System

Abstract

An object of a system according to an embodiment is to promote effective use of vacant houses and realize optimal matching between owners and consumers.SOLUTION: A system includes an incentive providing unit, a matching unit, and an advice support unit. The incentive providing part provides rental income and a privilege to the vacant house owner. The matching unit collects and analyzes vacant house information and consumer information using AI, and performs optimal matching. The advice support component provides advice and support related to the renovation of empty houses.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology has had the problem of not making effective use of vacant houses and not efficiently matching owners with buyers.

[0005] The system according to the embodiment aims to promote the effective use of vacant houses and to achieve optimal matching between owners and demanders. [Means for solving the problem]

[0006] The system according to the embodiment comprises an incentive providing unit, a matching unit, and an advice and support unit. The incentive providing unit provides rental income and benefits to owners of vacant houses. The matching unit uses AI to collect and analyze information on vacant houses and users, and performs optimal matching. The advice and support unit provides advice and support regarding the renovation of vacant houses. [Effects of the Invention]

[0007] The system according to the embodiment can promote the effective use of vacant houses and realize optimal matching between owners and demanders. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] 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.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] 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.

[0020] 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 (for example, 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 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The comprehensive platform according to an embodiment of the present invention is a system that matches owners of vacant houses with those who wish to use them. As a result, the comprehensive platform can promote the effective use of vacant houses in areas that have a problem with vacant houses, thereby revitalizing the area.

[0029] A comprehensive platform according to an embodiment includes an incentive providing unit, a matching unit, and an advice and support unit. The incentive providing unit provides rental income and benefits to owners of vacant homes. For example, the incentive providing unit may offer tax reductions or subsidies for renting out a vacant home for a certain period of time. Furthermore, the incentive providing unit may offer benefits such as subsidizing part of the renovation costs if the owner renovates and rents out the vacant home. Furthermore, the incentive providing unit may provide a program for owners of vacant homes to earn rental income. For example, the incentive providing unit may calculate the income that can be earned by renting out the vacant home and present it to the owner. The matching unit uses AI to collect and analyze information about vacant homes and users to perform optimal matching. For example, the matching unit may register information about the location, condition, price, and other information about vacant homes in a database and compare it with the user's desired conditions. Furthermore, the matching unit may use a generation AI to analyze desired conditions entered by a user and suggest the most suitable vacant home based on the results. For example, if the user enters desired conditions such as "looking for a vacant home with a 3LDK in Tokyo," the generation AI may search the database for matching vacant homes and suggest the most suitable property. The advice and support unit provides advice and support regarding the renovation of vacant houses. For example, the advice and support unit analyzes the condition of the vacant house and surrounding market trends, and proposes the renovation content and costs. The advice and support unit also uses generative AI to analyze photos and floor plans of the vacant house and provide estimates of the areas that need renovation and the costs. Furthermore, the advice and support unit analyzes surrounding market trends to predict the rental and selling prices after renovation. As a result, the comprehensive platform according to the embodiment can promote the effective use of vacant houses and revitalize local areas. For example, vacant house owners can enjoy economic benefits by earning rental income, and it becomes easier for buyers to find the properties they want. The renovation advice and support system can also increase the value of vacant houses.

[0030] The incentive provision unit can analyze the past rental history and renovation history of vacant home owners and customize and provide optimal incentives. For example, the incentive provision unit registers the past rental history of vacant home owners in a database and customizes optimal incentives based on that data. For example, it analyzes the period and rent of past rentals and provides special benefits to owners who have rented out their homes for long periods of time. The incentive provision unit also analyzes renovation history and provides incentives based on the frequency and content of renovations. For example, an owner who has previously performed major renovations can be provided with a benefit that partially subsidizes the cost of the next renovation. The incentive provision unit also analyzes rental history and renovation history in an integrated manner and customizes incentives based on the owner's behavioral patterns. For example, an owner who frequently renovates and rents out their homes can be provided with a discount coupon for renovation materials. In this way, it is possible to increase the owner's motivation by analyzing the past rental history and renovation history of vacant home owners and providing optimal incentives.

[0031] The incentive providing unit can provide benefits that take into consideration the lifestyle, hobbies, and preferences of vacant home owners. For example, the incentive providing unit collects information about the lifestyle, hobbies, and preferences of vacant home owners through questionnaires and interviews, and customizes benefits based on that data. For example, a travel voucher is provided to an owner whose hobby is traveling. The incentive providing unit also builds a system that personalizes benefits based on the owner's hobby and preferences. For example, a discount coupon for gardening equipment is provided to an owner whose hobby is gardening. The incentive providing unit also partners with local stores and services to provide benefits that take into consideration the lifestyle, hobbies, and preferences of vacant home owners. For example, discount coupons for local restaurants and cafes are provided. In this way, the satisfaction of vacant home owners can be increased by providing benefits that take into consideration the lifestyle, hobbies, and preferences of vacant home owners.

[0032] The incentive provision unit can include partnerships with local shops and services in the incentive program to promote the revitalization of the local economy. For example, the incentive provision unit can include partnerships with local shops and services in the incentive program to provide discount coupons that the owner can use at local stores. For example, the incentive provision unit can issue coupons that can be used at local supermarkets and restaurants. The incentive provision unit can also partner with local shops and services to provide benefits that allow the owner to participate in local events and workshops. For example, the incentive provision unit can provide tickets to local cultural events and sporting events. The incentive provision unit can also include local specialties and services in the incentive program to promote the revitalization of the local economy. For example, the incentive provision unit can offer local agricultural products and crafts as benefits. In this way, by including partnerships with local shops and services in the incentive program, the revitalization of the local economy can be promoted.

[0033] The incentive provision unit can link the incentive program with community events and workshops in which vacant house owners participate. For example, the incentive provision unit links the incentive program with community events and workshops so that owners can receive rewards by participating. For example, rewards are provided for participating in local cleanup activities or renovation workshops. The incentive provision unit also builds a system that provides special incentives to owners who participate in community events and workshops. For example, points are awarded to event participants, and the points can be exchanged for rewards. The incentive provision unit also encourages owners to actively participate in the local community through the incentive program. For example, rewards can be provided for participating in local exchange events or study sessions. In this way, by linking the incentive program with community events and workshops, it is possible to encourage vacant house owners to participate in the local community.

[0034] The matching unit uses generation AI to generate detailed information about the internal structure and facilities of a vacant house as a 3D model, which can be visually provided to consumers. For example, the matching unit uses generation AI to build a system that generates detailed information about the internal structure and facilities of a vacant house as a 3D model and visually provides this information to consumers. For example, the floor plan and layout of the facilities of the vacant house are displayed in a 3D model. The matching unit also inputs photos and floor plans of the vacant house, and the generation AI automatically generates a 3D model based on that information. For example, the interior of the vacant house is visually provided in the form of a virtual tour. The matching unit also uses generation AI to generate a simulated 3D model of the vacant house after renovation and provides this to consumers. For example, a comparison before and after renovation is visually displayed in a 3D model. In this way, detailed information about the internal structure and facilities of a vacant house can be provided as a 3D model, providing visual information to consumers and making it easier for them to choose a property.

[0035] The matching unit can use generation AI to analyze a consumer's past search history and browsing history and make individually customized property proposals. For example, the matching unit uses generation AI to analyze a consumer's past search history and browsing history and build a system that makes individually customized property proposals. For example, it proposes optimal properties based on the conditions searched in the past. The matching unit also analyzes a consumer's browsing history and makes property proposals tailored to the consumer's preferences and needs. For example, it proposes similar properties based on the characteristics of properties viewed in the past. The matching unit also uses generation AI to analyze a consumer's search history and browsing history in real time and develop a system that makes individually customized property proposals. For example, it proposes properties based on the consumer's latest search conditions. In this way, by analyzing a consumer's past search history and browsing history and making individually customized property proposals, it is possible to increase consumer satisfaction.

[0036] The matching department can add a function that allows consumers to tour properties in virtual reality (VR). For example, the matching department adds a VR tour function to the matching platform, allowing consumers to tour properties in virtual reality. For example, a VR headset can be used to realistically experience the interior of the property. The matching department also builds a system in which a generation AI provides real-time guidance when consumers tour properties in VR. For example, the property's features and facilities can be explained in VR. The matching department also develops a system that uses the VR tour function to allow consumers to experience a simulation of the property after renovation. For example, a visual comparison of the before and after renovation can be provided in VR. This allows consumers to tour properties in virtual reality, thereby improving the accuracy of property selection.

[0037] The matching unit can add a chatbot function that allows consumers to ask questions about properties in real time. For example, the matching unit adds a chatbot function to the matching platform, allowing consumers to ask questions about properties in real time. For example, consumers can ask questions about detailed information about the property and the surrounding environment. The matching unit also uses a generation AI to develop a chatbot that answers consumers' questions in real time. For example, it can immediately answer questions about the property's facilities and contract terms. The matching unit also builds a system in which, when consumers ask questions about properties using the chatbot function, the generation AI automatically provides relevant information. For example, it can display photos and floor plans of the property in response to the consumer's questions. This allows consumers to ask questions about properties in real time, thereby improving the accuracy of property selection.

[0038] The advice support unit can use the generation AI to generate simulated images and videos of the vacant house after renovation and provide them to the owner. For example, the advice support unit builds a system that uses the generation AI to generate simulated images of the vacant house after renovation and provides them to the owner. For example, it provides comparison images before and after renovation. The advice support unit also inputs photos and floor plans of the vacant house, and the generation AI automatically generates a simulated video of the vacant house after renovation based on that information. For example, it provides a visual video of the renovation process. The advice support unit also uses the generation AI to generate a simulated 3D model of the vacant house after renovation and provides it to the owner. For example, it visually displays the internal structure and equipment layout after renovation in a 3D model. In this way, by providing simulated images and videos of the vacant house after renovation, the owner can visually confirm the results of the renovation.

[0039] The advice support unit can use generation AI to automatically generate a detailed list of materials and work required for renovation and provide it to the owner. For example, the advice support unit will build a system that uses generation AI to automatically generate a detailed list of materials and work required for renovation. For example, it will provide a materials list based on the scale and content of the renovation. The advice support unit will also input the condition of the vacant house and the renovation plan, and the generation AI will automatically generate a list of the necessary materials and work based on that information. For example, it will provide a list of wall materials, flooring materials, and equipment. The advice support unit will also develop a system that uses generation AI to generate a detailed list of materials and work required for renovation in real time and provide it to the owner. For example, it will update the list according to the progress of the renovation. This will make it easier for the owner to plan the renovation by providing a detailed list of materials and work required for the renovation.

[0040] The advice and support unit can add a function that allows the owner to check the progress of the renovation in real time. For example, the advice and support unit adds a progress check function to a renovation advice and support system, allowing the owner to check the progress of the renovation in real time. For example, each renovation process is displayed on a timeline. The advice and support unit also uses generative AI to analyze the progress of the renovation in real time and builds a system that notifies the owner. For example, it sends emails or app notifications to the owner depending on the progress of the renovation. The advice and support unit also develops a system that allows the owner to check the progress of the renovation in real time using the renovation progress check function and make changes or adjustments as needed. For example, it adjusts the renovation plan depending on the progress. This makes it easier for the owner to understand the status of the renovation by being able to check the progress of the renovation in real time.

[0041] The advice and support unit can add a chatbot function that allows questions about renovations to be asked in real time. For example, the advice and support unit adds a chatbot function to a renovation advice and support system, allowing owners to ask questions about renovations in real time. For example, they can ask about renovation details and progress. The advice and support unit also uses a generation AI to develop a chatbot that answers owners' questions in real time. For example, it immediately answers questions about renovation materials and construction details. The advice and support unit also builds a system in which, when owners ask questions about renovations using the chatbot function, the generation AI automatically provides relevant information. For example, it displays photos of the renovation and progress status in response to the owner's question. This allows owners to ask questions about renovations in real time, allowing them to instantly resolve their renovation-related concerns.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The incentive provision department can also provide benefits that take into consideration the health condition of vacant house owners. For example, it can provide coupons for health checkups or free tickets to fitness gyms. The incentive provision department can also build a system that customizes benefits that are useful for maintaining health based on the owner's health data. For example, if the owner has high blood pressure, it can provide discount coupons for health foods. The incentive provision department can also partner with local medical institutions and health-related services to provide benefits that allow owners to receive health checkups and health consultations. In this way, it is possible to support the maintenance of health of vacant house owners by providing benefits that take into consideration the owner's health condition.

[0044] The incentive provision department can also provide rewards to increase the environmental awareness of vacant house owners. For example, it can provide discount coupons for eco-friendly home appliances or rewards related to promoting the use of renewable energy. The incentive provision department can also build a system to customize rewards that owners can receive by taking environmentally friendly actions. For example, if an owner installs a solar power generation system, it can provide a reward that subsidizes part of the installation costs. The incentive provision department can also partner with local environmental protection organizations and eco-related services to provide rewards that allow owners to participate in environmental protection activities. In this way, it is possible to promote environmental protection activities by providing rewards that increase the environmental awareness of vacant house owners.

[0045] The incentive provision department can also provide rewards to support vacant home owners' social contribution activities. For example, it can provide rewards for participating in volunteer activities or a donation matching program. The incentive provision department can also build a system to customize the rewards that owners can receive by participating in social contribution activities. For example, if an owner participates in local cleanup activities, special points can be awarded and the points can be exchanged for rewards. The incentive provision department can also partner with local NPOs and volunteer groups to provide rewards for owners to participate in social contribution activities. In this way, by providing rewards to support vacant home owners' social contribution activities, it is possible to promote the development of the local community.

[0046] The incentive provision unit can include partnerships with local shops and services in the incentive program to promote the revitalization of the local economy. For example, the incentive program can include partnerships with local shops and services to provide discount coupons that owners can use at local stores. For example, coupons that can be used at local supermarkets and restaurants can be issued. The incentive provision unit can also partner with local shops and services to provide benefits that allow owners to participate in local events and workshops. For example, tickets to local cultural events and sporting events can be provided. The incentive provision unit can also include local specialties and services in the incentive program to promote the revitalization of the local economy. For example, local agricultural products and crafts can be provided as benefits. In this way, by including partnerships with local shops and services in the incentive program, the revitalization of the local economy can be promoted.

[0047] The incentive provision unit can link the incentive program with community events and workshops in which vacant house owners participate. For example, by linking the incentive program with community events and workshops, owners can receive rewards by participating. For example, rewards can be provided for participating in local cleanup activities or renovation workshops. The incentive provision unit also builds a system that provides special incentives to owners who participate in community events and workshops. For example, points can be awarded to event participants, and the points can be exchanged for rewards. The incentive provision unit also encourages owners to actively participate in the local community through the incentive program. For example, rewards can be provided for participating in local exchange events or study sessions. In this way, by linking the incentive program with community events and workshops, it is possible to encourage vacant house owners to participate in the local community.

[0048] The matching unit uses generation AI to generate detailed information about the internal structure and facilities of vacant houses as a 3D model, which can be visually provided to consumers. For example, a system can be built in which generation AI is used to generate detailed information about the internal structure and facilities of vacant houses as a 3D model and provide this visually to consumers. For example, the floor plan and layout of the facilities of the vacant house are displayed in a 3D model. The matching unit also inputs photos and floor plans of the vacant house, and the generation AI automatically generates a 3D model based on that information. For example, the interior of the vacant house is visually provided in the form of a virtual tour. The matching unit also uses generation AI to generate a simulated 3D model of the vacant house after renovation and provide it to consumers. For example, a comparison before and after renovation is visually displayed in a 3D model. In this way, detailed information about the internal structure and facilities of vacant houses can be provided as a 3D model, providing visual information to consumers and making it easier for them to choose a property.

[0049] The matching unit can use generation AI to analyze a consumer's past search history and browsing history and make individually customized property proposals. For example, a system can be built using generation AI to analyze a consumer's past search history and browsing history and make individually customized property proposals. For example, the system can propose optimal properties based on the conditions searched in the past. The matching unit can also analyze a consumer's browsing history and make property proposals tailored to the consumer's preferences and needs. For example, the system can propose similar properties based on the characteristics of properties viewed in the past. The matching unit can also use generation AI to analyze a consumer's search history and browsing history in real time and develop a system that makes individually customized property proposals. For example, the system can propose properties based on the consumer's most recent search conditions. This can increase consumer satisfaction by analyzing a consumer's past search history and browsing history and making individually customized property proposals.

[0050] The matching department can add a function that allows buyers to tour properties in virtual reality (VR). For example, a VR tour function could be added to the matching platform, allowing buyers to tour properties in virtual reality. For example, a VR headset could be used to realistically experience the interior of the property. The matching department could also build a system in which a generation AI provides real-time guidance when buyers tour properties in VR. For example, the property's features and facilities could be explained in VR. The matching department could also develop a system that uses the VR tour function to allow buyers to experience a simulation of the property after renovation. For example, a visual comparison of the before and after renovation could be provided in VR. This allows buyers to tour properties in virtual reality, thereby improving the accuracy of property selection.

[0051] The matching department can add a chatbot function that allows consumers to ask questions about properties in real time. For example, a chatbot function can be added to the matching platform, allowing consumers to ask questions about properties in real time. For example, they can ask about detailed information about the property and the surrounding environment. The matching department can also develop a chatbot that uses a generation AI to answer consumers' questions in real time. For example, it can instantly answer questions about the property's facilities and contract terms. The matching department can also build a system in which, when consumers ask questions about properties using the chatbot function, the generation AI automatically provides relevant information. For example, it can display photos and floor plans of the property in response to the consumer's questions. This allows consumers to ask questions about properties in real time, thereby improving the accuracy of property selection.

[0052] The advice support unit can use the generation AI to generate simulated images and videos of the vacant house after renovation and provide them to the owner. For example, a system can be built that uses the generation AI to generate simulated images of the vacant house after renovation and provide them to the owner. For example, comparison images can be provided before and after renovation. The advice support unit can also input photos and floor plans of the vacant house, and the generation AI can automatically generate a simulated video of the house after renovation based on that information. For example, the renovation process can be visually provided in a video. The advice support unit can also use the generation AI to generate a simulated 3D model of the vacant house after renovation and provide it to the owner. For example, the 3D model can visually display the internal structure and equipment layout after renovation. This allows the owner to visually confirm the results of the renovation by providing simulated images and videos of the house after renovation.

[0053] The advice and support department can use generation AI to automatically generate a detailed list of materials and work required for renovation and provide it to the owner. For example, a system can be built that uses generation AI to automatically generate a detailed list of materials and work required for renovation. For example, a materials list based on the scale and content of the renovation can be provided. The advice and support department can also input the condition of the vacant house and the renovation plan, and the generation AI can automatically generate a list of the necessary materials and work based on that information. For example, it can provide a list of wall materials, flooring materials, and equipment. The advice and support department can also develop a system that uses generation AI to generate a detailed list of materials and work required for renovation in real time and provide it to the owner. For example, the list can be updated according to the progress of the renovation. This makes it easier for owners to plan their renovations by providing a detailed list of materials and work required for renovation.

[0054] The advice and support department can add a function that allows owners to check the progress of renovations in real time. For example, a progress check function can be added to a renovation advice and support system, allowing owners to check the progress of renovations in real time. For example, each renovation step can be displayed on a timeline. The advice and support department can also use generative AI to analyze the progress of renovations in real time and build a system that notifies owners. For example, emails and app notifications can be sent to owners according to the progress of renovations. The advice and support department can also develop a system that allows owners to check the progress of renovations in real time using the renovation progress check function and make changes or adjustments as needed. For example, adjusting the renovation plan according to the progress. This makes it easier for owners to understand the status of renovations by allowing them to check the progress of renovations in real time.

[0055] The advice and support department can add a chatbot function that allows owners to ask questions about renovations in real time. For example, a chatbot function can be added to a renovation advice and support system, allowing owners to ask questions about renovations in real time. For example, they can ask about renovation details and progress. The advice and support department can also use a generation AI to develop a chatbot that answers owners' questions in real time. For example, it can instantly answer questions about renovation materials and construction details. The advice and support department can also build a system in which, when owners ask questions about renovations using the chatbot function, the generation AI automatically provides relevant information. For example, it can display photos of the renovation and progress status in response to the owner's question. This allows owners to ask questions about renovations in real time, allowing them to instantly resolve their renovation-related concerns.

[0056] The processing flow of the first embodiment will be briefly explained below.

[0057] Step 1: The Incentives Department provides rental income and benefits to owners of vacant homes. For example, by renting out a vacant home for a certain period of time, tax exemptions and subsidies are offered. In addition, if the home is renovated and rented out, a subsidy is offered to cover part of the renovation costs. Furthermore, a program for generating rental income is provided, and the income is calculated and presented to the owner. Step 2: The matching unit uses AI to collect and analyze information on vacant homes and users, and then performs optimal matching. For example, information on the location, condition, price, and other aspects of vacant homes is registered in a database, and compared with the desired conditions of users. Using the generation AI, the desired conditions entered by the user are analyzed, and the most suitable vacant homes are proposed based on that information. Step 3: The Advisory Support Department provides advice and support regarding the renovation of vacant homes. For example, it analyzes the condition of the vacant home and surrounding market trends to propose renovation content and costs. It uses generative AI to analyze photos and floor plans of the vacant home and provides estimates of areas that need renovation and costs. Furthermore, it analyzes surrounding market trends to predict the rental and selling prices after renovation.

[0058] (Example 2) The comprehensive platform according to an embodiment of the present invention is a system that matches owners of vacant houses with those who wish to use them. As a result, the comprehensive platform can promote the effective use of vacant houses in areas that have a problem with vacant houses, thereby revitalizing the area.

[0059] A comprehensive platform according to an embodiment includes an incentive providing unit, a matching unit, and an advice and support unit. The incentive providing unit provides rental income and benefits to owners of vacant homes. For example, the incentive providing unit may offer tax reductions or subsidies for renting out a vacant home for a certain period of time. Furthermore, the incentive providing unit may offer benefits such as subsidizing part of the renovation costs if the owner renovates and rents out the vacant home. Furthermore, the incentive providing unit may provide a program for owners of vacant homes to earn rental income. For example, the incentive providing unit may calculate the income that can be earned by renting out the vacant home and present it to the owner. The matching unit uses AI to collect and analyze information about vacant homes and users to perform optimal matching. For example, the matching unit may register information about the location, condition, price, and other information about vacant homes in a database and compare it with the user's desired conditions. Furthermore, the matching unit may use a generation AI to analyze desired conditions entered by a user and suggest the most suitable vacant home based on the results. For example, if the user enters desired conditions such as "looking for a vacant home with a 3LDK in Tokyo," the generation AI may search the database for matching vacant homes and suggest the most suitable property. The advice and support unit provides advice and support regarding the renovation of vacant houses. For example, the advice and support unit analyzes the condition of the vacant house and surrounding market trends, and proposes the renovation content and costs. The advice and support unit also uses generative AI to analyze photos and floor plans of the vacant house and provide estimates of the areas that need renovation and the costs. Furthermore, the advice and support unit analyzes surrounding market trends to predict the rental and selling prices after renovation. As a result, the comprehensive platform according to the embodiment can promote the effective use of vacant houses and revitalize local areas. For example, vacant house owners can enjoy economic benefits by earning rental income, and it becomes easier for buyers to find the properties they want. The renovation advice and support system can also increase the value of vacant houses.

[0060] The incentive provision unit can analyze the past rental history and renovation history of vacant home owners and customize and provide optimal incentives. For example, the incentive provision unit registers the past rental history of vacant home owners in a database and customizes optimal incentives based on that data. For example, it analyzes the period and rent of past rentals and provides special benefits to owners who have rented out their homes for long periods of time. The incentive provision unit also analyzes renovation history and provides incentives based on the frequency and content of renovations. For example, an owner who has previously performed major renovations can be provided with a benefit that partially subsidizes the cost of the next renovation. The incentive provision unit also analyzes rental history and renovation history in an integrated manner and customizes incentives based on the owner's behavioral patterns. For example, an owner who frequently renovates and rents out their homes can be provided with a discount coupon for renovation materials. In this way, it is possible to increase the owner's motivation by analyzing the past rental history and renovation history of vacant home owners and providing optimal incentives.

[0061] The incentive providing unit can provide benefits that take into consideration the lifestyle, hobbies, and preferences of vacant home owners. For example, the incentive providing unit collects information about the lifestyle, hobbies, and preferences of vacant home owners through questionnaires and interviews, and customizes benefits based on that data. For example, a travel voucher is provided to an owner whose hobby is traveling. The incentive providing unit also builds a system that personalizes benefits based on the owner's hobby and preferences. For example, a discount coupon for gardening equipment is provided to an owner whose hobby is gardening. The incentive providing unit also partners with local stores and services to provide benefits that take into consideration the lifestyle, hobbies, and preferences of vacant home owners. For example, discount coupons for local restaurants and cafes are provided. In this way, the satisfaction of vacant home owners can be increased by providing benefits that take into consideration the lifestyle, hobbies, and preferences of vacant home owners.

[0062] The incentive providing unit can use the emotion estimation function to analyze the emotional state of the vacant home owner and propose incentives that elicit positive emotions. For example, the incentive providing unit uses the emotion estimation function to analyze the emotional state of the vacant home owner in real time and propose incentives that elicit positive emotions. For example, if the owner is feeling stressed, a relaxation-related benefit is provided. The incentive providing unit also builds a system that customizes benefits according to the owner's emotional state based on the emotion estimation data. For example, if the owner is feeling happy, a benefit that further amplifies the joy is provided. The incentive providing unit also uses the emotion estimation function to analyze the owner's emotional state and propose incentives in real time that elicit positive emotions. For example, if the owner is feeling anxious, a benefit that provides a sense of security is proposed. In this way, the emotional state of the vacant home owner can be analyzed and incentives that elicit positive emotions can be provided, thereby increasing the owner's motivation.

[0063] The incentive provision unit can include partnerships with local shops and services in the incentive program to promote the revitalization of the local economy. For example, the incentive provision unit can include partnerships with local shops and services in the incentive program to provide discount coupons that the owner can use at local stores. For example, the incentive provision unit can issue coupons that can be used at local supermarkets and restaurants. The incentive provision unit can also partner with local shops and services to provide benefits that allow the owner to participate in local events and workshops. For example, the incentive provision unit can provide tickets to local cultural events and sporting events. The incentive provision unit can also include local specialties and services in the incentive program to promote the revitalization of the local economy. For example, the incentive provision unit can offer local agricultural products and crafts as benefits. In this way, by including partnerships with local shops and services in the incentive program, the revitalization of the local economy can be promoted.

[0064] The incentive provision unit can link the incentive program with community events and workshops in which vacant house owners participate. For example, the incentive provision unit links the incentive program with community events and workshops so that owners can receive rewards by participating. For example, rewards are provided for participating in local cleanup activities or renovation workshops. The incentive provision unit also builds a system that provides special incentives to owners who participate in community events and workshops. For example, points are awarded to event participants, and the points can be exchanged for rewards. The incentive provision unit also encourages owners to actively participate in the local community through the incentive program. For example, rewards can be provided for participating in local exchange events or study sessions. In this way, by linking the incentive program with community events and workshops, it is possible to encourage vacant house owners to participate in the local community.

[0065] The incentive providing unit uses the emotion estimation function to monitor the emotions of vacant home owners when they receive incentives in real time, and can provide rewards at the optimal timing. For example, the incentive providing unit uses the emotion estimation function to monitor the emotions of vacant home owners when they receive incentives in real time, and builds a system to provide rewards at the optimal timing. For example, rewards are provided when the owner is feeling happy. The incentive providing unit also develops a system to provide rewards in real time according to the owner's emotional state based on the emotion estimation data. For example, if the owner is feeling stressed, a relaxation-related reward is provided. The incentive providing unit also uses the emotion estimation function to monitor the owner's emotional state, and provides rewards at the optimal timing to elicit positive emotions. For example, if the owner is feeling anxious, a reward that provides a sense of security is proposed. In this way, by monitoring the emotions of vacant home owners in real time and providing rewards at the optimal timing, it is possible to increase the owner's satisfaction.

[0066] The matching unit uses generation AI to generate detailed information about the internal structure and facilities of a vacant house as a 3D model, which can be visually provided to consumers. For example, the matching unit uses generation AI to build a system that generates detailed information about the internal structure and facilities of a vacant house as a 3D model and visually provides this information to consumers. For example, the floor plan and layout of the facilities of the vacant house are displayed in a 3D model. The matching unit also inputs photos and floor plans of the vacant house, and the generation AI automatically generates a 3D model based on that information. For example, the interior of the vacant house is visually provided in the form of a virtual tour. The matching unit also uses generation AI to generate a simulated 3D model of the vacant house after renovation and provides this to consumers. For example, a comparison before and after renovation is visually displayed in a 3D model. In this way, detailed information about the internal structure and facilities of a vacant house can be provided as a 3D model, providing visual information to consumers and making it easier for them to choose a property.

[0067] The matching unit can use generation AI to analyze a consumer's past search history and browsing history and make individually customized property proposals. For example, the matching unit uses generation AI to analyze a consumer's past search history and browsing history and build a system that makes individually customized property proposals. For example, it proposes optimal properties based on the conditions searched in the past. The matching unit also analyzes a consumer's browsing history and makes property proposals tailored to the consumer's preferences and needs. For example, it proposes similar properties based on the characteristics of properties viewed in the past. The matching unit also uses generation AI to analyze a consumer's search history and browsing history in real time and develop a system that makes individually customized property proposals. For example, it proposes properties based on the consumer's latest search conditions. In this way, by analyzing a consumer's past search history and browsing history and making individually customized property proposals, it is possible to increase consumer satisfaction.

[0068] The matching unit can use the emotion estimation function to analyze the emotional state of the consumer and make property suggestions that elicit positive emotions. The matching unit, for example, uses the emotion estimation function to analyze the emotional state of the consumer in real time and build a system that makes property suggestions that elicit positive emotions. For example, it prioritizes suggestions of properties that the consumer will find joyful. The matching unit also develops a system that makes property suggestions based on the emotional state of the consumer based on the emotion estimation data. For example, if the consumer is feeling stressed, it suggests properties that will help the consumer relax. The matching unit also monitors the emotional state of the consumer using the emotion estimation function and makes property suggestions in real time that elicit positive emotions. For example, if the consumer is feeling anxious, it suggests properties that provide a sense of security. In this way, the consumer's satisfaction can be increased by analyzing the emotional state of the consumer and making property suggestions that elicit positive emotions.

[0069] The matching department can add a function that allows consumers to tour properties in virtual reality (VR). For example, the matching department adds a VR tour function to the matching platform, allowing consumers to tour properties in virtual reality. For example, a VR headset can be used to realistically experience the interior of the property. The matching department also builds a system in which a generation AI provides real-time guidance when consumers tour properties in VR. For example, the property's features and facilities can be explained in VR. The matching department also develops a system that uses the VR tour function to allow consumers to experience a simulation of the property after renovation. For example, a visual comparison of the before and after renovation can be provided in VR. This allows consumers to tour properties in virtual reality, thereby improving the accuracy of property selection.

[0070] The matching unit can add a chatbot function that allows consumers to ask questions about properties in real time. For example, the matching unit adds a chatbot function to the matching platform, allowing consumers to ask questions about properties in real time. For example, consumers can ask questions about detailed information about the property and the surrounding environment. The matching unit also uses a generation AI to develop a chatbot that answers consumers' questions in real time. For example, it can immediately answer questions about the property's facilities and contract terms. The matching unit also builds a system in which, when consumers ask questions about properties using the chatbot function, the generation AI automatically provides relevant information. For example, it can display photos and floor plans of the property in response to the consumer's questions. This allows consumers to ask questions about properties in real time, thereby improving the accuracy of property selection.

[0071] The matching unit can use the emotion estimation function to monitor the emotions of consumers when they browse properties in real time and suggest the most suitable property. The matching unit, for example, uses the emotion estimation function to monitor the emotions of consumers when they browse properties in real time and builds a system that suggests the most suitable property. For example, it prioritizes suggesting properties that make the consumer feel excited or happy. The matching unit also develops a system that suggests properties based on the emotion estimation data according to the consumer's emotional state. For example, if the consumer is feeling stressed, it suggests properties that will help the consumer relax. The matching unit also uses the emotion estimation function to monitor the consumer's emotional state and suggest properties in real time that will elicit positive emotions. For example, if the consumer is feeling anxious, it suggests properties that will provide a sense of security. In this way, it is possible to increase consumer satisfaction by monitoring the consumer's emotions in real time and suggesting the most suitable property.

[0072] The advice support unit can use the generation AI to generate simulated images and videos of the vacant house after renovation and provide them to the owner. For example, the advice support unit builds a system that uses the generation AI to generate simulated images of the vacant house after renovation and provides them to the owner. For example, it provides comparison images before and after renovation. The advice support unit also inputs photos and floor plans of the vacant house, and the generation AI automatically generates a simulated video of the vacant house after renovation based on that information. For example, it provides a visual video of the renovation process. The advice support unit also uses the generation AI to generate a simulated 3D model of the vacant house after renovation and provides it to the owner. For example, it visually displays the internal structure and equipment layout after renovation in a 3D model. In this way, by providing simulated images and videos of the vacant house after renovation, the owner can visually confirm the results of the renovation.

[0073] The advice support unit can use generation AI to automatically generate a detailed list of materials and work required for renovation and provide it to the owner. For example, the advice support unit will build a system that uses generation AI to automatically generate a detailed list of materials and work required for renovation. For example, it will provide a materials list based on the scale and content of the renovation. The advice support unit will also input the condition of the vacant house and the renovation plan, and the generation AI will automatically generate a list of the necessary materials and work based on that information. For example, it will provide a list of wall materials, flooring materials, and equipment. The advice support unit will also develop a system that uses generation AI to generate a detailed list of materials and work required for renovation in real time and provide it to the owner. For example, it will update the list according to the progress of the renovation. This will make it easier for the owner to plan the renovation by providing a detailed list of materials and work required for the renovation.

[0074] The advice support unit can use the emotion estimation function to analyze the owner's emotional state and make renovation suggestions that elicit positive emotions. The advice support unit, for example, uses the emotion estimation function to build a system that analyzes the owner's emotional state in real time and makes renovation suggestions that elicit positive emotions. For example, it proposes renovation plans that will make the owner happy. The advice support unit also develops a system that makes renovation suggestions based on the owner's emotional state based on the emotion estimation data. For example, if the owner is feeling stressed, it proposes a renovation plan that will help the owner relax. The advice support unit also uses the emotion estimation function to monitor the owner's emotional state and make renovation suggestions in real time that will elicit positive emotions. For example, if the owner is feeling anxious, it proposes a renovation plan that will provide a sense of security. In this way, the owner's satisfaction can be increased by analyzing the owner's emotional state and making renovation suggestions that elicit positive emotions.

[0075] The advice and support unit can add a function that allows the owner to check the progress of the renovation in real time. For example, the advice and support unit adds a progress check function to a renovation advice and support system, allowing the owner to check the progress of the renovation in real time. For example, each renovation process is displayed on a timeline. The advice and support unit also uses generative AI to analyze the progress of the renovation in real time and builds a system that notifies the owner. For example, it sends emails or app notifications to the owner depending on the progress of the renovation. The advice and support unit also develops a system that allows the owner to check the progress of the renovation in real time using the renovation progress check function and make changes or adjustments as needed. For example, it adjusts the renovation plan depending on the progress. This makes it easier for the owner to understand the status of the renovation by being able to check the progress of the renovation in real time.

[0076] The advice and support unit can add a chatbot function that allows questions about renovations to be asked in real time. For example, the advice and support unit adds a chatbot function to a renovation advice and support system, allowing owners to ask questions about renovations in real time. For example, they can ask about renovation details and progress. The advice and support unit also uses a generation AI to develop a chatbot that answers owners' questions in real time. For example, it immediately answers questions about renovation materials and construction details. The advice and support unit also builds a system in which, when owners ask questions about renovations using the chatbot function, the generation AI automatically provides relevant information. For example, it displays photos of the renovation and progress status in response to the owner's question. This allows owners to ask questions about renovations in real time, allowing them to instantly resolve their renovation-related concerns.

[0077] The advice support unit uses the emotion estimation function to monitor the emotions of the owner when checking the progress of the renovation in real time and can provide optimal advice. For example, the advice support unit uses the emotion estimation function to monitor the emotions of the owner when checking the progress of the renovation in real time and builds a system that provides optimal advice. For example, if the owner is feeling anxious, advice that provides a sense of security is provided. The advice support unit also develops a system that provides renovation advice according to the owner's emotional state based on the emotion estimation data. For example, if the owner is feeling happy, advice that further amplifies the joy is provided. The advice support unit also uses the emotion estimation function to monitor the owner's emotional state and provide renovation advice in real time to elicit positive emotions. For example, if the owner is feeling stressed, advice related to relaxation is provided. In this way, the owner's emotions can be monitored in real time and optimal advice can be provided, thereby increasing the owner's satisfaction.

[0078] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0079] The incentive provision department can also provide benefits that take into consideration the health condition of vacant house owners. For example, it can provide coupons for health checkups or free tickets to fitness gyms. The incentive provision department can also build a system that customizes benefits that are useful for maintaining health based on the owner's health data. For example, if the owner has high blood pressure, it can provide discount coupons for health foods. The incentive provision department can also partner with local medical institutions and health-related services to provide benefits that allow owners to receive health checkups and health consultations. In this way, it is possible to support the maintenance of health of vacant house owners by providing benefits that take into consideration the owner's health condition.

[0080] The incentive provision department can also provide rewards to increase the environmental awareness of vacant house owners. For example, it can provide discount coupons for eco-friendly home appliances or rewards related to promoting the use of renewable energy. The incentive provision department can also build a system to customize rewards that owners can receive by taking environmentally friendly actions. For example, if an owner installs a solar power generation system, it can provide a reward that subsidizes part of the installation costs. The incentive provision department can also partner with local environmental protection organizations and eco-related services to provide rewards that allow owners to participate in environmental protection activities. In this way, it is possible to promote environmental protection activities by providing rewards that increase the environmental awareness of vacant house owners.

[0081] The incentive provision department can also provide rewards to support vacant home owners' social contribution activities. For example, it can provide rewards for participating in volunteer activities or a donation matching program. The incentive provision department can also build a system to customize the rewards that owners can receive by participating in social contribution activities. For example, if an owner participates in local cleanup activities, special points can be awarded and the points can be exchanged for rewards. The incentive provision department can also partner with local NPOs and volunteer groups to provide rewards for owners to participate in social contribution activities. In this way, by providing rewards to support vacant home owners' social contribution activities, it is possible to promote the development of the local community.

[0082] The incentive providing unit can use the emotion estimation function to analyze the emotional state of the vacant house owner and propose incentives that elicit positive emotions. For example, if the owner is feeling stressed, a relaxation-related benefit is provided. The incentive providing unit also builds a system that customizes benefits according to the owner's emotional state based on the emotion estimation data. For example, if the owner is feeling happy, a benefit that further amplifies the joy is provided. The incentive providing unit also uses the emotion estimation function to analyze the owner's emotional state and propose incentives in real time to elicit positive emotions. For example, if the owner is feeling anxious, a benefit that provides a sense of security is proposed. In this way, the emotional state of the vacant house owner can be analyzed and incentives that elicit positive emotions can be provided, thereby increasing the owner's motivation.

[0083] The incentive provision unit can include partnerships with local shops and services in the incentive program to promote the revitalization of the local economy. For example, the incentive program can include partnerships with local shops and services to provide discount coupons that owners can use at local stores. For example, coupons that can be used at local supermarkets and restaurants can be issued. The incentive provision unit can also partner with local shops and services to provide benefits that allow owners to participate in local events and workshops. For example, tickets to local cultural events and sporting events can be provided. The incentive provision unit can also include local specialties and services in the incentive program to promote the revitalization of the local economy. For example, local agricultural products and crafts can be provided as benefits. In this way, by including partnerships with local shops and services in the incentive program, the revitalization of the local economy can be promoted.

[0084] The incentive provision unit can link the incentive program with community events and workshops in which vacant house owners participate. For example, by linking the incentive program with community events and workshops, owners can receive rewards by participating. For example, rewards can be provided for participating in local cleanup activities or renovation workshops. The incentive provision unit also builds a system that provides special incentives to owners who participate in community events and workshops. For example, points can be awarded to event participants, and the points can be exchanged for rewards. The incentive provision unit also encourages owners to actively participate in the local community through the incentive program. For example, rewards can be provided for participating in local exchange events or study sessions. In this way, by linking the incentive program with community events and workshops, it is possible to encourage vacant house owners to participate in the local community.

[0085] The incentive provision unit uses the emotion estimation function to monitor the emotions of vacant home owners when they receive incentives in real time, and can provide rewards at the optimal timing. For example, a system is constructed that uses the emotion estimation function to monitor the emotions of vacant home owners when they receive incentives in real time, and provides rewards at the optimal timing. For example, a reward is provided when the owner is feeling happy. The incentive provision unit also develops a system that provides rewards in real time according to the owner's emotional state based on the emotion estimation data. For example, if the owner is feeling stressed, a relaxation-related reward is provided. The incentive provision unit also uses the emotion estimation function to monitor the owner's emotional state, and provides rewards at the optimal timing to elicit positive emotions. For example, if the owner is feeling anxious, a reward that provides a sense of security is proposed. In this way, by monitoring the emotions of vacant home owners in real time and providing rewards at the optimal timing, it is possible to increase the owner's satisfaction.

[0086] The matching unit uses generation AI to generate detailed information about the internal structure and facilities of vacant houses as a 3D model, which can be visually provided to consumers. For example, a system can be built in which generation AI is used to generate detailed information about the internal structure and facilities of vacant houses as a 3D model and provide this visually to consumers. For example, the floor plan and layout of the facilities of the vacant house are displayed in a 3D model. The matching unit also inputs photos and floor plans of the vacant house, and the generation AI automatically generates a 3D model based on that information. For example, the interior of the vacant house is visually provided in the form of a virtual tour. The matching unit also uses generation AI to generate a simulated 3D model of the vacant house after renovation and provide it to consumers. For example, a comparison before and after renovation is visually displayed in a 3D model. In this way, detailed information about the internal structure and facilities of vacant houses can be provided as a 3D model, providing visual information to consumers and making it easier for them to choose a property.

[0087] The matching unit can use generation AI to analyze a consumer's past search history and browsing history and make individually customized property proposals. For example, a system can be built using generation AI to analyze a consumer's past search history and browsing history and make individually customized property proposals. For example, the system can propose optimal properties based on the conditions searched in the past. The matching unit can also analyze a consumer's browsing history and make property proposals tailored to the consumer's preferences and needs. For example, the system can propose similar properties based on the characteristics of properties viewed in the past. The matching unit can also use generation AI to analyze a consumer's search history and browsing history in real time and develop a system that makes individually customized property proposals. For example, the system can propose properties based on the consumer's most recent search conditions. This can increase consumer satisfaction by analyzing a consumer's past search history and browsing history and making individually customized property proposals.

[0088] The matching unit can use the emotion estimation function to analyze the emotional state of the consumer and make property suggestions that elicit positive emotions. For example, a system is constructed that uses the emotion estimation function to analyze the emotional state of the consumer in real time and make property suggestions that elicit positive emotions. For example, properties that the consumer will find joyful are preferentially suggested. The matching unit also develops a system that makes property suggestions based on the emotional state of the consumer based on the emotion estimation data. For example, if the consumer is feeling stressed, a property that will help the consumer relax is suggested. The matching unit also monitors the emotional state of the consumer using the emotion estimation function and makes property suggestions in real time that elicit positive emotions. For example, if the consumer is feeling anxious, a property that provides a sense of security is suggested. In this way, the consumer's satisfaction can be increased by analyzing the emotional state of the consumer and making property suggestions that elicit positive emotions.

[0089] The matching department can add a function that allows buyers to tour properties in virtual reality (VR). For example, a VR tour function could be added to the matching platform, allowing buyers to tour properties in virtual reality. For example, a VR headset could be used to realistically experience the interior of the property. The matching department could also build a system in which a generation AI provides real-time guidance when buyers tour properties in VR. For example, the property's features and facilities could be explained in VR. The matching department could also develop a system that uses the VR tour function to allow buyers to experience a simulation of the property after renovation. For example, a visual comparison of the before and after renovation could be provided in VR. This allows buyers to tour properties in virtual reality, thereby improving the accuracy of property selection.

[0090] The matching department can add a chatbot function that allows consumers to ask questions about properties in real time. For example, a chatbot function can be added to the matching platform, allowing consumers to ask questions about properties in real time. For example, they can ask about detailed information about the property and the surrounding environment. The matching department can also develop a chatbot that uses a generation AI to answer consumers' questions in real time. For example, it can instantly answer questions about the property's facilities and contract terms. The matching department can also build a system in which, when consumers ask questions about properties using the chatbot function, the generation AI automatically provides relevant information. For example, it can display photos and floor plans of the property in response to the consumer's questions. This allows consumers to ask questions about properties in real time, thereby improving the accuracy of property selection.

[0091] The matching unit can use the emotion estimation function to monitor the emotions of consumers in real time when they browse properties and suggest the most suitable property. For example, a system can be constructed that uses the emotion estimation function to monitor the emotions of consumers in real time when they browse properties and suggest the most suitable property. For example, properties that make the consumer feel excited or happy can be preferentially suggested. The matching unit can also develop a system that suggests properties based on the emotion estimation data according to the consumer's emotional state. For example, if the consumer is feeling stressed, it can suggest properties that will help the consumer relax. The matching unit can also use the emotion estimation function to monitor the consumer's emotional state and suggest properties in real time that will elicit positive emotions. For example, if the consumer is feeling anxious, it can suggest properties that will provide a sense of security. In this way, it is possible to increase consumer satisfaction by monitoring the consumer's emotions in real time and suggesting the most suitable property.

[0092] The advice support unit can use the generation AI to generate simulated images and videos of the vacant house after renovation and provide them to the owner. For example, a system can be built that uses the generation AI to generate simulated images of the vacant house after renovation and provide them to the owner. For example, comparison images can be provided before and after renovation. The advice support unit can also input photos and floor plans of the vacant house, and the generation AI can automatically generate a simulated video of the house after renovation based on that information. For example, the renovation process can be visually provided in a video. The advice support unit can also use the generation AI to generate a simulated 3D model of the vacant house after renovation and provide it to the owner. For example, the 3D model can visually display the internal structure and equipment layout after renovation. This allows the owner to visually confirm the results of the renovation by providing simulated images and videos of the house after renovation.

[0093] The advice and support department can use generation AI to automatically generate a detailed list of materials and work required for renovation and provide it to the owner. For example, a system can be built that uses generation AI to automatically generate a detailed list of materials and work required for renovation. For example, a materials list based on the scale and content of the renovation can be provided. The advice and support department can also input the condition of the vacant house and the renovation plan, and the generation AI can automatically generate a list of the necessary materials and work based on that information. For example, it can provide a list of wall materials, flooring materials, and equipment. The advice and support department can also develop a system that uses generation AI to generate a detailed list of materials and work required for renovation in real time and provide it to the owner. For example, the list can be updated according to the progress of the renovation. This makes it easier for owners to plan their renovations by providing a detailed list of materials and work required for renovation.

[0094] The advice support unit can use the emotion estimation function to analyze the owner's emotional state and make renovation suggestions that elicit positive emotions. For example, a system is constructed that uses the emotion estimation function to analyze the owner's emotional state in real time and make renovation suggestions that elicit positive emotions. For example, a renovation plan that will make the owner happy is proposed. The advice support unit also develops a system that makes renovation suggestions based on the owner's emotional state based on the emotion estimation data. For example, if the owner is feeling stressed, a renovation plan that will help them relax is proposed. The advice support unit also uses the emotion estimation function to monitor the owner's emotional state and make renovation suggestions in real time that will elicit positive emotions. For example, if the owner is feeling anxious, a renovation plan that will provide a sense of security is proposed. In this way, the owner's satisfaction can be increased by analyzing the owner's emotional state and making renovation suggestions that elicit positive emotions.

[0095] The advice and support department can add a function that allows owners to check the progress of renovations in real time. For example, a progress check function can be added to a renovation advice and support system, allowing owners to check the progress of renovations in real time. For example, each renovation step can be displayed on a timeline. The advice and support department can also use generative AI to analyze the progress of renovations in real time and build a system that notifies owners. For example, emails and app notifications can be sent to owners according to the progress of renovations. The advice and support department can also develop a system that allows owners to check the progress of renovations in real time using the renovation progress check function and make changes or adjustments as needed. For example, adjusting the renovation plan according to the progress. This makes it easier for owners to understand the status of renovations by allowing them to check the progress of renovations in real time.

[0096] The advice and support department can add a chatbot function that allows owners to ask questions about renovations in real time. For example, a chatbot function can be added to a renovation advice and support system, allowing owners to ask questions about renovations in real time. For example, they can ask about renovation details and progress. The advice and support department can also use a generation AI to develop a chatbot that answers owners' questions in real time. For example, it can instantly answer questions about renovation materials and construction details. The advice and support department can also build a system in which, when owners ask questions about renovations using the chatbot function, the generation AI automatically provides relevant information. For example, it can display photos of the renovation and progress status in response to the owner's question. This allows owners to ask questions about renovations in real time, allowing them to instantly resolve their renovation-related concerns.

[0097] The advice support unit uses the emotion estimation function to monitor the emotions of the owner when checking the progress of the renovation in real time and can provide optimal advice. For example, a system is constructed that uses the emotion estimation function to monitor the emotions of the owner when checking the progress of the renovation in real time and provides optimal advice. For example, if the owner is feeling anxious, advice that provides a sense of security is provided. The advice support unit also develops a system that provides renovation advice based on the emotion estimation data according to the owner's emotional state. For example, if the owner is feeling happy, advice that will further amplify that joy. The advice support unit also uses the emotion estimation function to monitor the owner's emotional state and provide renovation advice in real time to elicit positive emotions. For example, if the owner is feeling stressed, advice related to relaxation is provided. In this way, the owner's emotions can be monitored in real time and optimal advice can be provided, thereby increasing the owner's satisfaction.

[0098] The processing flow of the second embodiment will be briefly explained below.

[0099] Step 1: The Incentives Department provides rental income and benefits to owners of vacant homes. For example, by renting out a vacant home for a certain period of time, tax exemptions and subsidies are offered. In addition, if the home is renovated and rented out, a subsidy is offered to cover part of the renovation costs. Furthermore, a program for generating rental income is provided, and the income is calculated and presented to the owner. Step 2: The matching unit uses AI to collect and analyze information on vacant homes and users, and then performs optimal matching. For example, information on the location, condition, price, and other aspects of vacant homes is registered in a database, and compared with the desired conditions of users. Using the generation AI, the desired conditions entered by the user are analyzed, and the most suitable vacant homes are proposed based on that information. Step 3: The Advisory Support Department provides advice and support regarding the renovation of vacant homes. For example, it analyzes the condition of the vacant home and surrounding market trends to propose renovation content and costs. It uses generative AI to analyze photos and floor plans of the vacant home and provides estimates of areas that need renovation and costs. Furthermore, it analyzes surrounding market trends to predict the rental and selling prices after renovation.

[0100] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0101] 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> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0102] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0103] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0104] 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.

[0105] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0106] 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.

[0107] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0108] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0109] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0110] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0111] 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.

[0112] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0113] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0114] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0115] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0116] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0117] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0118] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0119] 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.

[0120] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0121] 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.

[0122] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0123] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0124] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0125] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0126] 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.

[0127] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0128] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0129] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0130] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0131] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0132] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0133] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0134] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0135] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0136] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0137] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0138] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0139] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0140] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the 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.

[0141] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0142] 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.

[0143] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0144] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0145] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0146] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0147] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0148] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0149] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0150] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0151] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0152] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0153] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0154] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0155] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0156] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0157] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0158] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0159] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0160] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0161] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0162] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0163] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0164] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0165] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0166] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0167] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. An incentive provision department that provides rental income and benefits to vacant house owners, and The matching department utilizes AI to collect and analyze information on vacant houses and customers, and makes optimal matches. An advice and support department that provides advice and support regarding the renovation of vacant houses. A system characterized by:

2. The incentive providing unit: Analyze the rental and renovation history of the vacant home owner and customize the most suitable incentives to provide them.

2. The system of claim 1.

3. The incentive providing unit: Offer benefits that take into consideration the lifestyle and hobbies of the vacant home owner 2. The system of claim 1.

4. The incentive providing unit: Analyze the emotional state of the vacant house owner and propose incentives to elicit positive emotions 2. The system of claim 1.

5. The incentive providing unit: Incentive programs include partnerships with local businesses and services to stimulate local economies.

2. The system of claim 1.

6. The incentive providing unit: Link the incentive program to community events and workshops that involve the owners of the vacant homes.

2. The system of claim 1.

7. The incentive providing unit: Monitor the emotions of the vacant home owners when they receive incentives in real time and provide rewards at the optimal time.

2. The system of claim 1.

8. The matching unit Using generation AI, detailed information about the internal structure and facilities of the vacant house is generated as a 3D model, which is visually provided to the consumer.

2. The system of claim 1.

Images