System

Abstract

To perform processing from selection of a care facility, confirmation of an empty status and to exchanging information with the facility in an unitary manner, and to reduce a load of a family, in a system according to an embodiment.SOLUTION: A system according to an embodiment comprises: a reception unit; a proposal unit; a confirmation unit; and a communication unit. The reception unit inputs information of a residential area, age, annual income, and a care-need level. The proposal unit analyzes information input by the reception unit, and proposes a care facility on the basis of a state of a body of a user. The confirmation unit confirms an empty status of the facility proposed by the proposal unit. The communication unit exchanges information between itself and the facility confirmed by the confirmation unit.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

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

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

[0004] With conventional technology, selecting a nursing care facility, checking availability, and communicating with the facility were all cumbersome, placing a heavy burden on families.

[0005] The system of the embodiment aims to reduce the burden on families by centralizing the process from selecting nursing care facilities to checking availability and communicating with the facilities. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, a proposal unit, a confirmation unit, and a communication unit. The reception unit inputs information such as the area of ​​residence, age, annual income, and level of care required. The proposal unit analyzes the information input by the reception unit and proposes a care facility based on the user's physical condition. The confirmation unit confirms the availability of the facility proposed by the proposal unit. The communication unit communicates with the facility confirmed by the confirmation unit. Effect of the Invention

[0007] The system of the embodiment can reduce the burden on families by centralizing the selection of nursing care facilities, checking availability, and communicating with the facilities. [Brief description 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. [Diagram 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

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

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

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

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

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs and 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 code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or 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. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[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, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[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 (e.g., a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (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., voice and / or text). Display 40A displays visible information such as text and images according to instructions from processor 46. Speaker 40B outputs voice according to 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 Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

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

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

[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 the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[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 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. Also, the data processing device 12 may be a server device, or may be a terminal device (e.g., a mobile phone, a robot, a home appliance, etc.) owned by a user. Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The nursing care facility suggestion system according to the embodiment of the present invention is a system that allows users to check the availability of nursing care facilities and the like by inputting information such as the residential area, age, annual income, and level of care required. In this system, the user inputs information such as the residential area, age, annual income, and level of care required, and the system analyzes the input information to suggest appropriate facilities such as geriatric health facilities, nursing care hospitals, and special nursing homes for the elderly based on the user's physical condition. Furthermore, the system checks the availability of the proposed facilities and communicates with the picked facilities to reduce the burden on the family. If it is difficult to enter a facility, the system investigates and proposes systems and subsidies available in each local government, and in the case of elderly people, explains using a voice system. For example, a user inputs information such as the residential area, age, annual income, and level of care required. For example, if a 75-year-old man living in Tokyo has an annual income of 3 million yen and a level of care required of 3, this information is input into the system. Next, the system analyzes the input information. The system proposes appropriate facilities such as geriatric health facilities, nursing care hospitals, and special nursing homes for the elderly based on the user's physical condition. For example, if the level of care required is 3, it is determined that a special nursing home for the elderly is appropriate. Furthermore, the system checks the availability of the proposed facility. For example, the system checks the availability of a special nursing home for the elderly, and if there is availability, it proposes that facility. If there is no availability, it proposes another facility. The system also communicates with the picked facility. For example, it contacts the facility's person in charge, arranges a tour date, and proceeds with the admission procedure. This reduces the burden on the family. If it is difficult to enter the facility, the system checks and proposes systems and subsidies available in each local government. For example, it proposes how to use home nursing care services and nursing care insurance. In the case of elderly people, an explanation is given using a voice system. For example, it explains by voice, "By using home nursing care services, you can receive support for daily life." In this way, the present invention is a system that collectively checks the availability of nursing care facilities, etc., proposes an appropriate facility, and reduces the burden on the family. As a result, the nursing care facility suggestion system can reduce the burden on the family by proposing an appropriate nursing care facility based on the user's information, checking the availability, and interacting with the facility.

[0029] The nursing care facility suggestion system according to the embodiment includes a reception unit, a proposal unit, a confirmation unit, and a contact unit. The reception unit inputs information such as a residential area, age, annual income, and level of care required. For example, if a user is a 75-year-old male living in Tokyo, has an annual income of 3 million yen, and is level of care required, this information can be input into the system. The proposal unit analyzes the information input by the reception unit and proposes an appropriate nursing care facility based on the user's physical condition. For example, if the level of care required is 3, it is determined that a special nursing home is appropriate. The proposal unit uses a generation AI to analyze the user's physical condition and proposes an appropriate facility. For example, the generation AI receives a prompt saying "Please propose a facility suitable for a user with a level of care required of 3," and proposes an appropriate facility. The confirmation unit checks the availability of the facility proposed by the proposal unit. For example, it checks the availability of a special nursing home, and if there is availability, it proposes the facility. The confirmation unit can access a database of facilities to check availability in real time. The contact unit exchanges with the facility confirmed by the confirmation unit. For example, the user contacts the facility staff to arrange a tour schedule and proceed with the admission procedure. The communication unit can contact the facility staff to arrange a tour schedule. As a result, the nursing care facility proposal system according to the embodiment can reduce the burden on the family by proposing an appropriate nursing care facility based on the user's information, checking the availability, and interacting with the facility. A part or all of the above-mentioned processing in the proposal unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the proposal unit can input the user's physical condition into the generation AI and cause the generation AI to execute the proposal of an appropriate facility. A part or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the availability of the facility into the generation AI and cause the generation AI to execute the confirmation of the availability. A part or all of the above-mentioned processing in the communication unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the communication unit can input the interaction with the facility staff into the generation AI and cause the generation AI to execute the adjustment of the interaction.

[0030] The reception unit inputs information such as residential area, age, annual income, and level of care required. For example, if the user is a 75-year-old man living in Tokyo, has an annual income of 3 million yen, and is level 3 in care required, this information can be input into the system. Specifically, the user inputs this information through a dedicated interface. The interface is designed to be easy for users to operate, and allows them to select information using input forms and drop-down menus. For example, residential area can be selected at the prefecture or city / ward / town / village level, and age is automatically calculated by inputting the date of birth. Annual income can be selected in a range or a specific amount, and level of care required can be selected based on the results of nursing care certification. This allows the reception unit to accurately collect detailed information about the user and provide data necessary for subsequent processing. In addition, the reception unit also has a function to check the consistency of the input information, and if there is a deficiency or error, notify the user and encourage correction. For example, if the relationship between age and level of care required is unnatural, or if the annual income is extremely high or low, a confirmation message is displayed and the user is asked to re-enter the information. This allows the reception unit to collect reliable data and improve the accuracy of the entire system.

[0031] The suggestion unit analyzes the information input by the reception unit and suggests an appropriate nursing facility based on the user's physical condition. For example, if the level of care required is 3, it is determined that a special nursing home is appropriate. The suggestion unit uses the generation AI to analyze the user's physical condition and suggest an appropriate facility. Specifically, the generation AI receives a prompt saying "Please suggest a facility suitable for a user with a level of care required of 3," and suggests an appropriate facility. The generation AI selects the facility that is most suitable for the user's condition based on past data and statistical information. For example, the generation AI comprehensively evaluates information such as the level of care required, age, residential area, and annual income, and also takes into account the reputation and service content of the facility in a specific area. In addition, the generation AI can reflect the individual needs and wishes of the user. For example, if a specific medical service is required or if there is a desire to continue living in a specific area, the system preferentially suggests facilities that meet those conditions. This allows the suggestion unit to suggest the optimal nursing facility for the user with high accuracy. The suggestion unit also has an interface for presenting the proposal content to the user in an easy-to-understand manner. For example, the suggestion unit displays detailed information, photos, user reviews, etc. of the proposed facility, making it easier for the user to compare and consider. This allows the suggestion unit to increase user satisfaction and support the selection of an appropriate facility.

[0032] The confirmation unit checks the availability of the facilities proposed by the proposal unit. For example, it checks the availability of special nursing homes for the elderly, and if there is availability, it proposes the facility. The confirmation unit can access the facility database to check the availability in real time. Specifically, the confirmation unit uses an API to link with the database of each facility and obtain the latest availability. This makes it possible to quickly check whether the proposed facility is actually available. In addition, the confirmation unit can obtain not only the availability but also detailed information such as the facility's terms of use, fees, and service contents, and provide them to the user. For example, if a specific facility is fully booked, it is possible to propose a similar facility in the vicinity as an alternative. The confirmation unit can use the generation AI to automate and streamline the availability confirmation process. For example, the generation AI can be input with a prompt such as "Please check the availability of facilities suitable for users with a care level of 3 in a specific area," and the generation AI can automatically check the availability of multiple facilities and return the results. In this way, the confirmation unit can provide the user with quick and accurate information and support the selection of an appropriate facility.

[0033] The communication unit communicates with the facility confirmed by the confirmation unit. For example, the communication unit contacts the facility's staff to arrange a tour date and proceed with the admission procedure. The communication unit can contact the facility's staff to arrange a tour date. Specifically, the communication unit informs the facility's staff of the user's desired tour date and time, and arranges a date and time that suits both parties. The communication unit can also provide the user with information such as documents and belongings required for the tour, and precautions. Furthermore, the communication unit also provides support for the admission procedure. For example, the communication unit supports the preparation and submission of necessary documents, confirmation of contract contents, and payment procedures for initial fees. The communication unit can use the generation AI to streamline these communication and adjustment processes. For example, the generation AI can be input with a prompt such as "Please arrange a tour date for a specific facility," and the generation AI can automatically contact the facility's staff and arrange the tour date. In this way, the communication unit can provide the user with quick and efficient support and smoothly proceed with a series of processes from facility selection to admission procedures. As a result, the communication unit can reduce the user's burden and provide an environment in which the user can use the nursing care facility with peace of mind.

[0034] The suggestion unit can suggest facilities such as a geriatric health facility, a nursing hospital, and a special nursing home for the elderly based on the user's physical condition. The suggestion unit, for example, analyzes the user's physical condition and suggests an appropriate facility. For example, if the level of care required is 3, it is determined that a special nursing home for the elderly is appropriate. The suggestion unit can also analyze the user's physical condition and suggest an appropriate facility using a generation AI. For example, the generation AI receives a prompt saying "Please suggest a facility suitable for a user with a level of care required of 3" and suggests an appropriate facility. This makes it possible to select an optimal nursing facility by suggesting an appropriate facility according to the user's physical condition. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the suggestion unit can input the user's physical condition to the generation AI and cause the generation AI to execute the suggestion of an appropriate facility.

[0035] The confirmation unit can access the facility database and check the availability in real time. The confirmation unit, for example, accesses the facility database and checks the availability in real time. For example, the confirmation unit checks the availability of a special nursing home, and if there is availability, suggests the facility. The confirmation unit can access the facility database and check the availability in real time. This makes it possible to provide the latest information by checking the availability in real time. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the availability of the facility to the generation AI and cause the generation AI to check the availability.

[0036] The communication unit can contact a person in charge of the facility and adjust the schedule for the tour. The communication unit can, for example, contact a person in charge of the facility and adjust the schedule for the tour. For example, the communication unit can contact a person in charge of a special nursing home and adjust the schedule for the tour. The communication unit can contact a person in charge of the facility and adjust the schedule for the tour. This allows the user to directly check the facility by adjusting the schedule for the tour. Some or all of the above-mentioned processing in the communication unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the communication unit can input interactions with the person in charge of the facility into the generation AI and have the generation AI execute the adjustment of the interactions.

[0037] The liaison unit can contact the person in charge of the facility and proceed with the move-in procedures. The liaison unit can, for example, contact the person in charge of the facility and proceed with the move-in procedures. For example, the liaison unit can contact the person in charge of a special nursing home and proceed with the move-in procedures. The liaison unit can contact the person in charge of the facility and proceed with the move-in procedures. This allows for smooth move-in by proceeding with the move-in procedures. Some or all of the above-mentioned processing in the liaison unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the liaison unit can input interactions with the person in charge of the facility into the generation AI and have the generation AI coordinate the interactions.

[0038] The proposal unit can propose systems and subsidies available in each local government when it is difficult to enter a facility. The proposal unit, for example, proposes systems and subsidies available in each local government when it is difficult to enter a facility. For example, it proposes methods of using home nursing care services and nursing care insurance. The proposal unit can propose systems and subsidies available in each local government when it is difficult to enter a facility. This makes it possible to support the user's life by proposing other support measures even when it is difficult to enter a facility. Some or all of the above-mentioned processing in the proposal unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the proposal unit can input system and subsidy information of each local government into the generation AI and cause the generation AI to execute appropriate proposals.

[0039] In the case of an elderly person, the suggestion unit can use a voice system to provide an explanation. For example, in the case of an elderly person, the suggestion unit uses a voice system to provide an explanation. For example, the suggestion unit explains by voice, "By using home care services, you can receive support for your daily life." In the case of an elderly person, the suggestion unit can use a voice system to provide an explanation. This helps the elderly person understand by providing an explanation by voice. A part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the suggestion unit can input the voice system into the generation AI and cause the generation AI to execute the voice explanation.

[0040] The reception unit can analyze the user's past input history and select the optimal input method. For example, the reception unit preferentially suggests an input method (such as voice or text) that the user has frequently used in the past. For example, the reception unit predicts and suggests an input method to be used in a specific time period from the user's past input history. In addition, the reception unit can automatically complete input items based on information previously input by the user. This allows the optimal input method to be selected based on the past input history, thereby improving user convenience. A part or all of the above-mentioned processing in the reception unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the reception unit can input the user's past input history to the generation AI and cause the generation AI to select the optimal input method.

[0041] The reception unit can customize the input items based on the user's current living situation and field of interest when inputting information. The reception unit customizes the input items so that the user inputs only necessary information based on the user's current living situation. For example, based on the user's field of interest, related input items are preferentially displayed. The input items can also be automatically adjusted based on the user's living situation and field of interest. This can improve the efficiency of input by providing input items according to the user's living situation and field of interest. A part or all of the above-mentioned processing in the reception unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the reception unit can input the user's living situation and field of interest into the generation AI and cause the generation AI to customize the input items.

[0042] The reception unit can preferentially input highly relevant information in consideration of the user's geographical location information when inputting information. For example, the reception unit preferentially inputs information on nearby nursing care facilities based on the user's current location. For example, based on the user's geographical location information, related local government systems and subsidy information are preferentially input. In addition, optimal input items can be automatically displayed in consideration of the user's geographical location information. This allows highly relevant information to be preferentially input by considering the user's geographical location information. Part or all of the above-mentioned processing in the reception unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the reception unit can input the user's geographical location information to the generation AI and cause the generation AI to execute the input of highly relevant information.

[0043] The reception unit can analyze the user's social media activity and input related information when inputting information. For example, the reception unit automatically inputs information on nursing facilities of interest from the user's social media activity. For example, based on the user's social media activity, related local government systems and subsidy information can be input. In addition, the reception unit can analyze the user's social media activity and suggest optimal input items. In this way, by analyzing social media activity, information related to the user can be efficiently input. Some or all of the above-mentioned processing in the reception unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the reception unit can input the user's social media activity to the generation AI and cause the generation AI to input related information.

[0044] The suggestion unit can adjust the level of detail of the proposal based on the user's physical condition at the time of proposal. For example, when the user's physical condition is poor, the suggestion unit makes a proposal including detailed information. For example, when the user's physical condition is good, the suggestion unit makes a concise proposal. In addition, the suggestion unit can adjust the optimal level of detail of the proposal based on the user's physical condition. This allows appropriate information to be provided by adjusting the level of detail of the proposal according to the user's physical condition. A part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the suggestion unit can input the user's physical condition to the generation AI and cause the generation AI to adjust the level of detail of the proposal.

[0045] At the time of proposal, the suggestion unit can suggest the optimal facility by referring to the user's past nursing facility use history. The suggestion unit, for example, suggests the optimal facility based on information on nursing facilities used by the user in the past. For example, it suggests related facilities from the user's past nursing facility use history. It is also possible to analyze the user's past nursing facility use history and suggest the most appropriate facility. As a result, it is possible to provide the user with the optimal option by suggesting the optimal facility based on the past use history. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the suggestion unit can input the user's past nursing facility use history into the generation AI and cause the generation AI to execute the proposal of the optimal facility.

[0046] The suggestion unit can suggest the most suitable facility by considering the geographical location information of the user at the time of suggestion. The suggestion unit, for example, suggests a nearby nursing care facility based on the user's current location. For example, based on the user's geographical location information, related local government systems and subsidy information are suggested. In addition, the most suitable facility can be automatically suggested by considering the user's geographical location information. In this way, by considering the user's geographical location information, an appropriate nearby facility can be suggested. A part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the suggestion unit can input the user's geographical location information to the generation AI and cause the generation AI to suggest the most suitable facility.

[0047] At the time of proposal, the suggestion unit can analyze the user's social media activity and propose related facilities. The suggestion unit, for example, proposes nursing care facilities of interest from the user's social media activity. For example, based on the user's social media activity, the suggestion unit proposes related local government systems and support information. The suggestion unit can also analyze the user's social media activity and propose optimal facilities. In this way, by analyzing social media activity, it is possible to efficiently propose facilities related to the user. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the suggestion unit can input the user's social media activity into the generation AI and cause the generation AI to execute the proposal of related facilities.

[0048] The confirmation unit can make a prediction by referring to the facility's past availability data when checking availability. The confirmation unit, for example, predicts the current availability based on the facility's past availability data. For example, the confirmation unit analyzes the facility's past availability data and predicts future availability. In addition, the confirmation unit can provide an optimal confirmation method by referring to the facility's past availability data. This makes it possible to provide a more accurate availability by making a prediction based on the past availability data. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the facility's past availability data into the generation AI and cause the generation AI to execute an availability prediction.

[0049] The confirmation unit can adjust the level of detail of the confirmation based on the service content provided by the facility when confirming availability. For example, when the service content provided by the facility is large, the confirmation unit provides a detailed confirmation method. For example, when the service content provided by the facility is small, the confirmation unit provides a simple confirmation method. The confirmation unit can also adjust the optimal confirmation method based on the service content provided by the facility. This makes it possible to provide appropriate information by adjusting the level of detail of the confirmation according to the service content provided by the facility. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the service content provided by the facility to the generation AI and cause the generation AI to adjust the level of detail of the confirmation.

[0050] The confirmation unit can check availability while taking into consideration the geographical distribution of facilities. For example, the confirmation unit preferentially checks availability of nearby facilities based on the geographical distribution of the facilities. For example, an optimal checking method is provided while taking into consideration the geographical distribution of the facilities. Also, availability can be checked by referring to the geographical distribution of the facilities. As a result, availability of nearby facilities can be checked preferentially by taking into consideration the geographical distribution of the facilities. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the geographical distribution of the facilities to the generation AI and cause the generation AI to check availability.

[0051] The confirmation unit can improve the accuracy of confirmation by referring to literature related to the facility when checking availability. The confirmation unit improves the accuracy of confirmation of availability, for example, based on literature related to the facility. For example, the confirmation unit provides an optimal confirmation method by referring to literature related to the facility. The confirmation unit can also analyze literature related to the facility and improve the accuracy of confirmation of availability. As a result, the accuracy of confirmation of availability can be improved by referring to the related literature. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input literature related to the facility into the generation AI and cause the generation AI to improve the confirmation accuracy.

[0052] The communication unit can select the optimal contact method by referring to the past response history of the facility person in charge at the time of contact. For example, the communication unit preferentially selects a contact method that the facility person in charge has responded to quickly in the past. For example, the communication unit proposes the optimal contact method based on the past response history of the facility person in charge. In addition, the communication unit can analyze the past response history of the facility person in charge and select the most effective contact method. As a result, effective communication is possible by selecting the optimal contact method based on the past response history. Part or all of the above-mentioned processing in the communication unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the communication unit can input the past response history of the facility person in charge into the generation AI and cause the generation AI to select the optimal contact method.

[0053] The contact unit can adjust the level of detail of the contact by referring to the user's past contact history at the time of contact. For example, if the user has requested detailed contact in the past, the contact unit contacts the user including detailed information. For example, if the user has requested brief contact in the past, the contact unit contacts the user including brief information. The contact unit can also adjust the optimal level of detail of the contact based on the user's past contact history. This allows optimal contact for the user by adjusting the level of detail of the contact based on the past contact history. A part or all of the above-mentioned processing in the contact unit may be performed using, for example, a generation AI, or may be performed without using the generation AI. For example, the contact unit can input the user's past contact history into the generation AI and cause the generation AI to adjust the level of detail of the contact.

[0054] The contact unit can select the optimal contact method in consideration of the geographical location information of the facility at the time of contact. The contact unit selects a quick contact method for nearby facilities based on, for example, the geographical location information of the facility. For example, the contact unit proposes an optimal contact method in consideration of the geographical location information of the facility. The optimal contact method can also be selected by referring to the geographical location information of the facility. This makes it possible to quickly contact nearby facilities by considering the geographical location information of the facility. Some or all of the above-mentioned processing in the contact unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the contact unit can input the geographical location information of the facility to the generation AI and cause the generation AI to select the optimal contact method.

[0055] At the time of contact, the contact unit can analyze the facility's social media activity and suggest a means of contact. The contact unit, for example, suggests the optimal means of contact from the facility's social media activity. For example, the contact unit selects an effective means of contact based on the facility's social media activity. The contact unit can also analyze the facility's social media activity and suggest the optimal means of contact. In this way, the optimal means of contact can be suggested by analyzing social media activity. Some or all of the above-mentioned processing in the contact unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the contact unit can input the facility's social media activity into the generation AI and have the generation AI execute the suggestion of a means of contact.

[0056] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0057] The suggestion unit can suggest facilities such as a geriatric health facility, a nursing hospital, and a special nursing home for the elderly based on the user's physical condition. The suggestion unit, for example, analyzes the user's physical condition and suggests an appropriate facility. For example, if the level of care required is 3, it is determined that a special nursing home for the elderly is appropriate. The suggestion unit can also analyze the user's physical condition and suggest an appropriate facility using a generation AI. For example, the generation AI receives a prompt saying "Please suggest a facility suitable for a user with a level of care required of 3" and suggests an appropriate facility. This makes it possible to select an optimal nursing facility by suggesting an appropriate facility according to the user's physical condition. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the suggestion unit can input the user's physical condition to the generation AI and cause the generation AI to execute the suggestion of an appropriate facility.

[0058] The confirmation unit can access the facility database and check the availability in real time. The confirmation unit, for example, accesses the facility database and checks the availability in real time. For example, the confirmation unit checks the availability of a special nursing home, and if there is availability, suggests the facility. The confirmation unit can access the facility database and check the availability in real time. This makes it possible to provide the latest information by checking the availability in real time. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the availability of the facility to the generation AI and cause the generation AI to check the availability.

[0059] The communication unit can contact a person in charge of the facility and adjust the schedule for the tour. The communication unit can, for example, contact a person in charge of the facility and adjust the schedule for the tour. For example, the communication unit can contact a person in charge of a special nursing home and adjust the schedule for the tour. The communication unit can contact a person in charge of the facility and adjust the schedule for the tour. This allows the user to directly check the facility by adjusting the schedule for the tour. Some or all of the above-mentioned processing in the communication unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the communication unit can input interactions with the person in charge of the facility into the generation AI and have the generation AI execute the adjustment of the interactions.

[0060] The liaison unit can contact the person in charge of the facility and proceed with the move-in procedures. The liaison unit can, for example, contact the person in charge of the facility and proceed with the move-in procedures. For example, the liaison unit can contact the person in charge of a special nursing home and proceed with the move-in procedures. The liaison unit can contact the person in charge of the facility and proceed with the move-in procedures. This allows for smooth move-in by proceeding with the move-in procedures. Some or all of the above-mentioned processing in the liaison unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the liaison unit can input interactions with the person in charge of the facility into the generation AI and have the generation AI coordinate the interactions.

[0061] The proposal unit can propose systems and subsidies available in each local government when it is difficult to enter a facility. The proposal unit, for example, proposes systems and subsidies available in each local government when it is difficult to enter a facility. For example, it proposes methods of using home nursing care services and nursing care insurance. The proposal unit can propose systems and subsidies available in each local government when it is difficult to enter a facility. This makes it possible to support the user's life by proposing other support measures even when it is difficult to enter a facility. Some or all of the above-mentioned processing in the proposal unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the proposal unit can input system and subsidy information of each local government into the generation AI and cause the generation AI to execute appropriate proposals.

[0062] The process flow of the first embodiment will be briefly described below.

[0063] Step 1: The reception unit inputs information such as the area of ​​residence, age, annual income, level of care required, etc. For example, if the user is a 75-year-old man living in Tokyo, with an annual income of 3 million yen and a level of care required of 3, this information can be entered into the system. Step 2: The suggestion unit analyzes the information entered by the reception unit and suggests an appropriate nursing care facility based on the user's physical condition. For example, if the level of care required is 3, it is determined that a special nursing home is appropriate. The suggestion unit uses the generation AI to analyze the user's physical condition and suggests an appropriate facility. For example, the generation AI receives a prompt saying, "Please suggest a facility suitable for a user with a level of care required of 3," and suggests an appropriate facility. Step 3: The confirmation unit checks the availability of the facility proposed by the proposal unit. For example, the confirmation unit checks the availability of a special nursing home for the elderly, and if there is availability, proposes the facility. The confirmation unit can access the database of facilities to check the availability in real time. Step 4: The Liaison Department communicates with the facility confirmed by the Confirmation Department. For example, the Liaison Department may contact the facility's staff to arrange a tour date or to proceed with the move-in procedure. The Liaison Department may contact the facility's staff to arrange a tour date.

[0064] (Example 2) The nursing care facility suggestion system according to the embodiment of the present invention is a system that allows users to check the availability of nursing care facilities and the like by inputting information such as the residential area, age, annual income, and level of care required. In this system, the user inputs information such as the residential area, age, annual income, and level of care required, and the system analyzes the input information to suggest appropriate facilities such as geriatric health facilities, nursing care hospitals, and special nursing homes for the elderly based on the user's physical condition. Furthermore, the system checks the availability of the proposed facilities and communicates with the picked facilities to reduce the burden on the family. If it is difficult to enter a facility, the system investigates and proposes systems and subsidies available in each local government, and in the case of elderly people, explains using a voice system. For example, a user inputs information such as the residential area, age, annual income, and level of care required. For example, if a 75-year-old man living in Tokyo has an annual income of 3 million yen and a level of care required of 3, this information is input into the system. Next, the system analyzes the input information. The system proposes appropriate facilities such as geriatric health facilities, nursing care hospitals, and special nursing homes for the elderly based on the user's physical condition. For example, if the level of care required is 3, it is determined that a special nursing home for the elderly is appropriate. Furthermore, the system checks the availability of the proposed facility. For example, the system checks the availability of a special nursing home for the elderly, and if there is availability, it proposes that facility. If there is no availability, it proposes another facility. The system also communicates with the picked facility. For example, it contacts the facility's person in charge, arranges a tour date, and proceeds with the admission procedure. This reduces the burden on the family. If it is difficult to enter the facility, the system checks and proposes systems and subsidies available in each local government. For example, it proposes how to use home nursing care services and nursing care insurance. In the case of elderly people, an explanation is given using a voice system. For example, it explains by voice, "By using home nursing care services, you can receive support for daily life." In this way, the present invention is a system that collectively checks the availability of nursing care facilities, etc., proposes an appropriate facility, and reduces the burden on the family. As a result, the nursing care facility suggestion system can reduce the burden on the family by proposing an appropriate nursing care facility based on the user's information, checking the availability, and interacting with the facility.

[0065] The nursing care facility suggestion system according to the embodiment includes a reception unit, a proposal unit, a confirmation unit, and a contact unit. The reception unit inputs information such as a residential area, age, annual income, and level of care required. For example, if a user is a 75-year-old male living in Tokyo, has an annual income of 3 million yen, and is level of care required, this information can be input into the system. The proposal unit analyzes the information input by the reception unit and proposes an appropriate nursing care facility based on the user's physical condition. For example, if the level of care required is 3, it is determined that a special nursing home is appropriate. The proposal unit uses a generation AI to analyze the user's physical condition and proposes an appropriate facility. For example, the generation AI receives a prompt saying "Please propose a facility suitable for a user with a level of care required of 3," and proposes an appropriate facility. The confirmation unit checks the availability of the facility proposed by the proposal unit. For example, it checks the availability of a special nursing home, and if there is availability, it proposes the facility. The confirmation unit can access a database of facilities to check availability in real time. The contact unit exchanges with the facility confirmed by the confirmation unit. For example, the user contacts the facility staff to arrange a tour schedule and proceed with the admission procedure. The communication unit can contact the facility staff to arrange a tour schedule. As a result, the nursing care facility proposal system according to the embodiment can reduce the burden on the family by proposing an appropriate nursing care facility based on the user's information, checking the availability, and interacting with the facility. A part or all of the above-mentioned processing in the proposal unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the proposal unit can input the user's physical condition into the generation AI and cause the generation AI to execute the proposal of an appropriate facility. A part or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the availability of the facility into the generation AI and cause the generation AI to execute the confirmation of the availability. A part or all of the above-mentioned processing in the communication unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the communication unit can input the interaction with the facility staff into the generation AI and cause the generation AI to execute the adjustment of the interaction.

[0066] The reception unit inputs information such as residential area, age, annual income, and level of care required. For example, if the user is a 75-year-old man living in Tokyo, has an annual income of 3 million yen, and is level 3 in care required, this information can be input into the system. Specifically, the user inputs this information through a dedicated interface. The interface is designed to be easy for users to operate, and allows them to select information using input forms and drop-down menus. For example, residential area can be selected at the prefecture or city / ward / town / village level, and age is automatically calculated by inputting the date of birth. Annual income can be selected in a range or a specific amount, and level of care required can be selected based on the results of nursing care certification. This allows the reception unit to accurately collect detailed information about the user and provide data necessary for subsequent processing. In addition, the reception unit also has a function to check the consistency of the input information, and if there is a deficiency or error, notify the user and encourage correction. For example, if the relationship between age and level of care required is unnatural, or if the annual income is extremely high or low, a confirmation message is displayed and the user is asked to re-enter the information. This allows the reception unit to collect reliable data and improve the accuracy of the entire system.

[0067] The suggestion unit analyzes the information input by the reception unit and suggests an appropriate nursing facility based on the user's physical condition. For example, if the level of care required is 3, it is determined that a special nursing home is appropriate. The suggestion unit uses the generation AI to analyze the user's physical condition and suggest an appropriate facility. Specifically, the generation AI receives a prompt saying "Please suggest a facility suitable for a user with a level of care required of 3," and suggests an appropriate facility. The generation AI selects the facility that is most suitable for the user's condition based on past data and statistical information. For example, the generation AI comprehensively evaluates information such as the level of care required, age, residential area, and annual income, and also takes into account the reputation and service content of the facility in a specific area. In addition, the generation AI can reflect the individual needs and wishes of the user. For example, if a specific medical service is required or if there is a desire to continue living in a specific area, the system preferentially suggests facilities that meet those conditions. This allows the suggestion unit to suggest the optimal nursing facility for the user with high accuracy. The suggestion unit also has an interface for presenting the proposal content to the user in an easy-to-understand manner. For example, the suggestion unit displays detailed information, photos, user reviews, etc. of the proposed facility, making it easier for the user to compare and consider. This allows the suggestion unit to increase user satisfaction and support the selection of an appropriate facility.

[0068] The confirmation unit checks the availability of the facilities proposed by the proposal unit. For example, it checks the availability of special nursing homes for the elderly, and if there is availability, it proposes the facility. The confirmation unit can access the facility database to check the availability in real time. Specifically, the confirmation unit uses an API to link with the database of each facility and obtain the latest availability. This makes it possible to quickly check whether the proposed facility is actually available. In addition, the confirmation unit can obtain not only the availability but also detailed information such as the facility's terms of use, fees, and service contents, and provide them to the user. For example, if a specific facility is fully booked, it is possible to propose a similar facility in the vicinity as an alternative. The confirmation unit can use the generation AI to automate and streamline the availability confirmation process. For example, the generation AI can be input with a prompt such as "Please check the availability of facilities suitable for users with a care level of 3 in a specific area," and the generation AI can automatically check the availability of multiple facilities and return the results. In this way, the confirmation unit can provide the user with quick and accurate information and support the selection of an appropriate facility.

[0069] The communication unit communicates with the facility confirmed by the confirmation unit. For example, the communication unit contacts the facility's staff to arrange a tour date and proceed with the admission procedure. The communication unit can contact the facility's staff to arrange a tour date. Specifically, the communication unit informs the facility's staff of the user's desired tour date and time, and arranges a date and time that suits both parties. The communication unit can also provide the user with information such as documents and belongings required for the tour, and precautions. Furthermore, the communication unit also provides support for the admission procedure. For example, the communication unit supports the preparation and submission of necessary documents, confirmation of contract contents, and payment procedures for initial fees. The communication unit can use the generation AI to streamline these communication and adjustment processes. For example, the generation AI can be input with a prompt such as "Please arrange a tour date for a specific facility," and the generation AI can automatically contact the facility's staff and arrange the tour date. In this way, the communication unit can provide the user with quick and efficient support and smoothly proceed with a series of processes from facility selection to admission procedures. As a result, the communication unit can reduce the user's burden and provide an environment in which the user can use the nursing care facility with peace of mind.

[0070] The suggestion unit can suggest facilities such as a geriatric health facility, a nursing hospital, and a special nursing home for the elderly based on the user's physical condition. The suggestion unit, for example, analyzes the user's physical condition and suggests an appropriate facility. For example, if the level of care required is 3, it is determined that a special nursing home for the elderly is appropriate. The suggestion unit can also analyze the user's physical condition and suggest an appropriate facility using a generation AI. For example, the generation AI receives a prompt saying "Please suggest a facility suitable for a user with a level of care required of 3" and suggests an appropriate facility. This makes it possible to select an optimal nursing facility by suggesting an appropriate facility according to the user's physical condition. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the suggestion unit can input the user's physical condition to the generation AI and cause the generation AI to execute the suggestion of an appropriate facility.

[0071] The confirmation unit can access the facility database and check the availability in real time. The confirmation unit, for example, accesses the facility database and checks the availability in real time. For example, the confirmation unit checks the availability of a special nursing home, and if there is availability, suggests the facility. The confirmation unit can access the facility database and check the availability in real time. This makes it possible to provide the latest information by checking the availability in real time. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the availability of the facility to the generation AI and cause the generation AI to check the availability.

[0072] The communication unit can contact a person in charge of the facility and adjust the schedule for the tour. The communication unit can, for example, contact a person in charge of the facility and adjust the schedule for the tour. For example, the communication unit can contact a person in charge of a special nursing home and adjust the schedule for the tour. The communication unit can contact a person in charge of the facility and adjust the schedule for the tour. This allows the user to directly check the facility by adjusting the schedule for the tour. Some or all of the above-mentioned processing in the communication unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the communication unit can input interactions with the person in charge of the facility into the generation AI and have the generation AI execute the adjustment of the interactions.

[0073] The liaison unit can contact the person in charge of the facility and proceed with the move-in procedures. The liaison unit can, for example, contact the person in charge of the facility and proceed with the move-in procedures. For example, the liaison unit can contact the person in charge of a special nursing home and proceed with the move-in procedures. The liaison unit can contact the person in charge of the facility and proceed with the move-in procedures. This allows for smooth move-in by proceeding with the move-in procedures. Some or all of the above-mentioned processing in the liaison unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the liaison unit can input interactions with the person in charge of the facility into the generation AI and have the generation AI coordinate the interactions.

[0074] The proposal unit can propose systems and subsidies available in each local government when it is difficult to enter a facility. The proposal unit, for example, proposes systems and subsidies available in each local government when it is difficult to enter a facility. For example, it proposes methods of using home nursing care services and nursing care insurance. The proposal unit can propose systems and subsidies available in each local government when it is difficult to enter a facility. This makes it possible to support the user's life by proposing other support measures even when it is difficult to enter a facility. Some or all of the above-mentioned processing in the proposal unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the proposal unit can input system and subsidy information of each local government into the generation AI and cause the generation AI to execute appropriate proposals.

[0075] In the case of an elderly person, the suggestion unit can use a voice system to provide an explanation. For example, in the case of an elderly person, the suggestion unit uses a voice system to provide an explanation. For example, the suggestion unit explains by voice, "By using home care services, you can receive support for your daily life." In the case of an elderly person, the suggestion unit can use a voice system to provide an explanation. This helps the elderly person understand by providing an explanation by voice. A part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the suggestion unit can input the voice system into the generation AI and cause the generation AI to execute the voice explanation.

[0076] The reception unit can estimate the user's emotion and adjust the timing of information input based on the estimated user's emotion. For example, when the user is stressed, the reception unit delays the timing of prompting input to provide an environment in which the user can relax. For example, when the user is relaxed, the reception unit adjusts the timing so that the user can input information smoothly. Also, when the user is in a hurry, the reception unit adjusts the timing so that the user can input information quickly. In this way, by adjusting the timing of information input according to the user's emotion, it is possible to reduce stress and promote smooth input. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the reception unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the reception unit can input the user's emotion data to the generation AI and cause the generation AI to execute emotion estimation.

[0077] The reception unit can analyze the user's past input history and select the optimal input method. For example, the reception unit preferentially suggests an input method (such as voice or text) that the user has frequently used in the past. For example, the reception unit predicts and suggests an input method to be used in a specific time period from the user's past input history. In addition, the reception unit can automatically complete input items based on information previously input by the user. This allows the optimal input method to be selected based on the past input history, thereby improving user convenience. A part or all of the above-mentioned processing in the reception unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the reception unit can input the user's past input history to the generation AI and cause the generation AI to select the optimal input method.

[0078] The reception unit can customize the input items based on the user's current living situation and field of interest when inputting information. The reception unit customizes the input items so that the user inputs only necessary information based on the user's current living situation. For example, based on the user's field of interest, related input items are preferentially displayed. The input items can also be automatically adjusted based on the user's living situation and field of interest. This can improve the efficiency of input by providing input items according to the user's living situation and field of interest. A part or all of the above-mentioned processing in the reception unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the reception unit can input the user's living situation and field of interest into the generation AI and cause the generation AI to customize the input items.

[0079] The reception unit can estimate the user's emotion and determine the priority of information to be input based on the estimated user's emotion. For example, when the user is feeling stressed, the reception unit adjusts the input so that important information is input preferentially. For example, when the user is relaxed, the reception unit adjusts the input so that detailed information is input. Also, when the user is in a hurry, the reception unit adjusts the input so that the minimum amount of information is input preferentially. In this way, by determining the priority of information to be input according to the user's emotion, important information can be input preferentially. The estimation of emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the reception unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the reception unit can input the user's emotion data to the generation AI and cause the generation AI to execute emotion estimation.

[0080] The reception unit can preferentially input highly relevant information in consideration of the user's geographical location information when inputting information. For example, the reception unit preferentially inputs information on nearby nursing care facilities based on the user's current location. For example, based on the user's geographical location information, related local government systems and subsidy information are preferentially input. In addition, optimal input items can be automatically displayed in consideration of the user's geographical location information. This allows highly relevant information to be preferentially input by considering the user's geographical location information. Part or all of the above-mentioned processing in the reception unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the reception unit can input the user's geographical location information to the generation AI and cause the generation AI to execute the input of highly relevant information.

[0081] The reception unit can analyze the user's social media activity and input related information when inputting information. For example, the reception unit automatically inputs information on nursing facilities of interest from the user's social media activity. For example, based on the user's social media activity, related local government systems and subsidy information can be input. In addition, the reception unit can analyze the user's social media activity and suggest optimal input items. In this way, by analyzing social media activity, information related to the user can be efficiently input. Some or all of the above-mentioned processing in the reception unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the reception unit can input the user's social media activity to the generation AI and cause the generation AI to input related information.

[0082] The suggestion unit can estimate the user's emotion and adjust the way of expressing the proposal based on the estimated user's emotion. For example, when the user is stressed, the suggestion unit makes a simple and easy-to-understand proposal. For example, when the user is relaxed, the suggestion unit makes a proposal including detailed information. Also, when the user is in a hurry, the suggestion unit makes a quick proposal that covers the main points. This allows the suggestion to be easily understood by the user by adjusting the way of expressing the proposal according to the user's emotion. The estimation of the emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the suggestion unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the suggestion unit can input the user's emotion data to the generation AI and cause the generation AI to adjust the way of expressing the proposal.

[0083] The suggestion unit can adjust the level of detail of the proposal based on the user's physical condition at the time of proposal. For example, when the user's physical condition is poor, the suggestion unit makes a proposal including detailed information. For example, when the user's physical condition is good, the suggestion unit makes a concise proposal. In addition, the suggestion unit can adjust the optimal level of detail of the proposal based on the user's physical condition. This allows appropriate information to be provided by adjusting the level of detail of the proposal according to the user's physical condition. A part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the suggestion unit can input the user's physical condition to the generation AI and cause the generation AI to adjust the level of detail of the proposal.

[0084] At the time of proposal, the suggestion unit can suggest the optimal facility by referring to the user's past nursing facility use history. The suggestion unit, for example, suggests the optimal facility based on information on nursing facilities used by the user in the past. For example, it suggests related facilities from the user's past nursing facility use history. It is also possible to analyze the user's past nursing facility use history and suggest the most appropriate facility. As a result, it is possible to provide the user with the optimal option by suggesting the optimal facility based on the past use history. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the suggestion unit can input the user's past nursing facility use history into the generation AI and cause the generation AI to execute the proposal of the optimal facility.

[0085] The suggestion unit can estimate the user's emotion and determine the priority of suggestions based on the estimated user's emotion. For example, when the user is stressed, the suggestion unit prioritizes important suggestions. For example, when the user is relaxed, the suggestion unit prioritizes detailed suggestions. Also, when the user is in a hurry, the suggestion unit prioritizes quick suggestions. In this way, important suggestions can be prioritized by determining the priority of suggestions according to the user's emotion. The estimation of emotions is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the suggestion unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the suggestion unit can input the user's emotion data to the generation AI and cause the generation AI to execute the determination of the priority of suggestions.

[0086] The suggestion unit can suggest the most suitable facility by considering the geographical location information of the user at the time of suggestion. The suggestion unit, for example, suggests a nearby nursing care facility based on the user's current location. For example, based on the user's geographical location information, related local government systems and subsidy information are suggested. In addition, the most suitable facility can be automatically suggested by considering the user's geographical location information. In this way, by considering the user's geographical location information, an appropriate nearby facility can be suggested. A part or all of the above-mentioned processing in the suggestion unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the suggestion unit can input the user's geographical location information to the generation AI and cause the generation AI to suggest the most suitable facility.

[0087] At the time of proposal, the suggestion unit can analyze the user's social media activity and propose related facilities. The suggestion unit, for example, proposes nursing care facilities of interest from the user's social media activity. For example, based on the user's social media activity, the suggestion unit proposes related local government systems and support information. The suggestion unit can also analyze the user's social media activity and propose optimal facilities. In this way, by analyzing social media activity, it is possible to efficiently propose facilities related to the user. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the suggestion unit can input the user's social media activity into the generation AI and cause the generation AI to execute the proposal of related facilities.

[0088] The confirmation unit can estimate the user's emotion and adjust the confirmation method of availability based on the estimated user's emotion. For example, when the user is stressed, the confirmation unit provides a simple and easy-to-understand confirmation method. For example, when the user is relaxed, the confirmation unit provides a confirmation method including detailed information. Also, when the user is in a hurry, the confirmation unit provides a method for quickly confirming availability. This provides a confirmation method according to the user's emotion, thereby reducing stress and enabling smooth confirmation. The estimation of emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the confirmation unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the user's emotion data to the generation AI and cause the generation AI to execute the adjustment of the confirmation method.

[0089] The confirmation unit can make a prediction by referring to the facility's past availability data when checking availability. The confirmation unit, for example, predicts the current availability based on the facility's past availability data. For example, the confirmation unit analyzes the facility's past availability data and predicts future availability. In addition, the confirmation unit can provide an optimal confirmation method by referring to the facility's past availability data. This makes it possible to provide a more accurate availability by making a prediction based on the past availability data. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the facility's past availability data into the generation AI and cause the generation AI to execute an availability prediction.

[0090] The confirmation unit can adjust the level of detail of the confirmation based on the service content provided by the facility when confirming availability. For example, when the service content provided by the facility is large, the confirmation unit provides a detailed confirmation method. For example, when the service content provided by the facility is small, the confirmation unit provides a simple confirmation method. The confirmation unit can also adjust the optimal confirmation method based on the service content provided by the facility. This makes it possible to provide appropriate information by adjusting the level of detail of the confirmation according to the service content provided by the facility. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the service content provided by the facility to the generation AI and cause the generation AI to adjust the level of detail of the confirmation.

[0091] The confirmation unit can estimate the user's emotion and adjust the display method of the availability status based on the estimated user's emotion. For example, when the user is stressed, the confirmation unit provides a simple and highly visible display method. For example, when the user is relaxed, the confirmation unit provides a display method including detailed information. Also, when the user is in a hurry, the confirmation unit provides a display method that focuses on the main points. This can improve visibility by providing a display method according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the confirmation unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the user's emotion data to the generation AI and cause the generation AI to adjust the display method.

[0092] The confirmation unit can check availability while taking into consideration the geographical distribution of facilities. For example, the confirmation unit preferentially checks availability of nearby facilities based on the geographical distribution of the facilities. For example, an optimal checking method is provided while taking into consideration the geographical distribution of the facilities. Also, availability can be checked by referring to the geographical distribution of the facilities. As a result, availability of nearby facilities can be checked preferentially by taking into consideration the geographical distribution of the facilities. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the geographical distribution of the facilities to the generation AI and cause the generation AI to check availability.

[0093] The confirmation unit can improve the accuracy of confirmation by referring to literature related to the facility when checking availability. The confirmation unit improves the accuracy of confirmation of availability, for example, based on literature related to the facility. For example, the confirmation unit provides an optimal confirmation method by referring to literature related to the facility. The confirmation unit can also analyze literature related to the facility and improve the accuracy of confirmation of availability. As a result, the accuracy of confirmation of availability can be improved by referring to the related literature. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input literature related to the facility into the generation AI and cause the generation AI to improve the confirmation accuracy.

[0094] The contact unit can estimate the user's emotions and adjust the contact method based on the estimated user's emotions. For example, when the user is stressed, the contact unit provides a simple and easy-to-understand contact method. For example, when the user is relaxed, the contact unit provides a contact method including detailed information. Also, when the user is in a hurry, the contact unit provides a method that allows quick contact. In this way, by providing a contact method according to the user's emotions, stress can be reduced and smooth contact can be made. The estimation of emotions is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the contact unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the contact unit can input the user's emotion data into the generation AI and cause the generation AI to execute the adjustment of the contact method.

[0095] The communication unit can select the optimal contact method by referring to the past response history of the facility person in charge at the time of contact. For example, the communication unit preferentially selects a contact method that the facility person in charge has responded to quickly in the past. For example, the communication unit proposes the optimal contact method based on the past response history of the facility person in charge. In addition, the communication unit can analyze the past response history of the facility person in charge and select the most effective contact method. As a result, effective communication is possible by selecting the optimal contact method based on the past response history. Part or all of the above-mentioned processing in the communication unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the communication unit can input the past response history of the facility person in charge into the generation AI and cause the generation AI to select the optimal contact method.

[0096] The contact unit can adjust the level of detail of the contact by referring to the user's past contact history at the time of contact. For example, if the user has requested detailed contact in the past, the contact unit contacts the user including detailed information. For example, if the user has requested brief contact in the past, the contact unit contacts the user including brief information. The contact unit can also adjust the optimal level of detail of the contact based on the user's past contact history. This allows optimal contact for the user by adjusting the level of detail of the contact based on the past contact history. A part or all of the above-mentioned processing in the contact unit may be performed using, for example, a generation AI, or may be performed without using the generation AI. For example, the contact unit can input the user's past contact history into the generation AI and cause the generation AI to adjust the level of detail of the contact.

[0097] The communication unit can estimate the user's emotion and determine the priority of the communication based on the estimated user's emotion. For example, when the user is feeling stressed, the communication unit prioritizes important communication. For example, when the user is relaxed, the communication unit prioritizes detailed communication. Also, when the user is in a hurry, the communication unit prioritizes quick communication. In this way, important communication can be prioritized by determining the priority of communication according to the user's emotion. The emotion estimation is realized by using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the communication unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the communication unit can input the user's emotion data to the generation AI and cause the generation AI to execute the determination of the priority of the communication.

[0098] The contact unit can select the optimal contact method in consideration of the geographical location information of the facility at the time of contact. The contact unit selects a quick contact method for nearby facilities based on, for example, the geographical location information of the facility. For example, the contact unit proposes an optimal contact method in consideration of the geographical location information of the facility. The optimal contact method can also be selected by referring to the geographical location information of the facility. This makes it possible to quickly contact nearby facilities by considering the geographical location information of the facility. Some or all of the above-mentioned processing in the contact unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the contact unit can input the geographical location information of the facility to the generation AI and cause the generation AI to select the optimal contact method.

[0099] At the time of contact, the contact unit can analyze the facility's social media activity and suggest a means of contact. The contact unit, for example, suggests the optimal means of contact from the facility's social media activity. For example, the contact unit selects an effective means of contact based on the facility's social media activity. The contact unit can also analyze the facility's social media activity and suggest the optimal means of contact. In this way, the optimal means of contact can be suggested by analyzing social media activity. Some or all of the above-mentioned processing in the contact unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the contact unit can input the facility's social media activity into the generation AI and have the generation AI execute the suggestion of a means of contact.

[0100] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0101] The suggestion unit can suggest facilities such as a geriatric health facility, a nursing hospital, and a special nursing home for the elderly based on the user's physical condition. The suggestion unit, for example, analyzes the user's physical condition and suggests an appropriate facility. For example, if the level of care required is 3, it is determined that a special nursing home for the elderly is appropriate. The suggestion unit can also analyze the user's physical condition and suggest an appropriate facility using a generation AI. For example, the generation AI receives a prompt saying "Please suggest a facility suitable for a user with a level of care required of 3" and suggests an appropriate facility. This makes it possible to select an optimal nursing facility by suggesting an appropriate facility according to the user's physical condition. Some or all of the above-mentioned processing in the suggestion unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the suggestion unit can input the user's physical condition to the generation AI and cause the generation AI to execute the suggestion of an appropriate facility.

[0102] The confirmation unit can access the facility database and check the availability in real time. The confirmation unit, for example, accesses the facility database and checks the availability in real time. For example, the confirmation unit checks the availability of a special nursing home, and if there is availability, suggests the facility. The confirmation unit can access the facility database and check the availability in real time. This makes it possible to provide the latest information by checking the availability in real time. Some or all of the above-mentioned processing in the confirmation unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the availability of the facility to the generation AI and cause the generation AI to check the availability.

[0103] The communication unit can contact a person in charge of the facility and adjust the schedule for the tour. The communication unit can, for example, contact a person in charge of the facility and adjust the schedule for the tour. For example, the communication unit can contact a person in charge of a special nursing home and adjust the schedule for the tour. The communication unit can contact a person in charge of the facility and adjust the schedule for the tour. This allows the user to directly check the facility by adjusting the schedule for the tour. Some or all of the above-mentioned processing in the communication unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the communication unit can input interactions with the person in charge of the facility into the generation AI and have the generation AI execute the adjustment of the interactions.

[0104] The liaison unit can contact the person in charge of the facility and proceed with the move-in procedures. The liaison unit can, for example, contact the person in charge of the facility and proceed with the move-in procedures. For example, the liaison unit can contact the person in charge of a special nursing home and proceed with the move-in procedures. The liaison unit can contact the person in charge of the facility and proceed with the move-in procedures. This allows for smooth move-in by proceeding with the move-in procedures. Some or all of the above-mentioned processing in the liaison unit can be performed, for example, using the generation AI, or can be performed without using the generation AI. For example, the liaison unit can input interactions with the person in charge of the facility into the generation AI and have the generation AI coordinate the interactions.

[0105] The proposal unit can propose systems and subsidies available in each local government when it is difficult to enter a facility. The proposal unit, for example, proposes systems and subsidies available in each local government when it is difficult to enter a facility. For example, it proposes methods of using home nursing care services and nursing care insurance. The proposal unit can propose systems and subsidies available in each local government when it is difficult to enter a facility. This makes it possible to support the user's life by proposing other support measures even when it is difficult to enter a facility. Some or all of the above-mentioned processing in the proposal unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the proposal unit can input system and subsidy information of each local government into the generation AI and cause the generation AI to execute appropriate proposals.

[0106] The reception unit can estimate the user's emotion and adjust the timing of information input based on the estimated user's emotion. For example, when the user is stressed, the reception unit delays the timing of prompting input to provide an environment in which the user can relax. For example, when the user is relaxed, the reception unit adjusts the timing so that the user can input information smoothly. Also, when the user is in a hurry, the reception unit adjusts the timing so that the user can input information quickly. In this way, by adjusting the timing of information input according to the user's emotion, it is possible to reduce stress and promote smooth input. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the reception unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the reception unit can input the user's emotion data to the generation AI and cause the generation AI to execute emotion estimation.

[0107] The reception unit can estimate the user's emotion and determine the priority of information to be input based on the estimated user's emotion. For example, when the user is feeling stressed, the reception unit adjusts the input so that important information is input preferentially. For example, when the user is relaxed, the reception unit adjusts the input so that detailed information is input. Also, when the user is in a hurry, the reception unit adjusts the input so that the minimum amount of information is input preferentially. In this way, by determining the priority of information to be input according to the user's emotion, important information can be input preferentially. The estimation of emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the reception unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the reception unit can input the user's emotion data to the generation AI and cause the generation AI to execute emotion estimation.

[0108] The suggestion unit can estimate the user's emotion and adjust the way of expressing the proposal based on the estimated user's emotion. For example, when the user is stressed, the suggestion unit makes a simple and easy-to-understand proposal. For example, when the user is relaxed, the suggestion unit makes a proposal including detailed information. Also, when the user is in a hurry, the suggestion unit makes a quick proposal that covers the main points. This allows the proposal to be easily understood by the user by adjusting the way of expressing the proposal according to the user's emotion. The estimation of the emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the suggestion unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the suggestion unit can input the user's emotion data to the generation AI and cause the generation AI to adjust the way of expressing the proposal.

[0109] The suggestion unit can estimate the user's emotion and determine the priority of suggestions based on the estimated user's emotion. For example, when the user is stressed, the suggestion unit prioritizes important suggestions. For example, when the user is relaxed, the suggestion unit prioritizes detailed suggestions. Also, when the user is in a hurry, the suggestion unit prioritizes quick suggestions. In this way, important suggestions can be prioritized by determining the priority of suggestions according to the user's emotion. The estimation of emotions is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the suggestion unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the suggestion unit can input the user's emotion data to the generation AI and cause the generation AI to execute the determination of the priority of suggestions.

[0110] The confirmation unit can estimate the user's emotion and adjust the confirmation method of availability based on the estimated user's emotion. For example, when the user is stressed, the confirmation unit provides a simple and easy-to-understand confirmation method. For example, when the user is relaxed, the confirmation unit provides a confirmation method including detailed information. Also, when the user is in a hurry, the confirmation unit provides a method for quickly confirming availability. This provides a confirmation method according to the user's emotion, thereby reducing stress and enabling smooth confirmation. The estimation of emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the confirmation unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the confirmation unit can input the user's emotion data to the generation AI and cause the generation AI to execute the adjustment of the confirmation method.

[0111] The process flow of the second embodiment will be briefly described below.

[0112] Step 1: The reception unit inputs information such as the area of ​​residence, age, annual income, level of care required, etc. For example, if the user is a 75-year-old man living in Tokyo, with an annual income of 3 million yen and a level of care required of 3, this information can be entered into the system. Step 2: The suggestion unit analyzes the information entered by the reception unit and suggests an appropriate nursing care facility based on the user's physical condition. For example, if the level of care required is 3, it is determined that a special nursing home is appropriate. The suggestion unit uses the generation AI to analyze the user's physical condition and suggests an appropriate facility. For example, the generation AI receives a prompt saying, "Please suggest a facility suitable for a user with a level of care required of 3," and suggests an appropriate facility. Step 3: The confirmation unit checks the availability of the facility proposed by the proposal unit. For example, the confirmation unit checks the availability of a special nursing home for the elderly, and if there is availability, proposes the facility. The confirmation unit can access the database of facilities to check the availability in real time. Step 4: The Liaison Department communicates with the facility confirmed by the Confirmation Department. For example, the Liaison Department may contact the facility's staff to arrange a tour date or to proceed with the move-in procedure. The Liaison Department may contact the facility's staff to arrange a tour date.

[0113] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0114] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by 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 a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) are input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may also be an AI agent. In addition, when the processes of each of the above-mentioned parts are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples.In addition, processing performed by AI including the generation AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI including the generation AI.

[0115] Furthermore, the above-described processing by the data processing system 10 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 required for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information required for processing from the data processing device 12 or an external device.

[0116] Each of the multiple elements including the above-mentioned reception unit, suggestion unit, confirmation unit, communication unit, and emotion estimation function is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart device 14, and inputs information such as the user's residential area, age, annual income, and level of care required. The suggestion unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and suggests an appropriate nursing care facility based on the user's physical condition. The confirmation unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and checks the availability of the proposed facility. The communication unit is realized, for example, by the control unit 46A of the smart device 14, and contacts the person in charge of the facility to arrange a tour schedule. The emotion estimation function is realized, for example, by the specific processing unit 290 of the data processing device 12, and estimates the user's emotion and adjusts the timing of information input. The correspondence between each unit and the device or control unit is not limited to the above-mentioned example, and various changes are possible.

[0117] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0118] 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.

[0119] 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, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0120] 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.

[0121] 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 the voice according to instructions from the processor 46.

[0122] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0123] 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 performed in a secure state.

[0124] Fig. 4 shows an example of main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0125] 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.

[0126] 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 the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0127] In the smart glasses 214, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. 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 glasses 214 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 also perform processing similar to that of the specific processing unit 290 using these models.

[0128] 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 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0129] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0130] 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. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0131] 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 be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, 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, and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device.

[0132] Each of the multiple elements including the above-mentioned reception unit, suggestion unit, confirmation unit, communication unit, and emotion estimation function is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart glasses 214, and inputs information such as the user's residential area, age, annual income, and level of care required. The suggestion unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and suggests an appropriate nursing care facility based on the user's physical condition. The confirmation unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and checks the availability of the proposed facility. The communication unit is realized, for example, by the control unit 46A of the smart glasses 214, and contacts the person in charge of the facility to arrange a tour schedule. The emotion estimation function is realized, for example, by the specific processing unit 290 of the data processing device 12, and estimates the user's emotion and adjusts the timing of information input. The correspondence between each unit and the device or control unit is not limited to the above-mentioned example, and various changes are possible.

[0133] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0134] 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.

[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, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0136] 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.

[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 the voice according to instructions from the processor 46.

[0138] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[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 performed in a secure state.

[0140] 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.

[0141] 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.

[0142] 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 the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0143] In the headset type terminal 314, the specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50, and executes the read specific 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 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 identification processing unit 290 using these models.

[0144] 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 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0145] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input for the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0146] 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. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0147] 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 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. In addition, 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, and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device.

[0148] Each of the plurality of elements including the above-mentioned reception unit, suggestion unit, confirmation unit, communication unit, and emotion estimation function is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the headset type terminal 314, and inputs information such as the user's residential area, age, annual income, and level of care required. The suggestion unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and suggests an appropriate nursing care facility based on the user's physical condition. The confirmation unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and checks the availability of the proposed facility. The communication unit is realized, for example, by the control unit 46A of the headset type terminal 314, and contacts the person in charge of the facility to arrange a tour schedule. The emotion estimation function is realized, for example, by the specific processing unit 290 of the data processing device 12, and estimates the user's emotion and adjusts the timing of information input. The correspondence between each unit and the device or control unit is not limited to the above-mentioned example, and various changes are possible.

[0149] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0150] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0151] 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, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0152] 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.

[0153] 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 the voice according to instructions from the processor 46.

[0154] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of a typical healthy person).

[0155] 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 performed in a secure state.

[0156] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and legs. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, and legs. 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.

[0157] 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.

[0158] 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.

[0159] 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 the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0160] In the robot 414, the specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads out the specific program 60 from the storage 50, and executes the specific 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 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.

[0161] 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 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0162] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0163] 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. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0164] 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 be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, 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.

[0165] Each of the plurality of elements including the reception unit, the proposal unit, the confirmation unit, the communication unit, and the emotion estimation function described above is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the robot 414, and inputs information such as the user's residential area, age, annual income, and level of care required. The proposal unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and proposes an appropriate nursing care facility based on the user's physical condition. The confirmation unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and confirms the availability of the proposed facility. The communication unit is realized, for example, by the control unit 46A of the robot 414, and contacts the person in charge of the facility to arrange a tour schedule. The emotion estimation function is realized, for example, by the specific processing unit 290 of the data processing device 12, and estimates the user's emotion and adjusts the timing of information input. The correspondence between each unit and the device or control unit is not limited to the above example, and various changes are possible.

[0166] The emotion identification model 59 as an emotion engine may determine the emotion of the user according to a specific mapping. Specifically, the emotion identification model 59 may determine the emotion of the user according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the emotion of the robot, and the identification processing unit 290 may perform identification processing using the emotion of the robot.

[0167] FIG. 9 is a diagram showing 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. The closer to the center of the concentric circles, the more primitive emotions are arranged. The more outside the concentric circles, the more emotions that represent states and actions that arise from a state of mind are arranged. Emotions are a concept that includes emotions and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions that occur in the brain are arranged. On the right side of the concentric circles, emotions that are generally induced by situational judgment are arranged. On the upper and lower sides of the concentric circles, emotions that are generally generated from reactions that occur in the brain and are induced by situational judgment are arranged. In addition, on the upper side of the concentric circles, emotions of "pleasure" are arranged, and on the lower side, emotions of "discomfort" are arranged. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0168] These emotions are distributed in the 3 o'clock direction of emotion map 400 and usually 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.

[0169] The inside of emotion map 400 represents what is going on inside one's mind, and the outside of emotion map 400 represents behavior, so the further out you go on emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0170] Here, human emotions are based on various balances such as posture and blood sugar level, and when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. Emotions can also be created for robots, cars, motorcycles, etc., based on various balances such as posture and battery level, so that when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. The emotion map may be generated, for example, based on the emotion map of Dr. Mitsuyoshi (Research on speech emotion recognition and emotion brain physiological signal analysis system, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). On the left half of the emotion map, emotions belonging to an area called "reaction" where sensation is dominant are lined up. On the right half of the emotion map, emotions belonging to an area called "situation" where situation recognition is dominant are lined up.

[0171] The emotion map defines two emotions that promote learning. The first is the negative emotion around the middle of "repentance" or "remorse" on the situation side. In other words, this is 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 the positive emotion around "desire" on the response side. In other words, this is when the robot has positive feelings such as "I want more" or "I want to know more."

[0172] The emotion identification model 59 inputs the user input to a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the emotion of the user. This neural network is pre-trained based on multiple learning data that are combinations of the 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, "relief," "calm," and "encouraging," have similar emotion values.

[0173] 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.

[0174] 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 Universal Serial Bus (USB) 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.

[0175] In addition, 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 upon request from the data processing device 12.

[0176] 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.

[0177] As the hardware resource for executing the specific process, various processors as shown below can be used. An example of the processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing the specific process by executing software, i.e., a program. Another example of the processor is a dedicated electric circuit, which is a processor having a circuit configuration designed exclusively for executing a specific process, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), or an Application Specific Integrated Circuit (ASIC). Each processor has a built-in or connected memory, and each processor executes the specific process by using the memory.

[0178] The hardware resource that executes the specific process may be one of these various processors, or may be 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.

[0179] As an example of a configuration using one 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 configuration using a processor that realizes the functions of the 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.

[0180] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements. The above specific processes are merely examples. It goes without saying that unnecessary steps may be deleted, new steps may be added, or the order of processes may be changed without departing from the spirit of the invention.

[0181] In the above example, the first to fourth embodiments are described separately, but some or all of these embodiments may be combined. The smart device 14, the smart glasses 214, the headset terminal 314, and the robot 414 are only examples, and they may be combined with each other, or may be other devices. In the above example, the first and second embodiments are described separately, but they may be combined.

[0182] The above description and illustrations are detailed descriptions 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, function, action, and effect is an example of the configuration, function, action, and effect 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 replaced with respect to the description and illustrations shown above, within the scope of the gist of the technology of the present disclosure. In addition, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the description and illustrations shown above omit explanations of technical common sense that do not require particular explanation in enabling the implementation of the technology of the present disclosure.

[0183] All publications, patent applications, and standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, and standard was specifically and individually indicated to be incorporated by reference.

[0184] (Appendix 1) A reception desk where users can input information such as their residential area, age, annual income, and level of care required; A suggestion unit that analyzes the information input by the reception unit and suggests nursing care facilities based on the user's physical condition; A confirmation unit that confirms availability of the facility proposed by the proposal unit; a communication unit for communicating with the facility confirmed by the confirmation unit; A system characterized by: (Appendix 2) The suggestion unit, Suggesting elderly care facilities, nursing hospitals, and special nursing homes based on the user's physical condition 2. The system of claim 1, (Appendix 3) The confirmation unit is Access a property database to check availability in real time 2. The system of claim 1, (Appendix 4) The communication unit includes: Contact the facility manager and schedule a tour. 2. The system of claim 1, (Appendix 5) The communication unit includes: Contact the facility staff and complete the move-in procedure. 2. The system of claim 1, (Appendix 6) The suggestion unit, If moving into a facility is difficult, we will suggest systems and subsidies available from each local government. 2. The system of claim 1, (Appendix 7) The suggestion unit, For elderly people, explanations are given using a voice system. 2. The system of claim 1, (Appendix 8) The reception unit is To estimate a user's emotion and adjust the timing of information input based on the estimated user's emotion. 2. The system of claim 1, (Appendix 9) The reception unit is Analyze the user's past input history and select the optimal input method 2. The system of claim 1, (Appendix 10) The reception unit is As you enter information, customize the input based on your current life situation and interests 2. The system of claim 1, (Appendix 11) The reception unit is Estimate the user's emotions and prioritize the information to be input based on the estimated user's emotions. 2. The system of claim 1, (Appendix 12) The reception unit is When entering information, the system takes into account the user's geographic location information and prioritizes entering information that is more relevant 2. The system of claim 1, (Appendix 13) The reception unit is When you enter information, analyze your social media activity and enter relevant information 2. The system of claim 1, (Appendix 14) The suggestion unit, Infer user emotions and adjust the presentation of suggestions based on the inferred user emotions 2. The system of claim 1, (Appendix 15) The suggestion unit, When making suggestions, the level of detail of the suggestions is adjusted based on the user's physical state. 2. The system of claim 1, (Appendix 16) The suggestion unit, When making a proposal, the system refers to the user's past history of using nursing care facilities to suggest the most suitable facility. 2. The system of claim 1, (Appendix 17) The suggestion unit, Estimate user sentiment and prioritize suggestions based on the estimated user sentiment 2. The system of claim 1, (Appendix 18) The suggestion unit, When making suggestions, the system considers the user's geographic location information to suggest the most suitable facilities. 2. The system of claim 1, (Appendix 19) The suggestion unit, When making a recommendation, the system analyzes the user's social media activity and suggests related facilities. 2. The system of claim 1, (Appendix 20) The confirmation unit is Infer user emotions and adjust availability check methods based on the estimated user emotions 2. The system of claim 1, (Appendix 21) The confirmation unit is When checking availability, make predictions by referencing the facility's past availability data 2. The system of claim 1, (Appendix 22) The confirmation unit is When checking availability, adjust the level of detail based on the services the property offers 2. The system of claim 1, (Appendix 23) The confirmation unit is Infer user sentiment and adjust availability display based on the inferred user sentiment 2. The system of claim 1, (Appendix 24) The confirmation unit is When checking availability, take into account the geographical distribution of facilities. 2. The system of claim 1, (Appendix 25) The confirmation unit is When checking availability, improve the accuracy of the check by referring to related documents of the facility. 2. The system of claim 1, (Appendix 26) The communication unit includes: Inferring user sentiment and adjusting contact methods based on the inferred user sentiment 2. The system of claim 1, (Appendix 27) The communication unit includes: When contacting a facility, the system will select the most appropriate contact method by referring to the facility staff's past response history. 2. The system of claim 1, (Appendix 28) The communication unit includes: When contacting someone, refer to their past contact history to adjust the level of detail 2. The system of claim 1, (Appendix 29) The communication unit includes: To estimate a user's emotion and determine a priority of contacts based on the estimated user's emotion. 2. The system of claim 1, (Appendix 30) The communication unit includes: When contacting customers, consider the geographic location of the facility to determine the best method of contact 2. The system of claim 1, (Appendix 31) The communication unit includes: When contacting us, we analyze your facility's social media activity to suggest ways to contact you 2. The system of claim 1, [Explanation of symbols]

[0185] 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. A reception desk where users can input information such as their residential area, age, annual income, and level of care required; A suggestion unit that analyzes the information input by the reception unit and suggests nursing care facilities based on the user's physical condition; A confirmation unit that confirms availability of the facility proposed by the proposal unit; a communication unit for communicating with the facility confirmed by the confirmation unit; A system characterized by:

2. The suggestion unit, Suggesting elderly care facilities, nursing hospitals, and special nursing homes based on the user's physical condition 2. The system of claim 1 .

3. The confirmation unit is Access a property database to check availability in real time 2. The system of claim 1 .

4. The communication unit includes: Contact the facility manager and schedule a tour.

2. The system of claim 1 .

5. The communication unit includes: Contact the facility staff and complete the move-in procedure.

2. The system of claim 1 .

6. The suggestion unit, If moving into a facility is difficult, we will suggest systems and subsidies available from each local government.

2. The system of claim 1 .

7. The suggestion unit, For elderly people, explanations are given using a voice system.

2. The system of claim 1 .

8. The reception unit is To estimate a user's emotion and adjust the timing of information input based on the estimated user's emotion.

2. The system of claim 1 .

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