[0821] The server uses the data stored in Firebase to suggest the most suitable home for the user.

[0822] Input: Generated housing proposal data

[0823] Output: Home information suggested to the user

[0824] What it does: The server retrieves the recommendation data from Firebase and displays the best homes for the user through the application.

[0825] Step 5:

[0826] The user reviews the proposed home information and views detailed information.

[0827] Input: Proposed Home Information

[0828] Output: Show detailed information

[0829] Specific operation: The user taps on the suggested home information within the application and is redirected to a screen where they can view more detailed information.

[0830] In this way, users are presented with homes that are optimized to their needs, allowing them to truly find their ideal home.

[0831] In addition, an emotion engine that estimates the emotion of the user may be further combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0832] "Example 1"

[0833] In one embodiment of the present invention, a system is provided in which the means for collecting user needs includes an emotion engine that recognizes the user's emotions. This system is capable of grasping user needs more precisely by taking into account not only the user's behavior history and input information, but also the user's emotions. The emotion engine analyzes the user's emotions from facial expressions, tone of voice, and text input, and treats the information as part of the user's needs.

[0834] "Example 2"

[0835] As a concrete example, let's say a user is looking for a newly built detached house. The user inputs information into the system, such as their family composition, budget, and desired area. Furthermore, the emotion engine can sense from the user's tone of voice, facial expressions, and text input that the user places importance on a sense of security. Based on this information, the AI ​​will suggest properties in areas with good safety and educational environments. This makes it possible to suggest properties that meet not only the user's explicit needs, but also their emotional needs.

[0836] The process flow of each embodiment will be described below.

[0837] "Example 1"

[0838] Step 1: The user accesses the system and enters the necessary information (family composition, budget, desired area, etc.).

[0839] Step 2: The emotion engine analyzes the user's emotions from their tone of voice, facial expressions, and text input.

[0840] Step 3: Treat the analyzed emotional information as part of user needs.

[0841] Step 4: Based on the information and emotional information collected by the AI, the ideal home is suggested to the user.

[0842] "Example 2"

[0843] Step 1: The user enters information into the system that they are looking for a new home. Step 2: The emotion engine senses from the user's tone of voice, facial expression, and text input that the user values ​​a sense of security.

[0844] Step 3: Based on the information collected by the AI ​​and the emotional information it senses, it recommends properties in areas with good safety and educational environments.

[0845] Example 1

[0846] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0847] Conventional housing recommendation systems did not adequately collect user needs, making it difficult to make precise recommendations that took into account the user's emotions and behavioral history. In addition, they were unable to comprehensively collect information on social security, running costs, and the environment and consider them in an integrated manner, making it difficult to recommend the optimal home for the user. This led to issues such as low user satisfaction and the time and effort required to find the ideal home.

[0848] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0849] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means including an emotion engine for recognizing the user's emotions, a means for comprehensively considering the collected user needs, behavioral history, emotion data, running costs and environmental information, and a means for proposing an optimal home using a generative AI model. This makes it possible to grasp precise user needs taking into account the user's emotions and behavioral history, and to propose an optimal home that comprehensively takes into account social security, running costs and environmental information.

[0850] "User needs" refers to the hopes, requests, and conditions that users have regarding their home.

[0851] "Running costs" refers to ongoing expenses related to housing, such as social security, taxes, utility bills, etc.

[0852] "Environmental information" refers to information about the surrounding environment of a home, such as transportation access, surrounding facilities, public safety, and the natural environment.

[0853] "AI means" refers to a system that uses artificial intelligence technology to analyze data and generate the optimal home.

[0854] An "emotion engine" is a system that analyzes emotions from a user's facial expressions, tone of voice, and text input, and treats that information as part of the user's needs.

[0855] "Behavioral history" refers to data such as a user's past search history and browsing history.

[0856] A "generative AI model" is a model that uses machine learning algorithms to comprehensively consider user needs and collected information to propose the most suitable home.

[0857] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0858] This invention is a system that collects user needs, comprehensively collects running costs and environmental information, including social security, and creates an ideal home based on the collected information. A specific embodiment of this system will be described below.

[0859] Gathering user needs

[0860] A user logs into the system and inputs their housing requirements, including specific requirements such as rent, location, layout, and whether pets are allowed. The terminal transmits the user's input information to the server in real time. In addition, the server retrieves the user's past search and browsing history from a database and stores them together with the current requirements. Using an emotion engine, the system analyzes emotions from the user's facial expressions, tone of voice, and text input, and treats them as part of the user's needs.

[0861] Collection of running costs and environmental information

[0862] The server accesses public databases and automatically collects information on social security, taxes, utility fees, etc. for each region. It also scrapes and collects property information from real estate sites on the Internet. This makes it possible to comprehensively collect property information that matches the user's desired conditions.

[0863] Creating the ideal home

[0864] The server comprehensively considers the collected user needs, behavioral history, emotional data, running costs, and environmental information. Using a generative AI model, this data is input to generate the optimal home. For example, if the user prioritizes "a quiet environment and a park nearby," properties that meet these conditions will be selected as a priority. The generated home proposals are presented to the user by the server.

[0865] Examples

[0866] For example, let's say a user wants a property in Tokyo with a rent of less than 100,000 yen, pets allowed, and within a 10-minute walk from the station. In this case, the system will process as follows:

[0867] 1. The user enters the desired conditions into the system.

[0868] 2. The server collects property information for Tokyo from government statistical databases and real estate websites.

[0869] 3. The emotion engine analyzes the user's facial expressions and tone of voice when typing to identify the conditions that the user particularly values.

[0870] 4. Based on the collected information, the generative AI model suggests the most suitable properties.

[0871] Examples of prompt statements

[0872] "I am looking for a property in Tokyo that is under 100,000 yen in rent, allows pets, and is within a 10-minute walk from the station. I am particularly looking for a quiet environment and a park nearby."

[0873] By inputting this prompt into the generative AI model, properties that match the user's preferences are suggested.

[0874] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0875] Step 1:

[0876] A user logs into the system and inputs the desired conditions for a home.

[0877] Input: User's desired conditions (e.g. rent, location, layout, pets allowed, etc.)

[0878] Output: User's desired conditions data

[0879] Specific operation: The user enters the user name and password on the login screen and clicks the Login button. After that, the user enters the desired conditions in the input form and clicks the Send button.

[0880] Step 2:

[0881] The terminal transmits the user's input information to the server in real time.

[0882] Input: User's desired conditions data

[0883] Output: The desired conditions data sent to the server

[0884] Specific operation: The terminal transmits the desired conditions entered by the user to the server in real time. For example, conditions such as "rent less than 100,000 yen, in Tokyo, pets allowed, within 10 minutes' walk from the station" are transmitted.

[0885] Step 3:

[0886] The server retrieves the user's past search history and browsing history from a database and stores them together with the user's current desired conditions.

[0887] Input: User's desired conditions data, past search history and browsing history

[0888] Output: Consolidated user needs data

[0889] Specific operation: The server retrieves the user's past search history and browsing history from the database, integrates it with the current desired conditions, and saves it. For example, it retrieves information about properties searched for in the past and compares it with the current desired conditions.

[0890] Step 4:

[0891] The device uses an emotion engine to analyze the user's facial expressions and tone of voice, and transmits the emotion data to the server.

[0892] Input: User facial expressions, tone of voice, text input

[0893] Output: Emotion data

[0894] Specific operation: The device analyzes the user's facial expressions and tone of voice using an emotion engine, and sends emotional data to the server to identify the conditions that the user places special importance on. For example, if the user places importance on a "quiet environment," the device sends that information.

[0895] Step 5:

[0896] The server accesses public databases and automatically collects information such as social security, taxes, and utility fees for each region.

[0897] Input: Public database

[0898] Output: Social security, tax, utility fee information by region

[0899] Specific operation: The server accesses a government statistical database and collects information on social security, taxes, utility fees, etc. by region. For example, it obtains the average rent and living expenses in Tokyo.

[0900] Step 6:

[0901] The server scrapes and collects property information from real estate sites on the Internet.

[0902] Input: Real estate website on the Internet

[0903] Output:Property information

[0904] Specific operation: The server scrapes and collects property information from real estate sites on the Internet. For example, it obtains property information within Tokyo.

[0905] Step 7:

[0906] The server stores the collected information in a database and compares it with the user's desired conditions.

[0907] Input: Collected social security, taxes, utilities, property information

[0908] Output: Matched property information

[0909] Specific operation: The server saves the collected information in a database and compares it with the user's desired conditions. For example, it filters properties with rent of less than 100,000 yen, pet-friendly properties, and properties within a 10-minute walk from the station.

[0910] Step 8:

[0911] The server comprehensively considers collected user needs, behavioral history, emotional data, running costs, and environmental information.

[0912] Input: User needs, behavioral history, emotional data, running costs, environmental information

[0913] Output: Consolidated data

[0914] Specific operation: The server comprehensively considers the collected user needs, behavioral history, emotional data, running costs, and environmental information, and integrates the data.

[0915] Step 9:

[0916] The server inputs this data into a generative AI model to generate the optimal home.

[0917] Input: Consolidated data

[0918] Output: Optimal home proposal

[0919] Specific operation: The server inputs the integrated data into the generative AI model and generates the optimal home. For example, if the user prioritizes "a quiet environment and a park nearby," the server will prioritize properties that meet those conditions.

[0920] Step 10:

[0921] The server presents the generated housing proposals to the user.

[0922] Input: Best Home Proposal

[0923] Output: Home proposals presented to the user

[0924] Specific operation: The server presents the generated housing proposals to the user. The user can check the detailed information of the proposed properties and select the property they like.

[0925] (Application example 1)

[0926] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0927] Conventional housing proposal systems were unable to fully reflect the needs of users, and it was difficult to comprehensively collect information on social security, running costs, and the environment. As a result, it was difficult to propose the optimal home for the user. In addition, there was a problem of low user satisfaction because proposals could not be made that took the user's feelings into account.

[0928] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0929] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means including an emotion engine for analyzing user emotions, a means for automatically collecting information from public databases and the Internet, a means for comprehensively considering user needs and the collected information using a machine learning algorithm and proposing the most suitable property, and a means including a smartphone application. This makes it possible to propose the most suitable home considering the user's needs and emotions.

[0930] "Means of collecting user needs" refers to means for collecting the user's desired conditions and requests, and includes the user's input information and behavioral history.

[0931] "Means of comprehensively collecting information on running costs, including social security, and the environment" refers to means for comprehensively collecting information on social security, running costs, the environment, etc. related to housing, and includes systems that automatically collect information from public databases and the Internet.

[0932] An "AI method for generating an ideal home" is a method that uses artificial intelligence technology to generate the optimal home for the user based on collected information.

[0933] "Means including an emotion engine for analyzing user emotions" refers to means for analyzing emotions from a user's facial expressions, tone of voice, and text input, and treating the information as part of the user's needs.

[0934] "Means of automatically collecting information from public databases and the Internet" refers to means of automatically collecting information on social security, running costs, environmental information, etc. from public databases and the Internet.

[0935] "A means for comprehensively considering user needs and collected information using a machine learning algorithm to suggest the most suitable property" refers to a means for comprehensively analyzing user needs and collected information using machine learning technology to suggest the most suitable property to the user.

[0936] "Means including smartphone applications" refer to means including applications that users use to search for their ideal home via their smartphones.

[0937] This invention is a system that collects user needs, comprehensively collects information on social security, running costs, environmental information, etc., and creates an ideal home based on that information. A specific embodiment of this system is described below.

[0938] System Configuration

[0939] The system consists of the following main components:

[0940] 1. How to gather user needs:

[0941] Users input their desired conditions (e.g. budget, floor plan, location, etc.) through a smartphone application.

[0942] Record user activity (e.g. properties viewed, properties saved, etc.).

[0943] The emotion engine analyzes emotions from the user's facial expressions, tone of voice, and text input.

[0944] 2. Comprehensive collection of information:

[0945] Use a system that automatically collects information from public databases and the Internet.

[0946] The information to be collected includes social security, running costs, environmental information, etc.

[0947] 3. AI methods to generate ideal homes:

[0948] Using machine learning algorithms, the system comprehensively considers user needs and collected information to suggest the most suitable properties.

[0949] Program processing explanation

[0950] The server collects user input information, behavioral history, and emotion analysis results from an emotion engine. This allows the system to understand the user's needs in detail. It then automatically collects information from public databases and the Internet to comprehensively obtain information on social security, running costs, the environment, and more.

[0951] Based on this information, a machine learning algorithm is used to comprehensively analyze the user's needs and the collected information, and the system proposes the most suitable property. Specifically, the system considers the user's desired conditions and the results of sentiment analysis to generate the most suitable home.

[0952] Hardware and Software Used

[0953] Hardware:

[0954] Smartphone: A device that allows users to input desired conditions and perform sentiment analysis.

[0955] Server: A central processing unit for collecting, analyzing, and storing data.

[0956] software:

[0957] Emotion engine: Software for analyzing emotions from a user's facial expressions, tone of voice, and text input.

[0958] Machine learning algorithm: An algorithm that comprehensively analyzes user needs and collected information to suggest the most suitable properties.

[0959] Public database access system: A system for collecting information on social security, running costs, and the environment.

[0960] Examples

[0961] For example, if a user types in, "I'm looking for a quiet location with good schools nearby," the emotion engine will analyze the "sense of security" from the user's text and suggest the most suitable property along with budget and location information.

[0962] Examples of prompt statements

[0963] Design an application that, when searching for an ideal home, inputs the desired conditions (budget, layout, location, etc.), analyzes the user's emotions using an emotion engine, and suggests the most suitable property. Collect running costs and environmental information from public databases, and use a machine learning model to make suggestions by taking into consideration the user's needs and the collected information in an integrated manner.

[0964] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0965] Step 1:

[0966] The user inputs the desired conditions through a smartphone application.

[0967] Input: User's desired conditions (e.g. budget, layout, location, etc.)

[0968] Output: User's desired conditions data

[0969] Specific operation: The user enters the desired conditions into the application's input form and presses the submit button. The application sends the entered data to the server.

[0970] Step 2:

[0971] The server records the user's behavior.

[0972] Input: User behavior history (e.g. properties viewed, properties saved, etc.)

[0973] Output: User behavior history data

[0974] How it works: The application monitors user actions and sends information about viewed and saved properties to the server, which then stores the data in a database.

[0975] Step 3:

[0976] The server uses an emotion engine to analyze the user's emotions.

[0977] Input: User facial expressions, tone of voice, text input

[0978] Output: User sentiment data

[0979] How it works: The application captures the user's facial expressions and tone of voice with a camera and microphone, analyzes the text input, and sends this data to the emotion engine, which returns the analysis results to the server.

[0980] Step 4:

[0981] The server automatically collects information from public databases and the Internet.

[0982] Input: Public databases and information from the internet

[0983] Output: Social security, running costs, environmental information data

[0984] Specific operation: The server periodically crawls public databases and information on the Internet, collects the necessary data, and stores it in a database.

[0985] Step 5:

[0986] The server uses machine learning algorithms to comprehensively analyze user needs and collected information.

[0987] Input: User desired conditions data, behavioral history data, emotion data, social security, running costs, environmental information data

[0988] Output: Optimal property proposal data

[0989] How it works: The server runs a machine learning algorithm to comprehensively analyze the input data. The algorithm takes into account the user's needs and the collected information to suggest the best properties.

[0990] Step 6:

[0991] The server notifies the user of the best property suggestions.

[0992] Input: Data for optimal property proposals

[0993] Output:Notification to the user

[0994] Specific operation: The server sends the optimal property recommendation data to the smartphone application, and the application displays a notification to the user.

[0995] Example 2

[0996] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0997] Conventional housing recommendation systems mainly make suggestions based on the explicit needs of users, and do not take into account the emotional needs of users or detailed information about the area. This makes it difficult for users to find the ideal home.

[0998] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0999] In this invention, the server includes a means for collecting user needs, a means for performing emotion analysis, a means for collecting information such as the local childcare support system, the educational environment, and the number of parks, an artificial intelligence means for generating an ideal home based on the collected information, and a means for proposing the generated home to the user. This makes it possible to propose an optimal home that takes into account not only the explicit needs of the user but also emotional needs and detailed information about the area.

[1000] "User needs" refers to information that indicates the conditions and desires required by users.

[1001] "Emotion analysis" is a technology that analyzes emotions from a user's tone of voice, facial expressions, text input, etc.

[1002] The "local child-rearing support system" is a general term for child-rearing support and services provided in a specific area.

[1003] "Educational environment" is a general term for educational facilities and education-related environments in a particular area.

[1004] "Number of parks" is the total number of parks in a particular area.

[1005] "Artificial intelligence means" refers to artificial intelligence technology for generating an ideal home based on collected information.

[1006] "Means of proposing a home" refers to technology for presenting the generated ideal home to the user.

[1007] The present invention is a system for proposing an optimal residence based on the needs of a user. A specific embodiment of this system will be described below.

[1008] First, the user uses the terminal to input information such as family composition, budget, desired area, etc. For example, the user inputs information such as "Family composition is four people, budget is within 50 million yen, and desired area is within Tokyo."

[1009] Next, the device performs emotion analysis. While the user is entering information into the input form, the camera and microphone are used to record the user's facial expressions and tone of voice. For emotion analysis, a common emotion analysis API is used. For example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API is used to analyze the importance of the user's sense of security.

[1010] The server then stores the information entered by the user and the results of the sentiment analysis in a database, allowing the necessary information to be efficiently retrieved for subsequent processing.

[1011] Next, the server collects related information from the Internet. Specifically, it uses Google Maps API and the government's open data API to collect information such as the childcare support system, educational environment, and number of parks in the area where the user lives. For example, it obtains information such as "Number of parks in Tokyo: 50, number of public schools: 30, number of childcare support centers: 10."

[1012] The server uses a generative AI model based on the collected data and the results of sentiment analysis to generate properties that are optimal for the user. For example, OpenAI's GPT-4 is used for the generative AI model. This generative AI model proposes properties that meet the user's explicit and emotional needs.

[1013] Finally, the server proposes the generated property information to the user, who can then check the details of "a newly built detached house in a safe area of ​​Tokyo with a good educational environment" on his / her terminal.

[1014] As a concrete example, consider the case where a user is looking for a newly built detached house. The user inputs information into the system, such as family composition, budget, and desired area. Furthermore, the emotion engine senses from the user's tone of voice, facial expression, and text input that the user places importance on a sense of security. Based on this information, the AI ​​suggests properties in areas with good safety and educational environments. This makes it possible to suggest properties that meet not only the user's explicit needs, but also their emotional needs.

[1015] Examples of prompts include:

[1016] "We have a family of four and our budget is within 50 million yen. We would like to live in a location within Tokyo. We value a sense of security. We are looking for a newly built detached house in an area with a good childcare support system and educational environment."

[1017] In this way, the present invention can propose optimal housing that meets the diverse needs of users.

[1018] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1019] Step 1:

[1020] The user enters information

[1021] The user inputs information such as family composition, budget, and desired area into the input form on the terminal. For example, the user inputs "Family composition is 4 people, budget is 50 million yen or less, and desired area is within Tokyo." The input information is sent from the terminal to the server. The input data is text data such as family composition, budget, and desired area.

[1022] Step 2:

[1023] The device performs emotion analysis

[1024] The device uses a camera and microphone to record the user's facial expressions and tone of voice while the user is entering information into an input form. A common emotion analysis API is used for emotion analysis. For example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API is used to analyze whether the user values ​​a sense of security. The input data is the user's facial expressions and tone of voice, and the output data is the user's emotional state (e.g., emphasis on a sense of security).

[1025] Step 3:

[1026] The server stores the user's input in a database

[1027] The server stores the information entered by the user and the results of the emotion analysis in a database. This allows the necessary information to be efficiently retrieved for subsequent processing. The input data is text data such as family composition, budget, desired area, and emotional state, and the output data is the information stored in the database.

[1028] Step 4:

[1029] The server collects relevant information from the Internet.

[1030] The server uses Google Maps API and the government's open data API to collect information such as the child-rearing support system, educational environment, and number of parks in the area where the user lives. For example, it obtains information such as "Number of parks in Tokyo: 50, number of public schools: 30, number of child-rearing support centers: 10." The input data is the user's desired area, and the output data is information such as the local child-rearing support system, educational environment, and number of parks.

[1031] Step 5:

[1032] The server generates properties using generative AI models

[1033] The server uses a generative AI model (e.g., OpenAI's GPT-4) based on the collected data and the results of sentiment analysis to generate the best property for the user. The generative AI model proposes properties that meet the user's explicit and emotional needs. The input data are the user's needs, emotional state, and area information, and the output data is the proposed property information.

[1034] Step 6:

[1035] Propose server-generated properties to users

[1036] The server proposes the property information generated by the generative AI model to the user. The user can check detailed information on "a newly built detached house in a safe area of ​​Tokyo with a good educational environment" on the terminal. The input data is the generated property information, and the output data is the property information presented to the user.

[1037] (Application example 2)

[1038] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1039] Conventional real estate property recommendation systems were able to make suggestions based on the user's explicit needs, but were unable to make suggestions that took into account the user's emotional needs. This made it difficult for users to find properties that truly satisfied them. In addition, there was a lack of systems that comprehensively collected information such as the local childcare support system, educational environment, and number of parks, and suggested the most suitable home for users. This made it difficult for users, especially those of child-rearing age, to find the ideal home.

[1040] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1041] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information on running costs including social security and the like, the environment, and the like, an AI means for generating an ideal home based on the collected information, a means for analyzing the user's emotions, a means for proposing properties based on the user's emotional needs, and a means for displaying detailed information on the proposed properties. This makes it possible to propose properties that simultaneously satisfy the user's explicit needs and emotional needs.

[1042] "Means of collecting user needs" refers to the interface and data collection functions that allow users to input their desired conditions and requests.

[1043] "Means of comprehensively collecting information on running costs, including social security, and the environment" refers to a data collection system for comprehensively collecting information on the local social security system, living expenses, educational environment, number of parks, etc.

[1044] "AI means for generating an ideal home" refers to an artificial intelligence algorithm that uses collected information to generate a home that best suits the user's needs.

[1045] "Means of analyzing user emotions" refers to an emotion analysis engine for analyzing emotions from the user's tone of voice, facial expressions, text input, etc.

[1046] "Means for suggesting properties based on a user's emotional needs" refers to a system for suggesting properties that meet a user's emotional needs based on the results of sentiment analysis.

[1047] "Means for displaying detailed information about the proposed property" means a display or interface for visually providing detailed information about the proposed property to a user.

[1048] An embodiment of the present invention will be described below. The system described below includes AI means for collecting user needs, comprehensively collecting information on running costs including social security and the environment, and generating an ideal home based on the collected information. It also includes means for analyzing the user's emotions, proposing properties based on the emotional needs, and displaying detailed information on the proposed properties.

[1049] System Configuration

[1050] 1. Hardware and Software Use

[1051] Hardware: Smartphones, smart glasses

[1052] Software: Sentiment analysis engines (e.g. Affectiva), data collection APIs (e.g. Google Places API), generative AI models (e.g. GPT-4)

[1053] Data processing and calculation

[1054] 1. Gathering user needs

[1055] Users input information such as their family composition, budget, and desired area via their smartphone or smart glasses.

[1056] The emotion analysis engine analyzes emotions from the user's tone of voice, facial expressions, and text input.

[1057] 2. Collecting local information

[1058] Using the Google Places API, we collect information such as child care support systems, educational environments, and the number of parks in the area where the user lives.

[1059] 3. Creating the ideal home

[1060] Based on the collected data, a generative AI model (GPT-4) is used to generate a home that is suitable for raising children.

[1061] 4. Property proposal

[1062] Suggest properties that meet users' explicit and emotional needs.

[1063] Detailed information about the proposed property will be displayed on the display of a smartphone or smart glasses.

[1064] Examples

[1065] Example prompt:

[1066] User information: Family size = 4, Budget = 50 million yen, Preferred area = Tokyo

[1067] Sentiment analysis results: Emphasis on feeling safe

[1068] Local information: Childcare support system = comprehensive, educational environment = good, number of parks = many

[1069] Inputs to the generative AI model:

[1070] A user with a family of four and a budget of 50 million yen is looking for a property in Tokyo that prioritizes peace of mind. Please suggest a property in an area with a good child-rearing support system, a good educational environment, and many parks.

[1071] In this way, it becomes possible to propose properties that meet the user's explicit and emotional needs at the same time.

[1072] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1073] Step 1:

[1074] Users input information such as family composition, budget, and desired area through their smartphone or smart glasses. The input information is sent to the server, which then stores the information in a database.

[1075] Input: User information such as family composition, budget, desired area, etc.

[1076] Output: User information stored in the database

[1077] Step 2:

[1078] The server uses an emotion analysis engine to analyze the user's tone of voice, facial expressions, and text input to determine their emotions. The analysis results are stored in a database as the user's emotional needs.

[1079] Input: User tone of voice, facial expressions, text input

[1080] Output: Sentiment analysis results (e.g., emphasis on feeling safe)

[1081] Step 3:

[1082] The server uses the Google Places API to collect information about the childcare support system, educational environment, number of parks, etc. in the area where the user lives. The collected information is stored in a database.

[1083] Input: The user's preferred region

[1084] Output: Information on local childcare support systems, educational environment, number of parks, etc.

[1085] Step 4:

[1086] The server uses a generative AI model (GPT-4) based on collected user information, emotion analysis results, and regional information to generate homes that are suitable for raising children. The generated home information is stored in a database.

[1087] Input: User information, sentiment analysis results, region information

[1088] Output: Generated ideal home information

[1089] Step 5:

[1090] Based on the generated home information, the server suggests properties that meet the user's explicit and emotional needs, and the details of the suggested properties are displayed on the display of the smartphone or smart glasses.

[1091] Input: Generated ideal home information

[1092] Output: Details of the proposed property

[1093] Step 6:

[1094] Users check detailed property information displayed on their smartphone or smart glasses displays and select the property they are interested in. The information on the selected property is sent to the server and stored in a database.

[1095] Input: Proposed property details

[1096] Output: Information about the selected property

[1097] In this way, it becomes possible to propose properties that meet the user's explicit and emotional needs at the same time.

[1098] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1099] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1100] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1101] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1102] [Third embodiment]

[1103] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1104] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1105] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[1106] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1107] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[1108] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1109] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1110] Fig. 6 shows an example of main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1111] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1112] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1113] In the headset type terminal 314, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1114] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1115] "Example 1"

[1116] The system of the present invention includes a means for collecting user needs, a means for comprehensively collecting information on running costs and the environment, including social security, and an AI means for generating an ideal home based on the collected information. As a means for collecting user needs, it is possible to use information input by the user or a user's behavior history. In addition, as a means for comprehensively collecting information on running costs and the environment, including social security, it is possible to use a system that automatically collects information from public databases and the Internet. And, as an AI means for generating an ideal home based on this information, it is possible to use a system that uses a machine learning algorithm to comprehensively consider the user needs and the collected information and propose an ideal home.

[1117] "Example 2"

[1118] As a specific example, information that the user is of child-rearing age is collected as a user need, and comprehensive information such as the child-rearing support system, educational environment, and number of parks in the area where the user lives is collected. Then, based on this information, AI generates homes with an environment suitable for raising children and suggests them to the user. In this way, users are suggested homes that are optimized for their needs, allowing them to find their truly ideal home.

[1119] The process flow of each embodiment will be described below.

[1120] "Example 1"

[1121] Step 1: Collect user needs using information input by the user and user behavioral history, etc.

[1122] Step 2: Using a system that automatically collects information from public databases and the internet, comprehensively collect information on running costs, including social security, and the environment. Step 3: Using a machine learning algorithm, the system will comprehensively consider user needs and the collected information to propose an ideal home.

[1123] "Example 2"

[1124] Step 1: Collect information about the user's child-rearing generation as a user need. Step 2: Collect comprehensive information about the child-rearing support system, educational environment, number of parks, etc. in the area where the user lives.

[1125] Step 3: Based on this information, the AI ​​will generate homes with an environment suitable for raising children and make suggestions to the user.

[1126] Example 1

[1127] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1128] Conventional housing proposal systems have difficulty in integrating user needs with running costs and environmental information, including social security, making it difficult to propose optimal housing to users. In addition, there was a lack of means to accurately grasp needs by utilizing the user's behavioral history, which led to a problem of reduced proposal accuracy.

[1129] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1130] In this invention, the server includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the like and the environment, artificial intelligence means for generating an ideal home based on the collected information, means for generating a prompt sentence based on the user needs and the collected information, means for inputting the generated prompt sentence into an artificial intelligence model and generating a proposal for the ideal home, and means for transmitting the generated proposal to the user. This makes it possible to comprehensively consider the user needs, running costs including social security and the like, and environmental information, and to propose an optimal home to the user with high accuracy.

[1131] "User needs" refers to the conditions and requests that users have regarding their desired home.

[1132] "Running costs" refer to ongoing expenses related to housing, such as social security fees, taxes, and utility bills.

[1133] "Environmental information" refers to information about the surrounding environment of the home, including transportation access and the presence and distance of facilities such as schools, hospitals, and supermarkets.

[1134] "Artificial intelligence means" refers to means that use machine learning algorithms and generative AI models to generate an ideal home based on user needs and collected information.

[1135] A "prompt" is a document that is used as input to a generative AI model and is a written description that integrates user needs and collected information.

[1136] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to generate suggestions for ideal homes based on input prompt sentences.

[1137] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1138] This invention is a system that collects user needs, comprehensively collects running costs and environmental information, including social security, and creates an ideal home based on this information. A specific embodiment of this system will be described below.

[1139] Gathering user needs

[1140] Users input their housing needs through the terminal. For example, they input information such as the desired layout, budget, and location. The terminal transmits the input information to the server in real time. The transmission uses the HTTPS protocol to ensure data security. The user's behavioral history (previously viewed property information and search history) is also collected and stored in a database.

[1141] Collection of running costs and environmental information

[1142] The server automatically collects information from public databases and the Internet. Specifically, it collects information on social security fees, taxes, utility charges, transportation access, and the surrounding environment (schools, hospitals, supermarkets, etc.). To do this, it uses web scraping technologies such as Python's BeautifulSoup and Scrapy, as well as RESTful APIs. The collected information is stored in a database.

[1143] Creating the ideal home

[1144] The server generates a prompt based on the user's needs and the information it has collected. For example, it might generate a prompt like this:

[1145] User needs:

[1146] Desired layout: 3LDK

[1147] Budget: 30 million yen

[1148] Location: Within 10 minutes walk from the station

[1149] Information collected:

[1150] Social security costs: 200,000 yen per year

[1151] Utility bills: 10,000 yen per month

[1152] Access: 8 minutes walk to the nearest station

[1153] Neighborhood: Near supermarkets, hospitals, and schools

[1154] Use this information to suggest your ideal home.

[1155] The server inputs this prompt into a generative AI model (e.g. GPT-4). The generative AI model generates suggestions for ideal housing based on the input prompt. For example, it generates specific suggestions such as, "I found a 3LDK property within my budget. It's an 8-minute walk from the nearest station, and there are supermarkets, hospitals, and schools in the surrounding area."

[1156] Submit a proposal

[1157] The server sends the generated proposal to the user, who can then review the proposal through the terminal and decide on the next action to take.

[1158] In this way, the system of the present invention is able to comprehensively consider user needs, running costs including social security, and environmental information, and to propose the most suitable home for the user with a high degree of accuracy.

[1159] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1160] Step 1: Gather user needs

[1161] 1.1 The user inputs their housing needs through the device. Specifically, they input information such as the desired layout, budget, location, etc. The input information is saved in a dedicated application on the device.

[1162] 1.2 The terminal transmits the input information to the server in real time using the HTTPS protocol to ensure data security.

[1163] 1.3 The server stores the received user needs in a database, so that the user's desired conditions are accumulated in the system.

[1164] Step 2: Collect user behavior history

[1165] 2.1 The server collects the user's behavioral history, specifically, the property information viewed in the past and search history.

[1166] 2.2 The server stores the collected behavioral history in a database, which allows the server to understand the user's preferences more accurately.

[1167] Step 3: Collect running costs and environmental information

[1168] 3.1 The server automatically collects information from public databases and the Internet, such as information on social security fees, taxes, utility fees, transportation access, and the surrounding environment (schools, hospitals, supermarkets, etc.).

[1169] 3.2 The server retrieves the required information using a web scraping technique such as Python's BeautifulSoup or Scrapy, or, if an API is provided, retrieves the data using a RESTful API.

[1170] 3.3 The server stores the collected information in a database, so that the latest running costs and environmental information are accumulated in the system.

[1171] Step 4: Generate a prompt

[1172] 4.1 The server generates a prompt based on the user's needs and the collected information. Specifically, the server combines the user's desired conditions with the collected running costs and environmental information to generate a prompt like the following:

[1173] User needs:

[1174] Desired layout: 3LDK

[1175] Budget: 30 million yen

[1176] Location: Within 10 minutes walk from the station

[1177] Information collected:

[1178] Social security costs: 200,000 yen per year

[1179] Utility bills: 10,000 yen per month

[1180] Access: 8 minutes walk to the nearest station

[1181] Neighborhood: Near supermarkets, hospitals, and schools

[1182] Use this information to suggest your ideal home.

[1183] 4.2 The server prepares the generated prompt sentence to be input to the generative AI model.

[1184] Step 5: Create your dream home

[1185] 5.1 The server inputs a prompt to a generative AI model (e.g., GPT-4). The generative AI model generates a proposal for an ideal home based on the input prompt.

[1186] 5.2 The generative AI model generates housing proposals that best fit the user's criteria. For example, it generates specific proposals such as, "I found a 3LDK property within my budget. It's an 8-minute walk from the nearest station, and there are supermarkets, hospitals, and schools nearby."

[1187] 5.3 The server stores the generated suggestions in a database.

[1188] Step 6: Submit your proposal

[1189] 6.1 The server sends the generated proposal to the user, either via email or via the notification feature of the application.

[1190] 6.2 The user confirms the proposal through the terminal and can decide the next action based on the proposal.

[1191] (Application example 1)

[1192] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1193] In today's housing selection process, users need to gather and compare a lot of information, but this process takes a lot of time and effort. It is not easy to find a home that is optimized for the user's needs. Furthermore, it is difficult to take into account important factors such as running costs and environmental information, making it difficult to find the ideal home. To solve these problems, a system is needed that can accurately gather the user's needs and propose the ideal home based on comprehensive information.

[1194] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1195] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information on running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means for collecting user needs based on user input information and behavior history, a means for automatically collecting running cost and environmental information from the Internet and public databases, a means for comprehensively considering user needs and the collected information using a machine learning algorithm and proposing an ideal home, and an application installed on a smartphone. This enables users to efficiently find an ideal home that is optimized for their needs.

[1196] "User needs" refer to the hopes and demands that users have regarding their homes.

[1197] "Running costs" are the ongoing expenses required to maintain a home.

[1198] "Environmental information" refers to information about the surrounding environment of a home, including, for example, transportation access, public safety, and the presence or absence of educational facilities.

[1199] "AI means" refers to a means that uses artificial intelligence to analyze data and make optimal suggestions.

[1200] A "machine learning algorithm" is an algorithm that learns patterns from data and makes predictions and classifications.

[1201] A "smartphone" is a type of mobile phone, a multi-function device that can connect to the Internet and install applications.

[1202] An "application" is software designed to provide a specific function or service.

[1203] A "public database" is a database provided by a government or public institution that contains highly reliable information.

[1204] "Behavioral history" is a record of a user's past actions and choices.

[1205] The "Internet" is a huge information and communications network that interconnects computer networks all over the world.

[1206] A system for implementing this invention includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the environment, AI means for generating an ideal home based on the collected information, means for collecting user needs based on user input information and behavioral history, means for automatically collecting running cost and environmental information from the Internet or public databases, means for comprehensively considering user needs and the collected information using a machine learning algorithm to propose an ideal home, and an application installed on a smartphone.

[1207] Program processing explanation

[1208] The server collects the needs and desired conditions entered by the user via their smartphone. These include the desired location, budget, size, and facilities. The server then automatically collects information about the running costs and environment of the specified location from the Internet and public databases. This information includes transportation access, public safety, and the availability of educational facilities.

[1209] The collected data is analyzed using a machine learning algorithm. Specifically, the data is preprocessed and the ideal home is predicted by comprehensively considering the user's needs and environmental information. For example, the machine learning algorithm used is Random Forest Regressor.

[1210] The application installed on the user's smartphone receives suggestions from the server and presents the user with their ideal home. The application makes optimized suggestions based on the information entered by the user and their behavioral history.

[1211] Examples

[1212] For example, if a user inputs, "I would like to live in Tokyo with a budget of 30 million yen, a space of 70 square meters, and facilities such as air conditioning and a balcony," the server will collect environmental information about Tokyo and suggest the ideal home based on the user's desired conditions.

[1213] Example prompt:

[1214] Please enter your desired location: Tokyo

[1215] Enter your budget: 3000

[1216] Enter your desired size: 70

[1217] Please enter the desired amenities (separated by commas): air conditioning, balcony

[1218] After entering this prompt, the application receives suggestions from the server and presents ideal homes to the user, allowing the user to efficiently find the ideal home that best suits their needs.

[1219] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1220] Step 1:

[1221] Users use their smartphones to input their needs, such as desired location, budget, size, and facilities.

[1222] Input: User needs (desired location, budget, size, facilities)

[1223] Output: User needs data

[1224] Specific operation: The user enters the desired conditions into the application's input form and presses the submit button.

[1225] Step 2:

[1226] The server receives user needs data and collects running costs and environmental information for the specified location from the Internet and public databases.

[1227] Input: User needs data

[1228] Output: Environmental information data

[1229] Specific operation: The server uses the API to obtain running costs and environmental information for the specified location.

[1230] Step 3:

[1231] The server preprocesses the collected user needs data and environmental information data.

[1232] Input: User needs data, environmental information data

[1233] Output: Preprocessed data

[1234] Specific operation: The server performs data cleaning, normalization, and feature engineering.

[1235] Step 4:

[1236] The server feeds the preprocessed data into a machine learning algorithm to predict the ideal home.

[1237] Input: Preprocessed data

[1238] Output: Proposal data for an ideal home

[1239] How it works: The server uses a machine learning model such as RandomForestRegressor to predict the ideal home.

[1240] Step 5:

[1241] The server sends suggested data for the ideal home to the smartphone.

[1242] Input: Ideal home proposal data

[1243] Output: Sending proposal data to a smartphone

[1244] Specific operation: The server sends the proposal data to the user's smartphone via the network.

[1245] Step 6:

[1246] The smartphone displays the received proposal data to the user.

[1247] Input: Proposal data

[1248] Output: What is displayed to the user

[1249] Specific operation: The smartphone application analyzes the proposal data and displays the ideal home for the user.

[1250] Example 2

[1251] Next, a second embodiment of the second form will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1252] Conventional housing proposal systems have difficulty in making proposals that are fully optimized to meet the needs of users. In particular, for users of child-rearing age, there is a demand for proposals based on comprehensive collection of information such as the local child-rearing support system, educational environment, and number of parks, but no system that can achieve this exists. Therefore, a new system that can propose housing that is optimized to the needs of users is needed.

[1253] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1254] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as the local childcare support system, the educational environment, and the number of parks, a means for analyzing the collected information using a data analysis tool and extracting the conditions for a home that best suits the user's needs, a means for proposing a home that best suits the user's needs using a generative AI model, and a means for presenting the proposed content to the user. This makes it possible to propose a home that is optimized for the user's needs.

[1255] "User needs" refers to information that indicates the conditions and desires required by users.

[1256] The "local child-rearing support system" is a general term for public support and services related to child-rearing provided in a specific area.

[1257] "Educational environment" refers to the condition of schools, educational facilities, education-related services and infrastructure in a particular area.

[1258] "Number of parks" refers to the total number of parks that exist within a particular area.

[1259] "Data analysis tools" is a general term for software and programs used to organize and analyze collected data and extract meaningful information.

[1260] A "generative AI model" is a general term for algorithms and programs that use artificial intelligence to generate an appropriate output for a specific input.

[1261] "Proposal Content" refers to specific proposed information about a home created by the generative AI model based on the user's needs.

[1262] The present invention is a system for proposing an optimal residence based on the needs of a user. A specific embodiment of this system is described below.

[1263] First, the user inputs their needs using the terminal. For example, the user inputs, "I'm in the child-rearing generation and want to live in Tokyo." This information is sent from the terminal to the server.

[1264] Next, the server collects information about the childcare support system, educational environment, number of parks, etc., in the area desired by the user. To do this, a web scraping tool (e.g. BeautifulSoup) or an API (e.g. Google Places API) is used. For example, the server uses BeautifulSoup to scrape information about the childcare support system from the official Tokyo Metropolitan Government website, and obtains the number of parks using Google Places API.

[1265] The collected information is analyzed by the server using data analysis tools (e.g., Pandas, NumPy). The server converts the collected data into a data frame and scores it based on the level of support for childcare and the number of parks.

[1266] The server then uses a generative AI model (e.g. GPT-4) to suggest the best home for the user’s needs. It does this by inputting a prompt into the generative AI model. For example, the following prompt can be used:

[1267] Please suggest a suitable home in Tokyo for a child-rearing generation. Please consider the following conditions:

[1268] Childcare support system is well established

[1269] Good educational environment

[1270] There are many parks

[1271] The generative AI model generates suggestions based on this prompt.

[1272] Finally, the server sends the generated housing proposal to the device, and the device displays the proposal to the user. For example, the device may display on the user's screen, "The best area for raising children in Tokyo is ____ ward. There are many parks here, and the childcare support system is also well developed."

[1273] In this way, the user can receive proposals for homes that are optimized to their needs. This system performs a series of processes to propose the optimal home based on the user's needs, making it possible to provide the ideal home for the user.

[1274] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1275] Step 1:

[1276] Entering user information

[1277] The user uses the terminal to input his / her needs. For example, the user may input "I am of child-rearing age and would like to live in Tokyo."

[1278] Input: User needs (e.g. "child-rearing generation", "Tokyo area")

[1279] Output: User needs information is sent from the terminal to the server.

[1280] Specific operation: The user enters information on the screen of a smartphone or PC and presses the send button.

[1281] Step 2:

[1282] Gathering local information

[1283] The server collects information such as the child-rearing support system, educational environment, and number of parks in the user's desired area.

[1284] Input: User's needs information (e.g. "Tokyo")

[1285] Output: Information on local childcare support systems, educational environment, number of parks, etc.

[1286] Specific operation: The server uses a web scraping tool (e.g. BeautifulSoup) to scrape information about child-rearing support systems from the Tokyo Metropolitan Government's official website, and uses an API (e.g. Google Places API) to obtain the number of parks.

[1287] Step 3:

[1288] Data analysis and processing

[1289] The server analyzes the collected regional information using data analysis tools (e.g., Pandas, NumPy).

[1290] Input: Collected local information (e.g. childcare support system, educational environment, number of parks)

[1291] Output: The best living conditions for your needs

[1292] Specific operation: The server uses Pandas to convert the collected data into a data frame, and then performs scoring based on the comprehensiveness of the child-rearing support system and the number of parks.

[1293] Step 4:

[1294] Home proposal generation

[1295] The server uses a generative AI model (e.g. GPT-4) to suggest homes that best fit the user's needs.

[1296] Input: User needs information, analyzed regional information

[1297] Output: Housing proposals based on generative AI models

[1298] Specific operation: The server inputs the following prompt sentence into the generative AI model:

[1299] Please suggest a suitable home in Tokyo for a child-rearing generation. Please consider the following conditions:

[1300] Childcare support system is well established

[1301] Good educational environment

[1302] There are many parks

[1303] A generative AI model generates the suggestions.

[1304] Step 5:

[1305] Presenting the results

[1306] The server transmits the generated housing proposal to the terminal.

[1307] Input: Home proposals based on generative AI models

[1308] Output: Housing proposals presented to the user

[1309] Specific operation: The server sends the suggestions obtained from the generative AI model to the device, and the device displays on the user's screen, "The best area in Tokyo for raising children is Ward XX. There are many parks here, and there is an extensive child-rearing support system."

[1310] (Application example 2)

[1311] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1312] Conventional housing suggestion systems often do not provide suggestions that are fully optimized to meet the needs of users. In particular, for users of child-rearing age, there is a lack of housing suggestions that take into account information such as the local child-rearing support system, educational environment, and number of parks. This makes it difficult for users to find the home that is truly ideal for them.

[1313] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1314] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means for inputting that the user is of child-rearing age, a means for collecting information such as the local child-rearing support system, the educational environment, and the number of parks, a means for generating a home suitable for raising children based on the collected information, and a means for proposing the generated home to the user. This makes it possible to propose a home optimized to the user's needs.

[1315] "User needs" refers to the requirements and demands of users.

[1316] "Social security" refers to systems such as welfare, medical care, and pensions provided by the government and public institutions.

[1317] "Running costs" are the ongoing expenses required to maintain a home.

[1318] "Environment" refers to the natural and social conditions surrounding the home.

[1319] An "AI means" is a method or device that uses artificial intelligence to process information and achieve a specific purpose.

[1320] The "child-rearing generation" refers to people of the age group who are raising children.

[1321] A "childcare support system" refers to public services and systems provided to support childcare.

[1322] The "educational environment" refers to the facilities and surrounding conditions in which children learn.

[1323] "Number of parks" refers to the number of parks that exist within a particular area.

[1324] "Housing" refers to the house where people live and the surrounding environment.

[1325] A "suggestion" is the act of presenting the best option based on a specific purpose or condition.

[1326] A system for implementing this invention includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the environment, etc., AI means for generating an ideal home based on the collected information, means for inputting that the user is of child-rearing age, means for collecting information such as the local child-rearing support system, educational environment, and number of parks, means for generating a home suitable for raising children based on the collected information, and means for proposing the generated home to the user.

[1327] Hardware and Software Used

[1328] Hardware: Smartphone (iOS or Android)

[1329] Software: Python, TensorFlow (to generate AI models), Google Maps API (to collect local information), Firebase (database)

[1330] Data processing and calculation

[1331] Entering user information

[1332] Users log in to a smartphone application and enter information about themselves as parents. For example, they might enter, "I have two children, ages 3 and 5."

[1333] Gathering local information

[1334] The server uses the Google Maps API to collect information such as the childcare support system, educational environment, and number of parks in the area where the user lives. For example, "collect childcare support system, educational environment, and number of parks in Shibuya Ward, Tokyo."

[1335] Creating homes using AI models

[1336] The server uses TensorFlow to generate housing suitable for raising children based on the collected local information. For example, it identifies areas in Shibuya Ward with a robust childcare support system and suggests optimal housing.

[1337] Suggestions for users

[1338] The server uses the data stored in Firebase to suggest the best place to live for the user. For example, it might suggest, "The Yoyogi area of ​​Shibuya Ward is a good place to raise children. We recommend the following properties."

[1339] Examples and prompts

[1340] Examples

[1341] A user logs into the app and enters, "I have two children, ages 3 and 5."

[1342] The app uses the Google Maps API to collect information on child-rearing support systems, educational environments, and the number of parks in Shibuya Ward, Tokyo.

[1343] Use TensorFlow to determine whether the Yoyogi area of ​​Shibuya Ward is suitable for raising children.

[1344] Based on the data stored in Firebase, properties in the Yoyogi area are suggested to users.

[1345] Examples of prompt statements

[1346] Please enter that you are of child-rearing age. Next, we will collect information about the area you live in and let the AI ​​generate the best home for you. For example, please enter "I have two children, ages 3 and 5."

[1347] In this way, users are presented with homes that are optimized to their needs, allowing them to truly find their ideal home.

[1348] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1349] Step 1:

[1350] Users log into a smartphone application and enter that they are of child-rearing age.

[1351] Input: User information (e.g. "I have two children. They are 3 and 5 years old.")

[1352] Output: The user information is sent to the server.

[1353] Specific actions: The user enters information about the parenting generation into the app's input form and presses the submit button.

[1354] Step 2:

[1355] The server uses the Google Maps API to collect information such as child care support systems, educational environments, and the number of parks in the user's area.

[1356] Input: Area information where the user lives (e.g. Shibuya-ku, Tokyo)

[1357] Output: Information such as the local childcare support system, educational environment, and number of parks is stored on the server.

[1358] Specific operation: The server sends a request to the Google Maps API to obtain information such as the child care support system, educational environment, and number of parks in the specified area.

[1359] Step 3:

[1360] The server uses TensorFlow to generate housing suitable for raising children based on the collected local information.

[1361] Input: Local information (childcare support system, educational environment, number of parks, etc.)

[1362] Output: Proposal data for housing suitable for raising children

[1363] Specific operation: The server runs the TensorFlow model and uses the collected local information as input to generate housing suitable for raising children.

[1364] Step 4:

[1365] The server uses the data stored in Firebase to suggest the most suitable home for the user.

[1366] Input: Generated housing proposal data

[1367] Output: Home information suggested to the user

[1368] What it does: The server retrieves the recommendation data from Firebase and displays the best homes for the user through the application.

[1369] Step 5:

[1370] The user reviews the proposed home information and views detailed information.

[1371] Input: Proposed Home Information

[1372] Output: Show detailed information

[1373] Specific operation: The user taps on the suggested home information within the application and is redirected to a screen where they can view more detailed information.

[1374] In this way, users are presented with homes that are optimized to their needs, allowing them to truly find their ideal home.

[1375] In addition, an emotion engine that estimates the emotion of the user may be further combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[1376] "Example 1"

[1377] In one embodiment of the present invention, a system is provided in which the means for collecting user needs includes an emotion engine that recognizes the user's emotions. This system is capable of grasping user needs more precisely by taking into account not only the user's behavior history and input information, but also the user's emotions. The emotion engine analyzes the user's emotions from facial expressions, tone of voice, and text input, and treats the information as part of the user's needs.

[1378] "Example 2"

[1379] As a concrete example, let's say a user is looking for a newly built detached house. The user inputs information into the system, such as their family composition, budget, and desired area. Furthermore, the emotion engine can sense from the user's tone of voice, facial expressions, and text input that the user places importance on a sense of security. Based on this information, the AI ​​will suggest properties in areas with good safety and educational environments. This makes it possible to suggest properties that meet not only the user's explicit needs, but also their emotional needs.

[1380] The process flow of each embodiment will be described below.

[1381] "Example 1"

[1382] Step 1: The user accesses the system and enters the necessary information (family composition, budget, desired area, etc.).

[1383] Step 2: The emotion engine analyzes the user's emotions from their tone of voice, facial expressions, and text input.

[1384] Step 3: Treat the analyzed emotional information as part of user needs.

[1385] Step 4: Based on the information and emotional information collected by the AI, the ideal home is suggested to the user.

[1386] "Example 2"

[1387] Step 1: The user enters information into the system that they are looking for a new home. Step 2: The emotion engine senses from the user's tone of voice, facial expression, and text input that the user values ​​a sense of security.

[1388] Step 3: Based on the information collected by the AI ​​and the emotional information it senses, it recommends properties in areas with good safety and educational environments.

[1389] Example 1

[1390] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1391] Conventional housing recommendation systems did not adequately collect user needs, making it difficult to make precise recommendations that took into account the user's emotions and behavioral history. In addition, they were unable to comprehensively collect information on social security, running costs, and the environment and consider them in an integrated manner, making it difficult to recommend the optimal home for the user. This led to issues such as low user satisfaction and the time and effort required to find the ideal home.

[1392] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1393] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means including an emotion engine for recognizing the user's emotions, a means for comprehensively considering the collected user needs, behavioral history, emotion data, running costs and environmental information, and a means for proposing an optimal home using a generative AI model. This makes it possible to grasp precise user needs taking into account the user's emotions and behavioral history, and to propose an optimal home that comprehensively takes into account social security, running costs and environmental information.

[1394] "User needs" refers to the hopes, requests, and conditions that users have regarding their home.

[1395] "Running costs" refers to ongoing expenses related to housing, such as social security, taxes, utility bills, etc.

[1396] "Environmental information" refers to information about the surrounding environment of a home, such as transportation access, surrounding facilities, public safety, and the natural environment.

[1397] "AI means" refers to a system that uses artificial intelligence technology to analyze data and generate the optimal home.

[1398] An "emotion engine" is a system that analyzes emotions from a user's facial expressions, tone of voice, and text input, and treats that information as part of the user's needs.

[1399] "Behavioral history" refers to data such as a user's past search history and browsing history.

[1400] A "generative AI model" is a model that uses machine learning algorithms to comprehensively consider user needs and collected information to propose the most suitable home.

[1401] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1402] This invention is a system that collects user needs, comprehensively collects running costs and environmental information, including social security, and creates an ideal home based on the collected information. A specific embodiment of this system will be described below.

[1403] Gathering user needs

[1404] A user logs into the system and inputs their housing requirements, including specific requirements such as rent, location, layout, and whether pets are allowed. The terminal transmits the user's input information to the server in real time. In addition, the server retrieves the user's past search and browsing history from a database and stores them together with the current requirements. Using an emotion engine, the system analyzes emotions from the user's facial expressions, tone of voice, and text input, and treats them as part of the user's needs.

[1405] Collection of running costs and environmental information

[1406] The server accesses public databases and automatically collects information on social security, taxes, utility fees, etc. for each region. It also scrapes and collects property information from real estate sites on the Internet. This makes it possible to comprehensively collect property information that matches the user's desired conditions.

[1407] Creating the ideal home

[1408] The server comprehensively considers the collected user needs, behavioral history, emotional data, running costs, and environmental information. Using a generative AI model, this data is input to generate the optimal home. For example, if the user prioritizes "a quiet environment and a park nearby," properties that meet these conditions will be selected as a priority. The generated home proposals are presented to the user by the server.

[1409] Examples

[1410] For example, let's say a user wants a property in Tokyo with a rent of less than 100,000 yen, pets allowed, and within a 10-minute walk from the station. In this case, the system will process as follows:

[1411] 1. The user enters the desired conditions into the system.

[1412] 2. The server collects property information for Tokyo from government statistical databases and real estate websites.

[1413] 3. The emotion engine analyzes the user's facial expressions and tone of voice when typing to identify the conditions that the user particularly values.

[1414] 4. Based on the collected information, the generative AI model suggests the most suitable properties.

[1415] Examples of prompt statements

[1416] "I am looking for a property in Tokyo that is under 100,000 yen in rent, allows pets, and is within a 10-minute walk from the station. I am particularly looking for a quiet environment and a park nearby."

[1417] By inputting this prompt into the generative AI model, properties that match the user's preferences are suggested.

[1418] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1419] Step 1:

[1420] A user logs into the system and inputs the desired conditions for a home.

[1421] Input: User's desired conditions (e.g. rent, location, layout, pets allowed, etc.)

[1422] Output: User's desired conditions data

[1423] Specific operation: The user enters the user name and password on the login screen and clicks the Login button. After that, the user enters the desired conditions in the input form and clicks the Send button.

[1424] Step 2:

[1425] The terminal transmits the user's input information to the server in real time.

[1426] Input: User's desired conditions data

[1427] Output: The desired conditions data sent to the server

[1428] Specific operation: The terminal transmits the desired conditions entered by the user to the server in real time. For example, conditions such as "rent less than 100,000 yen, in Tokyo, pets allowed, within 10 minutes' walk from the station" are transmitted.

[1429] Step 3:

[1430] The server retrieves the user's past search history and browsing history from a database and stores them together with the user's current desired conditions.

[1431] Input: User's desired conditions data, past search history and browsing history

[1432] Output: Consolidated user needs data

[1433] Specific operation: The server retrieves the user's past search history and browsing history from the database, integrates it with the current desired conditions, and saves it. For example, it retrieves information about properties searched for in the past and compares it with the current desired conditions.

[1434] Step 4:

[1435] The device uses an emotion engine to analyze the user's facial expressions and tone of voice, and transmits the emotion data to the server.

[1436] Input: User facial expressions, tone of voice, text input

[1437] Output: Emotion data

[1438] Specific operation: The device analyzes the user's facial expressions and tone of voice using an emotion engine, and sends emotional data to the server to identify the conditions that the user places special importance on. For example, if the user places importance on a "quiet environment," the device sends that information.

[1439] Step 5:

[1440] The server accesses public databases and automatically collects information such as social security, taxes, and utility fees for each region.

[1441] Input: Public database

[1442] Output: Social security, tax, utility fee information by region

[1443] Specific operation: The server accesses a government statistical database and collects information on social security, taxes, utility fees, etc. by region. For example, it obtains the average rent and living expenses in Tokyo.

[1444] Step 6:

[1445] The server scrapes and collects property information from real estate sites on the Internet.

[1446] Input: Real estate website on the Internet

[1447] Output:Property information

[1448] Specific operation: The server scrapes and collects property information from real estate sites on the Internet. For example, it obtains property information within Tokyo.

[1449] Step 7:

[1450] The server stores the collected information in a database and compares it with the user's desired conditions.

[1451] Input: Collected social security, taxes, utilities, property information

[1452] Output: Matched property information

[1453] Specific operation: The server saves the collected information in a database and compares it with the user's desired conditions. For example, it filters properties with rent of less than 100,000 yen, pet-friendly properties, and properties within a 10-minute walk from the station.

[1454] Step 8:

[1455] The server comprehensively considers collected user needs, behavioral history, emotional data, running costs, and environmental information.

[1456] Input: User needs, behavioral history, emotional data, running costs, environmental information

[1457] Output: Consolidated data

[1458] Specific operation: The server comprehensively considers the collected user needs, behavioral history, emotional data, running costs, and environmental information, and integrates the data.

[1459] Step 9:

[1460] The server inputs this data into a generative AI model to generate the optimal home.

[1461] Input: Consolidated data

[1462] Output: Optimal home proposal

[1463] Specific operation: The server inputs the integrated data into the generative AI model and generates the optimal home. For example, if the user prioritizes "a quiet environment and a park nearby," the server will prioritize properties that meet those conditions.

[1464] Step 10:

[1465] The server presents the generated housing proposals to the user.

[1466] Input: Best Home Proposal

[1467] Output: Home proposals presented to the user

[1468] Specific operation: The server presents the generated housing proposals to the user. The user can check the detailed information of the proposed properties and select the property they like.

[1469] (Application example 1)

[1470] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1471] Conventional housing proposal systems were unable to fully reflect the needs of users, and it was difficult to comprehensively collect information on social security, running costs, and the environment. As a result, it was difficult to propose the optimal home for the user. In addition, there was a problem of low user satisfaction because proposals could not be made that took the user's feelings into account.

[1472] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1473] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means including an emotion engine for analyzing user emotions, a means for automatically collecting information from public databases and the Internet, a means for comprehensively considering user needs and the collected information using a machine learning algorithm and proposing the most suitable property, and a means including a smartphone application. This makes it possible to propose the most suitable home considering the user's needs and emotions.

[1474] "Means of collecting user needs" refers to means for collecting the user's desired conditions and requests, and includes the user's input information and behavioral history.

[1475] "Means of comprehensively collecting information on running costs, including social security, and the environment" refers to means for comprehensively collecting information on social security, running costs, the environment, etc. related to housing, and includes systems that automatically collect information from public databases and the Internet.

[1476] An "AI method for generating an ideal home" is a method that uses artificial intelligence technology to generate the optimal home for the user based on collected information.

[1477] "Means including an emotion engine for analyzing user emotions" refers to means for analyzing emotions from a user's facial expressions, tone of voice, and text input, and treating the information as part of the user's needs.

[1478] "Means of automatically collecting information from public databases and the Internet" refers to means of automatically collecting information on social security, running costs, environmental information, etc. from public databases and the Internet.

[1479] "A means for comprehensively considering user needs and collected information using a machine learning algorithm to suggest the most suitable property" refers to a means for comprehensively analyzing user needs and collected information using machine learning technology to suggest the most suitable property to the user.

[1480] "Means including smartphone applications" refer to means including applications that users use to search for their ideal home via their smartphones.

[1481] This invention is a system that collects user needs, comprehensively collects information on social security, running costs, environmental information, etc., and creates an ideal home based on that information. A specific embodiment of this system is described below.

[1482] System Configuration

[1483] The system consists of the following main components:

[1484] 1. How to gather user needs:

[1485] Users input their desired conditions (e.g. budget, floor plan, location, etc.) through a smartphone application.

[1486] Record user activity (e.g. properties viewed, properties saved, etc.).

[1487] The emotion engine analyzes emotions from the user's facial expressions, tone of voice, and text input.

[1488] 2. Comprehensive collection of information:

[1489] Use a system that automatically collects information from public databases and the Internet.

[1490] The information to be collected includes social security, running costs, environmental information, etc.

[1491] 3. AI methods to generate ideal homes:

[1492] Using machine learning algorithms, the system comprehensively considers user needs and collected information to suggest the most suitable properties.

[1493] Program processing explanation

[1494] The server collects user input information, behavioral history, and emotion analysis results from an emotion engine. This allows the system to understand the user's needs in detail. It then automatically collects information from public databases and the Internet to comprehensively obtain information on social security, running costs, the environment, and more.

[1495] Based on this information, a machine learning algorithm is used to comprehensively analyze the user's needs and the collected information, and the system proposes the most suitable property. Specifically, the system considers the user's desired conditions and the results of sentiment analysis to generate the most suitable home.

[1496] Hardware and Software Used

[1497] Hardware:

[1498] Smartphone: A device that allows users to input desired conditions and perform sentiment analysis.

[1499] Server: A central processing unit for collecting, analyzing, and storing data.

[1500] software:

[1501] Emotion engine: Software for analyzing emotions from a user's facial expressions, tone of voice, and text input.

[1502] Machine learning algorithm: An algorithm that comprehensively analyzes user needs and collected information to suggest the most suitable properties.

[1503] Public database access system: A system for collecting information on social security, running costs, and the environment.

[1504] Examples

[1505] For example, if a user types in, "I'm looking for a quiet location with good schools nearby," the emotion engine will analyze the "sense of security" from the user's text and suggest the most suitable property along with budget and location information.

[1506] Examples of prompt statements

[1507] Design an application that, when searching for an ideal home, inputs the desired conditions (budget, layout, location, etc.), analyzes the user's emotions using an emotion engine, and suggests the most suitable property. Collect running costs and environmental information from public databases, and use a machine learning model to make suggestions by taking into consideration the user's needs and the collected information in an integrated manner.

[1508] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1509] Step 1:

[1510] The user inputs the desired conditions through a smartphone application.

[1511] Input: User's desired conditions (e.g. budget, layout, location, etc.)

[1512] Output: User's desired conditions data

[1513] Specific operation: The user enters the desired conditions into the application's input form and presses the submit button. The application sends the entered data to the server.

[1514] Step 2:

[1515] The server records the user's behavior.

[1516] Input: User behavior history (e.g. properties viewed, properties saved, etc.)

[1517] Output: User behavior history data

[1518] How it works: The application monitors user actions and sends information about viewed and saved properties to the server, which then stores the data in a database.

[1519] Step 3:

[1520] The server uses an emotion engine to analyze the user's emotions.

[1521] Input: User facial expressions, tone of voice, text input

[1522] Output: User sentiment data

[1523] How it works: The application captures the user's facial expressions and tone of voice with a camera and microphone, analyzes the text input, and sends this data to the emotion engine, which returns the analysis results to the server.

[1524] Step 4:

[1525] The server automatically collects information from public databases and the Internet.

[1526] Input: Public databases and information from the internet

[1527] Output: Social security, running costs, environmental information data

[1528] Specific operation: The server periodically crawls public databases and information on the Internet, collects the necessary data, and stores it in a database.

[1529] Step 5:

[1530] The server uses machine learning algorithms to comprehensively analyze user needs and collected information.

[1531] Input: User desired conditions data, behavioral history data, emotion data, social security, running costs, environmental information data

[1532] Output: Optimal property proposal data

[1533] How it works: The server runs a machine learning algorithm to comprehensively analyze the input data. The algorithm takes into account the user's needs and the collected information to suggest the best properties.

[1534] Step 6:

[1535] The server notifies the user of the best property suggestions.

[1536] Input: Data for optimal property proposals

[1537] Output:Notification to the user

[1538] Specific operation: The server sends the optimal property recommendation data to the smartphone application, and the application displays a notification to the user.

[1539] Example 2

[1540] Next, a second embodiment of the second form will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1541] Conventional housing recommendation systems mainly make suggestions based on the explicit needs of users, and do not take into account the emotional needs of users or detailed information about the area. This makes it difficult for users to find the ideal home.

[1542] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1543] In this invention, the server includes a means for collecting user needs, a means for performing emotion analysis, a means for collecting information such as the local childcare support system, the educational environment, and the number of parks, an artificial intelligence means for generating an ideal home based on the collected information, and a means for proposing the generated home to the user. This makes it possible to propose an optimal home that takes into account not only the explicit needs of the user but also emotional needs and detailed information about the area.

[1544] "User needs" refers to information that indicates the conditions and desires required by users.

[1545] "Emotion analysis" is a technology that analyzes emotions from a user's tone of voice, facial expressions, text input, etc.

[1546] The "local child-rearing support system" is a general term for child-rearing support and services provided in a specific area.

[1547] "Educational environment" is a general term for educational facilities and education-related environments in a particular area.

[1548] "Number of parks" is the total number of parks in a particular area.

[1549] "Artificial intelligence means" refers to artificial intelligence technology for generating an ideal home based on collected information.

[1550] "Means of proposing a home" refers to technology for presenting the generated ideal home to the user.

[1551] The present invention is a system for proposing an optimal residence based on the needs of a user. A specific embodiment of this system will be described below.

[1552] First, the user uses the terminal to input information such as family composition, budget, desired area, etc. For example, the user inputs information such as "Family composition is four people, budget is within 50 million yen, and desired area is within Tokyo."

[1553] Next, the device performs emotion analysis. While the user is entering information into the input form, the camera and microphone are used to record the user's facial expressions and tone of voice. For emotion analysis, a common emotion analysis API is used. For example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API is used to analyze the importance of the user's sense of security.

[1554] The server then stores the information entered by the user and the results of the sentiment analysis in a database, allowing the necessary information to be efficiently retrieved for subsequent processing.

[1555] Next, the server collects related information from the Internet. Specifically, it uses Google Maps API and the government's open data API to collect information such as the childcare support system, educational environment, and number of parks in the area where the user lives. For example, it obtains information such as "Number of parks in Tokyo: 50, number of public schools: 30, number of childcare support centers: 10."

[1556] The server uses a generative AI model based on the collected data and the results of sentiment analysis to generate properties that are optimal for the user. For example, OpenAI's GPT-4 is used for the generative AI model. This generative AI model proposes properties that meet the user's explicit and emotional needs.

[1557] Finally, the server proposes the generated property information to the user, who can then check the details of "a newly built detached house in a safe area of ​​Tokyo with a good educational environment" on his / her terminal.

[1558] As a concrete example, consider the case where a user is looking for a newly built detached house. The user inputs information into the system, such as family composition, budget, and desired area. Furthermore, the emotion engine senses from the user's tone of voice, facial expression, and text input that the user places importance on a sense of security. Based on this information, the AI ​​suggests properties in areas with good safety and educational environments. This makes it possible to suggest properties that meet not only the user's explicit needs, but also their emotional needs.

[1559] Examples of prompts include:

[1560] "We have a family of four and our budget is within 50 million yen. We would like to live in a location within Tokyo. We value a sense of security. We are looking for a newly built detached house in an area with a good childcare support system and educational environment."

[1561] In this way, the present invention can propose optimal housing that meets the diverse needs of users.

[1562] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1563] Step 1:

[1564] The user enters information

[1565] The user inputs information such as family composition, budget, and desired area into the input form on the terminal. For example, the user inputs "Family composition is 4 people, budget is 50 million yen or less, and desired area is within Tokyo." The input information is sent from the terminal to the server. The input data is text data such as family composition, budget, and desired area.

[1566] Step 2:

[1567] The device performs emotion analysis

[1568] The device uses a camera and microphone to record the user's facial expressions and tone of voice while the user is entering information into an input form. A common emotion analysis API is used for emotion analysis. For example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API is used to analyze whether the user values ​​a sense of security. The input data is the user's facial expressions and tone of voice, and the output data is the user's emotional state (e.g., emphasis on a sense of security).

[1569] Step 3:

[1570] The server stores the user's input in a database

[1571] The server stores the information entered by the user and the results of the emotion analysis in a database. This allows the necessary information to be efficiently retrieved for subsequent processing. The input data is text data such as family composition, budget, desired area, and emotional state, and the output data is the information stored in the database.

[1572] Step 4:

[1573] The server collects relevant information from the Internet.

[1574] The server uses Google Maps API and the government's open data API to collect information such as the child-rearing support system, educational environment, and number of parks in the area where the user lives. For example, it obtains information such as "Number of parks in Tokyo: 50, number of public schools: 30, number of child-rearing support centers: 10." The input data is the user's desired area, and the output data is information such as the local child-rearing support system, educational environment, and number of parks.

[1575] Step 5:

[1576] The server generates properties using generative AI models

[1577] The server uses a generative AI model (e.g., OpenAI's GPT-4) based on the collected data and the results of sentiment analysis to generate the best property for the user. The generative AI model proposes properties that meet the user's explicit and emotional needs. The input data are the user's needs, emotional state, and area information, and the output data is the proposed property information.

[1578] Step 6:

[1579] Propose server-generated properties to users

[1580] The server proposes the property information generated by the generative AI model to the user. The user can check detailed information on "a newly built detached house in a safe area of ​​Tokyo with a good educational environment" on the terminal. The input data is the generated property information, and the output data is the property information presented to the user.

[1581] (Application example 2)

[1582] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1583] Conventional real estate property recommendation systems were able to make suggestions based on the user's explicit needs, but were unable to make suggestions that took into account the user's emotional needs. This made it difficult for users to find properties that truly satisfied them. In addition, there was a lack of systems that comprehensively collected information such as the local childcare support system, educational environment, and number of parks, and suggested the most suitable home for users. This made it difficult for users, especially those of child-rearing age, to find the ideal home.

[1584] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1585] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information on running costs including social security and the like, the environment, and the like, an AI means for generating an ideal home based on the collected information, a means for analyzing the user's emotions, a means for proposing properties based on the user's emotional needs, and a means for displaying detailed information on the proposed properties. This makes it possible to propose properties that simultaneously satisfy the user's explicit needs and emotional needs.

[1586] "Means of collecting user needs" refers to the interface and data collection functions that allow users to input their desired conditions and requests.

[1587] "Means of comprehensively collecting information on running costs, including social security, and the environment" refers to a data collection system for comprehensively collecting information on the local social security system, living expenses, educational environment, number of parks, etc.

[1588] "AI means for generating an ideal home" refers to an artificial intelligence algorithm that uses collected information to generate a home that best suits the user's needs.

[1589] "Means of analyzing user emotions" refers to an emotion analysis engine for analyzing emotions from the user's tone of voice, facial expressions, text input, etc.

[1590] "Means for suggesting properties based on a user's emotional needs" refers to a system for suggesting properties that meet a user's emotional needs based on the results of sentiment analysis.

[1591] "Means for displaying detailed information about the proposed property" means a display or interface for visually providing detailed information about the proposed property to a user.

[1592] An embodiment of the present invention will be described below. The system described below includes AI means for collecting user needs, comprehensively collecting information on running costs including social security and the environment, and generating an ideal home based on the collected information. It also includes means for analyzing the user's emotions, proposing properties based on the emotional needs, and displaying detailed information on the proposed properties.

[1593] System Configuration

[1594] 1. Hardware and Software Use

[1595] Hardware: Smartphones, smart glasses

[1596] Software: Sentiment analysis engines (e.g. Affectiva), data collection APIs (e.g. Google Places API), generative AI models (e.g. GPT-4)

[1597] Data processing and calculation

[1598] 1. Gathering user needs

[1599] Users input information such as their family composition, budget, and desired area via their smartphone or smart glasses.

[1600] The emotion analysis engine analyzes emotions from the user's tone of voice, facial expressions, and text input.

[1601] 2. Collecting local information

[1602] Using the Google Places API, we collect information such as child care support systems, educational environments, and the number of parks in the area where the user lives.

[1603] 3. Creating the ideal home

[1604] Based on the collected data, a generative AI model (GPT-4) is used to generate a home that is suitable for raising children.

[1605] 4. Property proposal

[1606] Suggest properties that meet users' explicit and emotional needs.

[1607] Detailed information about the proposed property will be displayed on the display of a smartphone or smart glasses.

[1608] Examples

[1609] Example prompt:

[1610] User information: Family size = 4, Budget = 50 million yen, Preferred area = Tokyo

[1611] Sentiment analysis results: Emphasis on feeling safe

[1612] Local information: Childcare support system = comprehensive, educational environment = good, number of parks = many

[1613] Inputs to the generative AI model:

[1614] A user with a family of four and a budget of 50 million yen is looking for a property in Tokyo that prioritizes peace of mind. Please suggest a property in an area with a good child-rearing support system, a good educational environment, and many parks.

[1615] In this way, it becomes possible to propose properties that meet the user's explicit and emotional needs at the same time.

[1616] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1617] Step 1:

[1618] Users input information such as family composition, budget, and desired area through their smartphone or smart glasses. The input information is sent to the server, which then stores the information in a database.

[1619] Input: User information such as family composition, budget, desired area, etc.

[1620] Output: User information stored in the database

[1621] Step 2:

[1622] The server uses an emotion analysis engine to analyze the user's tone of voice, facial expressions, and text input to determine their emotions. The analysis results are stored in a database as the user's emotional needs.

[1623] Input: User tone of voice, facial expressions, text input

[1624] Output: Sentiment analysis results (e.g., emphasis on feeling safe)

[1625] Step 3:

[1626] The server uses the Google Places API to collect information about the childcare support system, educational environment, number of parks, etc. in the area where the user lives. The collected information is stored in a database.

[1627] Input: The user's preferred region

[1628] Output: Information on local childcare support systems, educational environment, number of parks, etc.

[1629] Step 4:

[1630] The server uses a generative AI model (GPT-4) based on collected user information, emotion analysis results, and regional information to generate homes that are suitable for raising children. The generated home information is stored in a database.

[1631] Input: User information, sentiment analysis results, region information

[1632] Output: Generated ideal home information

[1633] Step 5:

[1634] Based on the generated home information, the server suggests properties that meet the user's explicit and emotional needs, and the details of the suggested properties are displayed on the display of the smartphone or smart glasses.

[1635] Input: Generated ideal home information

[1636] Output: Details of the proposed property

[1637] Step 6:

[1638] Users check detailed property information displayed on their smartphone or smart glasses displays and select the property they are interested in. The information on the selected property is sent to the server and stored in a database.

[1639] Input: Proposed property details

[1640] Output: Information about the selected property

[1641] In this way, it becomes possible to propose properties that meet the user's explicit and emotional needs at the same time.

[1642] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input for the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1643] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1644] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1645] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1646] [Fourth embodiment]

[1647] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1648] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1649] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[1650] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. In addition, the microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1651] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[1652] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1653] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1654] The control target 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, legs, etc. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, legs, etc. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1655] Fig. 8 shows an example of main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1656] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1657] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1658] In the robot 414, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1659] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1660] "Example 1"

[1661] The system of the present invention includes a means for collecting user needs, a means for comprehensively collecting information on running costs and the environment, including social security, and an AI means for generating an ideal home based on the collected information. As a means for collecting user needs, it is possible to use information input by the user or a user's behavior history. In addition, as a means for comprehensively collecting information on running costs and the environment, including social security, it is possible to use a system that automatically collects information from public databases and the Internet. And, as an AI means for generating an ideal home based on this information, it is possible to use a system that uses a machine learning algorithm to comprehensively consider the user needs and the collected information and propose an ideal home.

[1662] "Example 2"

[1663] As a specific example, information that the user is of child-rearing age is collected as a user need, and comprehensive information such as the child-rearing support system, educational environment, and number of parks in the area where the user lives is collected. Then, based on this information, AI generates homes with an environment suitable for raising children and suggests them to the user. In this way, users are suggested homes that are optimized for their needs, allowing them to find their truly ideal home.

[1664] The process flow of each embodiment will be described below.

[1665] "Example 1"

[1666] Step 1: Collect user needs using information input by the user and user behavioral history, etc.

[1667] Step 2: Using a system that automatically collects information from public databases and the internet, comprehensively collect information on running costs, including social security, and the environment. Step 3: Using a machine learning algorithm, the system will comprehensively consider user needs and the collected information to propose an ideal home.

[1668] "Example 2"

[1669] Step 1: Collect information about the user's child-rearing generation as a user need. Step 2: Collect comprehensive information about the child-rearing support system, educational environment, number of parks, etc. in the area where the user lives.

[1670] Step 3: Based on this information, the AI ​​will generate homes with an environment suitable for raising children and make suggestions to the user.

[1671] Example 1

[1672] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal".

[1673] Conventional housing proposal systems have difficulty in integrating user needs with running costs and environmental information, including social security, making it difficult to propose optimal housing to users. In addition, there was a lack of means to accurately grasp needs by utilizing the user's behavioral history, which led to a problem of reduced proposal accuracy.

[1674] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1675] In this invention, the server includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the like and the environment, artificial intelligence means for generating an ideal home based on the collected information, means for generating a prompt sentence based on the user needs and the collected information, means for inputting the generated prompt sentence into an artificial intelligence model and generating a proposal for the ideal home, and means for transmitting the generated proposal to the user. This makes it possible to comprehensively consider the user needs, running costs including social security and the like, and environmental information, and to propose an optimal home to the user with high accuracy.

[1676] "User needs" refers to the conditions and requests that users have regarding their desired home.

[1677] "Running costs" refer to ongoing expenses related to housing, such as social security fees, taxes, and utility bills.

[1678] "Environmental information" refers to information about the surrounding environment of the home, including transportation access and the presence and distance of facilities such as schools, hospitals, and supermarkets.

[1679] "Artificial intelligence means" refers to means that use machine learning algorithms and generative AI models to generate an ideal home based on user needs and collected information.

[1680] A "prompt" is a document that is used as input to a generative AI model and is a written description that integrates user needs and collected information.

[1681] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to generate suggestions for ideal homes based on input prompt sentences.

[1682] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1683] This invention is a system that collects user needs, comprehensively collects running costs and environmental information, including social security, and creates an ideal home based on this information. A specific embodiment of this system will be described below.

[1684] Gathering user needs

[1685] Users input their housing needs through the terminal. For example, they input information such as the desired layout, budget, and location. The terminal transmits the input information to the server in real time. The transmission uses the HTTPS protocol to ensure data security. The user's behavioral history (previously viewed property information and search history) is also collected and stored in a database.

[1686] Collection of running costs and environmental information

[1687] The server automatically collects information from public databases and the Internet. Specifically, it collects information on social security fees, taxes, utility charges, transportation access, and the surrounding environment (schools, hospitals, supermarkets, etc.). To do this, it uses web scraping technologies such as Python's BeautifulSoup and Scrapy, as well as RESTful APIs. The collected information is stored in a database.

[1688] Creating the ideal home

[1689] The server generates a prompt based on the user's needs and the information it has collected. For example, it might generate a prompt like this:

[1690] User needs:

[1691] Desired layout: 3LDK

[1692] Budget: 30 million yen

[1693] Location: Within 10 minutes walk from the station

[1694] Information collected:

[1695] Social security costs: 200,000 yen per year

[1696] Utility bills: 10,000 yen per month

[1697] Access: 8 minutes walk to the nearest station

[1698] Neighborhood: Near supermarkets, hospitals, and schools

[1699] Use this information to suggest your ideal home.

[1700] The server inputs this prompt into a generative AI model (e.g. GPT-4). The generative AI model generates suggestions for ideal housing based on the input prompt. For example, it generates specific suggestions such as, "I found a 3LDK property within my budget. It's an 8-minute walk from the nearest station, and there are supermarkets, hospitals, and schools in the surrounding area."

[1701] Submit a proposal

[1702] The server sends the generated proposal to the user, who can then review the proposal through the terminal and decide on the next action to take.

[1703] In this way, the system of the present invention is able to comprehensively consider user needs, running costs including social security, and environmental information, and to propose the most suitable home for the user with a high degree of accuracy.

[1704] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1705] Step 1: Gather user needs

[1706] 1.1 The user inputs their housing needs through the device. Specifically, they input information such as the desired layout, budget, location, etc. The input information is saved in a dedicated application on the device.

[1707] 1.2 The terminal transmits the input information to the server in real time using the HTTPS protocol to ensure data security.

[1708] 1.3 The server stores the received user needs in a database, so that the user's desired conditions are accumulated in the system.

[1709] Step 2: Collect user behavior history

[1710] 2.1 The server collects the user's behavioral history, specifically, the property information viewed in the past and search history.

[1711] 2.2 The server stores the collected behavioral history in a database, which allows the server to understand the user's preferences more accurately.

[1712] Step 3: Collect running costs and environmental information

[1713] 3.1 The server automatically collects information from public databases and the Internet, such as information on social security fees, taxes, utility fees, transportation access, and the surrounding environment (schools, hospitals, supermarkets, etc.).

[1714] 3.2 The server retrieves the required information using a web scraping technique such as Python's BeautifulSoup or Scrapy, or, if an API is provided, retrieves the data using a RESTful API.

[1715] 3.3 The server stores the collected information in a database, so that the latest running costs and environmental information are accumulated in the system.

[1716] Step 4: Generate a prompt

[1717] 4.1 The server generates a prompt based on the user's needs and the collected information. Specifically, the server combines the user's desired conditions with the collected running costs and environmental information to generate a prompt like the following:

[1718] User needs:

[1719] Desired layout: 3LDK

[1720] Budget: 30 million yen

[1721] Location: Within 10 minutes walk from the station

[1722] Information collected:

[1723] Social security costs: 200,000 yen per year

[1724] Utility bills: 10,000 yen per month

[1725] Access: 8 minutes walk to the nearest station

[1726] Neighborhood: Near supermarkets, hospitals, and schools

[1727] Use this information to suggest your ideal home.

[1728] 4.2 The server prepares the generated prompt sentence to be input to the generative AI model.

[1729] Step 5: Create your dream home

[1730] 5.1 The server inputs a prompt to a generative AI model (e.g., GPT-4). The generative AI model generates a proposal for an ideal home based on the input prompt.

[1731] 5.2 The generative AI model generates housing proposals that best fit the user's criteria. For example, it generates specific proposals such as, "I found a 3LDK property within my budget. It's an 8-minute walk from the nearest station, and there are supermarkets, hospitals, and schools nearby."

[1732] 5.3 The server stores the generated suggestions in a database.

[1733] Step 6: Submit your proposal

[1734] 6.1 The server sends the generated proposal to the user, either via email or via the notification feature of the application.

[1735] 6.2 The user confirms the proposal through the terminal and can decide the next action based on the proposal.

[1736] (Application example 1)

[1737] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal".

[1738] In today's housing selection process, users need to gather and compare a lot of information, but this process takes a lot of time and effort. It is not easy to find a home that is optimized for the user's needs. Furthermore, it is difficult to take into account important factors such as running costs and environmental information, making it difficult to find the ideal home. To solve these problems, a system is needed that can accurately gather the user's needs and propose the ideal home based on comprehensive information.

[1739] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1740] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information on running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means for collecting user needs based on user input information and behavior history, a means for automatically collecting running cost and environmental information from the Internet and public databases, a means for comprehensively considering user needs and the collected information using a machine learning algorithm and proposing an ideal home, and an application installed on a smartphone. This enables users to efficiently find an ideal home that is optimized for their needs.

[1741] "User needs" refer to the hopes and demands that users have regarding their homes.

[1742] "Running costs" are the ongoing expenses required to maintain a home.

[1743] "Environmental information" refers to information about the surrounding environment of a home, including, for example, transportation access, public safety, and the presence or absence of educational facilities.

[1744] "AI means" refers to a means that uses artificial intelligence to analyze data and make optimal suggestions.

[1745] A "machine learning algorithm" is an algorithm that learns patterns from data and makes predictions and classifications.

[1746] A "smartphone" is a type of mobile phone, a multi-function device that can connect to the Internet and install applications.

[1747] An "application" is software designed to provide a specific function or service.

[1748] A "public database" is a database provided by a government or public institution that contains highly reliable information.

[1749] "Behavioral history" is a record of a user's past actions and choices.

[1750] The "Internet" is a huge information and communications network that interconnects computer networks all over the world.

[1751] A system for implementing this invention includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the environment, AI means for generating an ideal home based on the collected information, means for collecting user needs based on user input information and behavioral history, means for automatically collecting running cost and environmental information from the Internet or public databases, means for comprehensively considering user needs and the collected information using a machine learning algorithm to propose an ideal home, and an application installed on a smartphone.

[1752] Program processing explanation

[1753] The server collects the needs and desired conditions entered by the user via their smartphone. These include the desired location, budget, size, and facilities. The server then automatically collects information about the running costs and environment of the specified location from the Internet and public databases. This information includes transportation access, public safety, and the availability of educational facilities.

[1754] The collected data is analyzed using a machine learning algorithm. Specifically, the data is preprocessed and the ideal home is predicted by comprehensively considering the user's needs and environmental information. For example, the machine learning algorithm used is Random Forest Regressor.

[1755] The application installed on the user's smartphone receives suggestions from the server and presents the user with their ideal home. The application makes optimized suggestions based on the information entered by the user and their behavioral history.

[1756] Examples

[1757] For example, if a user inputs, "I would like to live in Tokyo with a budget of 30 million yen, a space of 70 square meters, and facilities such as air conditioning and a balcony," the server will collect environmental information about Tokyo and suggest the ideal home based on the user's desired conditions.

[1758] Example prompt:

[1759] Please enter your desired location: Tokyo

[1760] Enter your budget: 3000

[1761] Enter your desired size: 70

[1762] Please enter the desired amenities (separated by commas): air conditioning, balcony

[1763] After entering this prompt, the application receives suggestions from the server and presents ideal homes to the user, allowing the user to efficiently find the ideal home that best suits their needs.

[1764] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1765] Step 1:

[1766] Users use their smartphones to input their needs, such as desired location, budget, size, and facilities.

[1767] Input: User needs (desired location, budget, size, facilities)

[1768] Output: User needs data

[1769] Specific operation: The user enters the desired conditions into the application's input form and presses the submit button.

[1770] Step 2:

[1771] The server receives user needs data and collects running costs and environmental information for the specified location from the Internet and public databases.

[1772] Input: User needs data

[1773] Output: Environmental information data

[1774] Specific operation: The server uses the API to obtain running costs and environmental information for the specified location.

[1775] Step 3:

[1776] The server preprocesses the collected user needs data and environmental information data.

[1777] Input: User needs data, environmental information data

[1778] Output: Preprocessed data

[1779] Specific operation: The server performs data cleaning, normalization, and feature engineering.

[1780] Step 4:

[1781] The server feeds the preprocessed data into a machine learning algorithm to predict the ideal home.

[1782] Input: Preprocessed data

[1783] Output: Proposal data for an ideal home

[1784] How it works: The server uses a machine learning model such as RandomForestRegressor to predict the ideal home.

[1785] Step 5:

[1786] The server sends suggested data for the ideal home to the smartphone.

[1787] Input: Ideal home proposal data

[1788] Output: Sending proposal data to a smartphone

[1789] Specific operation: The server sends the proposal data to the user's smartphone via the network.

[1790] Step 6:

[1791] The smartphone displays the received proposal data to the user.

[1792] Input: Proposal data

[1793] Output: What is displayed to the user

[1794] Specific operation: The smartphone application analyzes the proposal data and displays the ideal home for the user.

[1795] Example 2

[1796] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal".

[1797] Conventional housing proposal systems have difficulty in making proposals that are fully optimized to meet the needs of users. In particular, for users of child-rearing age, there is a demand for proposals based on comprehensive collection of information such as the local child-rearing support system, educational environment, and number of parks, but no system that can achieve this exists. Therefore, a new system that can propose housing that is optimized to the needs of users is needed.

[1798] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1799] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as the local childcare support system, the educational environment, and the number of parks, a means for analyzing the collected information using a data analysis tool and extracting the conditions for a home that best suits the user's needs, a means for proposing a home that best suits the user's needs using a generative AI model, and a means for presenting the proposed content to the user. This makes it possible to propose a home that is optimized for the user's needs.

[1800] "User needs" refers to information that indicates the conditions and desires required by users.

[1801] The "local child-rearing support system" is a general term for public support and services related to child-rearing provided in a specific area.

[1802] "Educational environment" refers to the condition of schools, educational facilities, education-related services and infrastructure in a particular area.

[1803] "Number of parks" refers to the total number of parks that exist within a particular area.

[1804] "Data analysis tools" is a general term for software and programs used to organize and analyze collected data and extract meaningful information.

[1805] A "generative AI model" is a general term for algorithms and programs that use artificial intelligence to generate an appropriate output for a specific input.

[1806] "Proposal Content" refers to specific proposed information about a home created by the generative AI model based on the user's needs.

[1807] The present invention is a system for proposing an optimal residence based on the needs of a user. A specific embodiment of this system is described below.

[1808] First, the user inputs their needs using the terminal. For example, the user inputs, "I'm in the child-rearing generation and want to live in Tokyo." This information is sent from the terminal to the server.

[1809] Next, the server collects information about the childcare support system, educational environment, number of parks, etc., in the area desired by the user. To do this, a web scraping tool (e.g. BeautifulSoup) or an API (e.g. Google Places API) is used. For example, the server uses BeautifulSoup to scrape information about the childcare support system from the official Tokyo Metropolitan Government website, and obtains the number of parks using Google Places API.

[1810] The collected information is analyzed by the server using data analysis tools (e.g., Pandas, NumPy). The server converts the collected data into a data frame and scores it based on the level of support for childcare and the number of parks.

[1811] The server then uses a generative AI model (e.g. GPT-4) to suggest the best home for the user’s needs. It does this by inputting a prompt into the generative AI model. For example, the following prompt can be used:

[1812] Please suggest a suitable home in Tokyo for a child-rearing generation. Please consider the following conditions:

[1813] Childcare support system is well established

[1814] Good educational environment

[1815] There are many parks

[1816] The generative AI model generates suggestions based on this prompt.

[1817] Finally, the server sends the generated housing proposal to the device, and the device displays the proposal to the user. For example, the device may display on the user's screen, "The best area for raising children in Tokyo is ____ ward. There are many parks here, and the childcare support system is also well developed."

[1818] In this way, the user can receive proposals for homes that are optimized to their needs. This system performs a series of processes to propose the optimal home based on the user's needs, making it possible to provide the ideal home for the user.

[1819] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1820] Step 1:

[1821] Entering user information

[1822] The user uses the terminal to input his / her needs. For example, the user may input "I am of child-rearing age and would like to live in Tokyo."

[1823] Input: User needs (e.g. "child-rearing generation", "Tokyo area")

[1824] Output: User needs information is sent from the terminal to the server.

[1825] Specific operation: The user enters information on the screen of a smartphone or PC and presses the send button.

[1826] Step 2:

[1827] Gathering local information

[1828] The server collects information such as the child-rearing support system, educational environment, and number of parks in the user's desired area.

[1829] Input: User's needs information (e.g. "Tokyo")

[1830] Output: Information on local childcare support systems, educational environment, number of parks, etc.

[1831] Specific operation: The server uses a web scraping tool (e.g. BeautifulSoup) to scrape information about child-rearing support systems from the Tokyo Metropolitan Government's official website, and uses an API (e.g. Google Places API) to obtain the number of parks.

[1832] Step 3:

[1833] Data analysis and processing

[1834] The server analyzes the collected regional information using data analysis tools (e.g., Pandas, NumPy).

[1835] Input: Collected local information (e.g. childcare support system, educational environment, number of parks)

[1836] Output: The best living conditions for your needs

[1837] Specific operation: The server uses Pandas to convert the collected data into a data frame, and then performs scoring based on the comprehensiveness of the child-rearing support system and the number of parks.

[1838] Step 4:

[1839] Home proposal generation

[1840] The server uses a generative AI model (e.g. GPT-4) to suggest homes that best fit the user's needs.

[1841] Input: User needs information, analyzed regional information

[1842] Output: Housing proposals based on generative AI models

[1843] Specific operation: The server inputs the following prompt sentence into the generative AI model:

[1844] Please suggest a suitable home in Tokyo for a child-rearing generation. Please consider the following conditions:

[1845] Childcare support system is well established

[1846] Good educational environment

[1847] There are many parks

[1848] A generative AI model generates the suggestions.

[1849] Step 5:

[1850] Presenting the results

[1851] The server transmits the generated housing proposal to the terminal.

[1852] Input: Home proposals based on generative AI models

[1853] Output: Housing proposals presented to the user

[1854] Specific operation: The server sends the suggestions obtained from the generative AI model to the device, and the device displays on the user's screen, "The best area in Tokyo for raising children is Ward XX. There are many parks here, and there is an extensive child-rearing support system."

[1855] (Application example 2)

[1856] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal".

[1857] Conventional housing suggestion systems often do not provide suggestions that are fully optimized to meet the needs of users. In particular, for users of child-rearing age, there is a lack of housing suggestions that take into account information such as the local child-rearing support system, educational environment, and number of parks. This makes it difficult for users to find the home that is truly ideal for them.

[1858] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1859] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means for inputting that the user is of child-rearing age, a means for collecting information such as the local child-rearing support system, the educational environment, and the number of parks, a means for generating a home suitable for raising children based on the collected information, and a means for proposing the generated home to the user. This makes it possible to propose a home optimized to the user's needs.

[1860] "User needs" refers to the requirements and demands of users.

[1861] "Social security" refers to systems such as welfare, medical care, and pensions provided by the government and public institutions.

[1862] "Running costs" are the ongoing expenses required to maintain a home.

[1863] "Environment" refers to the natural and social conditions surrounding the home.

[1864] An "AI means" is a method or device for processing information using artificial intelligence to achieve a specific purpose.

[1865] The "child-rearing generation" refers to people of the age group who are raising children.

[1866] A "childcare support system" refers to public services and systems provided to support childcare.

[1867] The "educational environment" refers to the facilities and surrounding conditions in which children learn.

[1868] "Number of parks" refers to the number of parks that exist within a particular area.

[1869] "Housing" refers to the house where people live and the surrounding environment.

[1870] A "suggestion" is the act of presenting the best option based on a specific purpose or condition.

[1871] A system for implementing this invention includes means for collecting user needs, means for comprehensively collecting information on running costs including social security and the environment, etc., AI means for generating an ideal home based on the collected information, means for inputting that the user is of child-rearing age, means for collecting information such as the local child-rearing support system, educational environment, and number of parks, means for generating a home suitable for raising children based on the collected information, and means for proposing the generated home to the user.

[1872] Hardware and Software Used

[1873] Hardware: Smartphone (iOS or Android)

[1874] Software: Python, TensorFlow (to generate AI models), Google Maps API (to collect local information), Firebase (database)

[1875] Data processing and calculation

[1876] Entering user information

[1877] Users log in to a smartphone application and enter information about themselves as parents. For example, they might enter, "I have two children, ages 3 and 5."

[1878] Gathering local information

[1879] The server uses the Google Maps API to collect information such as the childcare support system, educational environment, and number of parks in the area where the user lives. For example, "collect childcare support system, educational environment, and number of parks in Shibuya Ward, Tokyo."

[1880] Creating homes using AI models

[1881] The server uses TensorFlow to generate housing suitable for raising children based on the collected local information. For example, it identifies areas in Shibuya Ward with a robust childcare support system and suggests optimal housing.

[1882] Suggestions for users

[1883] The server uses the data stored in Firebase to suggest the best place to live for the user. For example, it might suggest, "The Yoyogi area of ​​Shibuya Ward is a good place to raise children. We recommend the following properties."

[1884] Examples and prompts

[1885] Examples

[1886] A user logs into the app and enters, "I have two children, ages 3 and 5."

[1887] The app uses the Google Maps API to collect information on child-rearing support systems, educational environments, and the number of parks in Shibuya Ward, Tokyo.

[1888] Use TensorFlow to determine whether the Yoyogi area of ​​Shibuya Ward is suitable for raising children.

[1889] Based on the data stored in Firebase, properties in the Yoyogi area are suggested to users.

[1890] Examples of prompt statements

[1891] Please enter that you are of child-rearing age. Next, we will collect information about the area you live in and let the AI ​​generate the best home for you. For example, please enter "I have two children, ages 3 and 5."

[1892] In this way, users are presented with homes that are optimized to their needs, allowing them to truly find their ideal home.

[1893] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1894] Step 1:

[1895] Users log into a smartphone application and enter that they are of child-rearing age.

[1896] Input: User information (e.g. "I have two children. They are 3 and 5 years old.")

[1897] Output: The user information is sent to the server.

[1898] Specific actions: The user enters information about the parenting generation into the app's input form and presses the submit button.

[1899] Step 2:

[1900] The server uses the Google Maps API to collect information such as child care support systems, educational environments, and the number of parks in the user's area.

[1901] Input: Area information where the user lives (e.g. Shibuya-ku, Tokyo)

[1902] Output: Information such as the local childcare support system, educational environment, and number of parks is stored on the server.

[1903] Specific operation: The server sends a request to the Google Maps API to obtain information such as the child care support system, educational environment, and number of parks in the specified area.

[1904] Step 3:

[1905] The server uses TensorFlow to generate housing suitable for raising children based on the collected local information.

[1906] Input: Local information (childcare support system, educational environment, number of parks, etc.)

[1907] Output: Proposal data for housing suitable for raising children

[1908] Specific operation: The server runs the TensorFlow model and uses the collected local information as input to generate housing suitable for raising children.

[1909] Step 4:

[1910] The server uses the data stored in Firebase to suggest the most suitable home for the user.

[1911] Input: Generated housing proposal data

[1912] Output: Home information suggested to the user

[1913] What it does: The server retrieves the recommendation data from Firebase and displays the best homes for the user through the application.

[1914] Step 5:

[1915] The user reviews the proposed home information and views detailed information.

[1916] Input: Proposed Home Information

[1917] Output: Show detailed information

[1918] Specific operation: The user taps on the suggested home information within the application and is redirected to a screen where they can view more detailed information.

[1919] In this way, users are presented with homes that are optimized to their needs, allowing them to truly find their ideal home.

[1920] In addition, an emotion engine that estimates the emotion of the user may be further combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[1921] "Example 1"

[1922] In one embodiment of the present invention, a system is provided in which the means for collecting user needs includes an emotion engine that recognizes the user's emotions. This system is capable of grasping user needs more precisely by taking into account not only the user's behavior history and input information, but also the user's emotions. The emotion engine analyzes the user's emotions from facial expressions, tone of voice, and text input, and treats the information as part of the user's needs.

[1923] "Example 2"

[1924] As a concrete example, let's say a user is looking for a newly built detached house. The user inputs information into the system, such as their family composition, budget, and desired area. Furthermore, the emotion engine can sense from the user's tone of voice, facial expressions, and text input that the user places importance on a sense of security. Based on this information, the AI ​​will suggest properties in areas with good safety and educational environments. This makes it possible to suggest properties that meet not only the user's explicit needs, but also their emotional needs.

[1925] The process flow of each embodiment will be described below.

[1926] "Example 1"

[1927] Step 1: The user accesses the system and enters the necessary information (family composition, budget, desired area, etc.).

[1928] Step 2: The emotion engine analyzes the user's emotions from their tone of voice, facial expressions, and text input.

[1929] Step 3: Treat the analyzed emotional information as part of user needs.

[1930] Step 4: Based on the information and emotional information collected by the AI, the ideal home is suggested to the user.

[1931] "Example 2"

[1932] Step 1: The user enters information into the system that they are looking for a new home. Step 2: The emotion engine senses from the user's tone of voice, facial expression, and text input that the user values ​​a sense of security.

[1933] Step 3: Based on the information collected by the AI ​​and the emotional information it senses, it recommends properties in areas with good safety and educational environments.

[1934] Example 1

[1935] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal".

[1936] Conventional housing recommendation systems did not adequately collect user needs, making it difficult to make precise recommendations that took into account the user's emotions and behavioral history. In addition, they were unable to comprehensively collect information on social security, running costs, and the environment and consider them in an integrated manner, making it difficult to recommend the optimal home for the user. This led to issues such as low user satisfaction and the time and effort required to find the ideal home.

[1937] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1938] In this invention, the server includes a means for collecting user needs, a means for comprehensively collecting information such as running costs including social security and the like and the environment, an AI means for generating an ideal home based on the collected information, a means including an emotion engine for recognizing the user's emotions, a means for comprehensively considering the collected user needs, behavioral history, emotion data, running costs and environmental information, and a means for proposing an optimal home using a generative AI model. This makes it possible to grasp precise user needs taking into account the user's emotions and behavioral history, and to propose an optimal home that comprehensively takes into account social security, running costs and environmental information.

[1939] "User needs" refers to the hopes, requests, and conditions that users have regarding their home.

[1940] "Running costs" refers to ongoing expenses related to housing, such as social security, taxes, utility bills, etc.

[1941] "Environmental information" refers to information about the surrounding environment of a home, such as transportation access, surrounding facilities, public safety, and the natural environment.

[1942] "AI means" refers to a system that uses artificial intelligence technology to analyze data and generate the optimal home.

[1943] An "emotion engine" ...

Claims

1. A means of collecting user needs; A means to comprehensively collect information on running costs and the environment, including social security, and An artificial intelligence means for generating an ideal home based on collected information; A means of generating prompts based on user needs and collected information; An AI means for inputting the generated prompt sentence into an artificial intelligence model to generate a proposal for an ideal home; A means for transmitting the ideal home proposal generated by the AI ​​means to a user; A system including:

2. The system according to claim 1 , wherein the AI ​​means suggests an ideal home to the user based on the collected information.

3. The system according to claim 1 , wherein the AI ​​means, when proposing an ideal home to a user based on the collected information, makes suggestions optimized to the user's needs.

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