System

Abstract

An object of a system according to an embodiment is to comprehensively provide life support and communication for elderly people.SOLUTION: A system according to an embodiment includes a vacant facility modification unit, a communication support unit, a day service providing unit, a housing facility providing unit, a transportation service providing unit, and a shopping support providing unit. The vacant facility modification unit modifies the vacant facility. The communication support unit supports communication of the elderly person. The day service providing unit provides an day service. The housing facility providing unit provides a housing facility. The traffic service providing unit provides a traffic service. The shopping support providing unit provides shopping support.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional technology, there is room for improvement in the issues of loneliness and lack of support for the elderly due to the declining birthrate and aging population.

[0005] The system according to the embodiment aims to comprehensively provide life support and communication for the elderly. [Means for solving the problem]

[0006] The system according to the embodiment includes a vacant facility renovation unit, a communication support unit, a day service provision unit, a housing facility provision unit, a transportation service provision unit, and a shopping support provision unit. The vacant facility renovation unit renovates vacant facilities. The communication support unit supports communication for elderly people. The day service provision unit provides day services. The housing facility provision unit provides housing facilities. The transportation service provision unit provides transportation services. The shopping support provision unit provides shopping support. [Effects of the Invention]

[0007] The system according to the embodiment can comprehensively provide life support and communication for the elderly. [Brief explanation of the drawings]

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

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

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

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

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

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

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

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

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

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

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

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

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

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

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

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

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

[0028] (Example 1) The care support system according to an embodiment of the present invention uses an AI network to provide care support for the challenges facing regions experiencing declining birthrates and aging populations. This care support system uses AI technology to smartly renovate vacant facilities such as closed schools and elementary schools, and utilize them as comprehensive support centers for the elderly. This enables the care support system to support communication among the elderly and reduce feelings of loneliness. It can also help prevent crime against the elderly and create jobs for young people.

[0029] A care support system according to an embodiment includes a vacant facility renovation unit, a communication support unit, a day service provision unit, a housing facility provision unit, a transportation service provision unit, and a shopping support provision unit. The vacant facility renovation unit renovates vacant facilities. For example, the vacant facility renovation unit smartly renovates vacant facilities such as abandoned schools and elementary schools using AI technology. The vacant facility renovation unit also optimizes the layout and equipment within the facility to create a comfortable environment for elderly people. For example, the vacant facility renovation unit uses AI to analyze facility design data and propose barrier-free designs and energy-efficient equipment layouts. The communication support unit supports communication between elderly people. For example, the communication support unit uses AI to act as a conversation partner for elderly people, engaging in everyday conversations and answering questions. The communication support unit also uses AI to analyze elderly people's emotions and take appropriate measures to reduce feelings of loneliness. The day service provision unit provides day services. For example, the day service provision unit uses AI to monitor the health status of elderly people and propose appropriate exercise programs and rehabilitation programs. In addition, the day service provision unit uses AI to manage the elderly's dietary content and provide nutritionally balanced meals. The housing facility provision unit provides housing facilities. For example, the housing facility provision unit uses AI to manage housing facilities and provide an environment where the elderly can live comfortably. In addition, the housing facility provision unit uses AI to automatically adjust room temperature and lighting, creating an environment that suits the elderly's lifestyle. The transportation service provision unit provides transportation services. For example, the transportation service provision unit uses AI to analyze the elderly's transportation needs and suggest the optimal means of transportation. In addition, the transportation service provision unit uses AI to manage the elderly's schedule and arrange for an autonomous vehicle when needed. The shopping support provision unit provides shopping support. For example, the shopping support provision unit uses AI to manage the elderly's shopping list and automatically order the necessary items. In addition, the shopping support provision unit uses AI to suggest products that suit the elderly's preferences and health condition. As a result, the care support system according to the embodiment can improve the quality of life of the elderly and revitalize the entire region. For example, by creating an environment where the elderly can live safely and creating jobs for young people, it is expected that the entire region will achieve sustainable development.

[0030] The Vacant Facility Renovation Department can analyze design data and propose barrier-free designs or energy-efficient equipment layouts. For example, AI can analyze a facility's design data and propose barrier-free designs. For example, it can propose eliminating steps or installing handrails. The Vacant Facility Renovation Department can also propose energy-efficient equipment layouts. For example, it can propose introducing solar power generation or using insulation materials. The Vacant Facility Renovation Department can also propose installing energy-efficient lighting. This can provide an environment where elderly people can live comfortably.

[0031] The communication support unit can act as a conversation partner for the elderly and respond to everyday conversations or consultations. For example, the communication support unit uses AI to act as a conversation partner for the elderly and respond to everyday conversations. For example, the AI ​​will ask questions such as "What did you do today?" and listen to what the elderly has to say. The communication support unit also uses AI to respond to consultations from the elderly. For example, it can provide health and lifestyle consultations. This can help reduce the sense of loneliness felt by the elderly.

[0032] The day service provision unit can monitor the health condition of the elderly and suggest an exercise program or rehabilitation. For example, AI can monitor the health condition of the elderly and suggest an exercise program. For example, AI can analyze the walking data of the elderly and suggest balance training. The day service provision unit can also suggest rehabilitation. For example, AI can suggest strength training for the elderly. The day service provision unit can also use AI to manage the dietary content of the elderly and provide nutritionally balanced meals. This can help maintain and improve the health of the elderly.

[0033] The housing facility providing unit can automatically adjust the room temperature or lighting to create an environment that suits the elderly person's lifestyle rhythm. In the housing facility providing unit, for example, AI automatically adjusts the room temperature. For example, AI adjusts the room temperature to suit the elderly person's lifestyle rhythm. In addition, the housing facility providing unit automatically adjusts the lighting. For example, AI adjusts the lighting to suit the elderly person's lifestyle rhythm. This makes it possible to provide an environment where the elderly can live comfortably.

[0034] The transportation service provider can analyze the transportation needs of the elderly and suggest the optimal means of transportation. For example, AI can manage the schedules of the elderly and arrange for self-driving cars when necessary. The transportation service provider can also use AI to analyze traffic conditions in real time and suggest the optimal route. This can efficiently support the transportation of the elderly.

[0035] The shopping support unit can analyze the consumption patterns of the elderly and automatically order the necessary items. For example, AI can analyze the consumption patterns of the elderly and automatically order the necessary items. For example, AI can analyze the consumption patterns of the elderly and periodically order the necessary items. The shopping support unit can also use AI to suggest products that suit the preferences and health condition of the elderly. For example, AI can suggest health foods that suit the health condition of the elderly. This can efficiently support shopping for the elderly.

[0036] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0037] The care support system can further include a hobby activity support unit that supports elderly people in their hobby activities. The hobby activity support unit analyzes the elderly's hobbies and interests and suggests appropriate hobby activities. For example, the hobby activity support unit uses AI to analyze the elderly's past hobby activity data and suggest hobby activities such as painting classes or music classes. The hobby activity support unit also uses AI to consider the elderly's physical strength and health condition and suggest hobby activities that are within their reasonable range. Furthermore, the hobby activity support unit can also use AI to find common hobbies between elderly people and suggest group activities. This can improve the quality of life of elderly people and reduce their sense of loneliness.

[0038] The care support system can also be equipped with a health monitoring unit that monitors the health status of elderly people in real time. The health monitoring unit constantly monitors the elderly's vital signs, such as heart rate, blood pressure, and body temperature, and responds promptly if an abnormality is detected. For example, the health monitoring unit uses AI to analyze the elderly's vital signs and notify a medical institution if an abnormality is detected. The health monitoring unit can also use AI to analyze the elderly's health status and provide advice on daily life and health management. Furthermore, the health monitoring unit can use AI to accumulate the elderly's health data and propose long-term health management plans. This can help maintain and improve the health of the elderly.

[0039] The care support system can further include a meal support unit that supports the elderly with their meals. The meal support unit analyzes the elderly's nutritional status and preferences and proposes an appropriate meal plan. For example, the meal support unit uses AI to analyze the elderly's nutritional status and propose a nutritionally balanced meal menu. The meal support unit can also use AI to analyze the elderly's preferences and provide meals tailored to their tastes. Furthermore, the meal support unit can use AI to take the elderly's health status into consideration and propose a meal plan that addresses specific health issues. This helps maintain the health of the elderly and provide them with the enjoyment of eating.

[0040] The care support system can also be equipped with a safety monitoring unit to ensure the safety of the elderly. The safety monitoring unit constantly monitors the elderly's living environment and responds quickly if an abnormality occurs. For example, the safety monitoring unit uses AI to analyze the elderly's movements and notify emergency contacts if an accident such as a fall occurs. The safety monitoring unit can also use AI to analyze the elderly's living environment and issue an alarm if it detects a risk such as a fire or gas leak. Furthermore, the safety monitoring unit can also use AI to analyze the elderly's living patterns and issue a warning if abnormal behavior is detected. This ensures the safety of the elderly and provides an environment where they can live with peace of mind.

[0041] The care support system can further include a learning support unit that supports the elderly's learning. The learning support unit analyzes the elderly's interests and learning needs and suggests appropriate learning programs. For example, the learning support unit uses AI to analyze the elderly's interests and suggest online courses or workshops. The learning support unit can also use AI to analyze the elderly's learning pace and suggest learning programs that are within their reasonable range. Furthermore, the learning support unit can use AI to analyze the elderly's past learning history and suggest continuous learning plans. This can improve the elderly's knowledge and skills and support lifelong learning.

[0042] The care support system can further include a pet care support unit that supports elderly people in caring for their pets. The pet care support unit analyzes the health status and needs of elderly people's pets and proposes appropriate care methods. For example, the pet care support unit uses AI to analyze the pet's health status and propose appropriate diet and exercise plans. The pet care support unit can also use AI to analyze the pet's behavior and propose ways to reduce stress. Furthermore, the pet care support unit can use AI to accumulate pet health data and propose long-term health management plans. This can provide an environment where elderly people can live with their pets with peace of mind.

[0043] The processing flow of the first embodiment will be briefly explained below.

[0044] Step 1: The Vacant Facility Renovation Department renovates vacant facilities. For example, it uses AI technology to smartly renovate vacant facilities such as abandoned schools and elementary schools, optimizing the layout and equipment within the facility. This creates an environment where elderly people can live comfortably. Specifically, the AI ​​analyzes the facility's design data and proposes barrier-free designs and energy-efficient equipment layouts. Step 2: The communication support unit supports communication between elderly people. For example, the AI ​​can act as a conversation partner for elderly people, providing everyday conversation and answering questions. The AI ​​can also analyze the emotions of elderly people and take appropriate measures to reduce feelings of loneliness. Step 3: The day care service provider provides day care services. For example, AI monitors the health of the elderly and suggests appropriate exercise programs and rehabilitation. AI also manages the elderly's diet and provides nutritionally balanced meals. Step 4: The Housing Facility Provision Department provides housing facilities. For example, AI manages the housing facilities and provides an environment where the elderly can live comfortably. AI also automatically adjusts the room temperature and lighting, creating an environment that suits the elderly's lifestyle. Step 5: The transportation service provider provides transportation services. For example, AI analyzes the mobility needs of elderly people and suggests the most suitable means of transportation. AI also manages the elderly people's schedules and arranges for self-driving cars when needed. Step 6: The shopping assistance provider provides shopping assistance. For example, AI manages the elderly person's shopping list and automatically orders the necessary items. AI also suggests products tailored to the elderly person's preferences and health condition.

[0045] (Example 2) The care support system according to an embodiment of the present invention uses an AI network to provide care support for the challenges facing regions experiencing declining birthrates and aging populations. This care support system uses AI technology to smartly renovate vacant facilities such as closed schools and elementary schools, and utilize them as comprehensive support centers for the elderly. This enables the care support system to support communication among the elderly and reduce feelings of loneliness. It can also help prevent crime against the elderly and create jobs for young people.

[0046] A care support system according to an embodiment includes a vacant facility renovation unit, a communication support unit, a day service provision unit, a housing facility provision unit, a transportation service provision unit, and a shopping support provision unit. The vacant facility renovation unit renovates vacant facilities. For example, the vacant facility renovation unit smartly renovates vacant facilities such as abandoned schools and elementary schools using AI technology. The vacant facility renovation unit also optimizes the layout and equipment within the facility to create a comfortable environment for elderly people. For example, the vacant facility renovation unit uses AI to analyze facility design data and propose barrier-free designs and energy-efficient equipment layouts. The communication support unit supports communication between elderly people. For example, the communication support unit uses AI to act as a conversation partner for elderly people, engaging in everyday conversations and answering questions. The communication support unit also uses AI to analyze elderly people's emotions and take appropriate measures to reduce feelings of loneliness. The day service provision unit provides day services. For example, the day service provision unit uses AI to monitor the health status of elderly people and propose appropriate exercise programs and rehabilitation programs. In addition, the day service provision unit uses AI to manage the elderly's dietary content and provide nutritionally balanced meals. The housing facility provision unit provides housing facilities. For example, the housing facility provision unit uses AI to manage housing facilities and provide an environment where the elderly can live comfortably. In addition, the housing facility provision unit uses AI to automatically adjust room temperature and lighting, creating an environment that suits the elderly's lifestyle. The transportation service provision unit provides transportation services. For example, the transportation service provision unit uses AI to analyze the elderly's transportation needs and suggest the optimal means of transportation. In addition, the transportation service provision unit uses AI to manage the elderly's schedule and arrange for an autonomous vehicle when needed. The shopping support provision unit provides shopping support. For example, the shopping support provision unit uses AI to manage the elderly's shopping list and automatically order the necessary items. In addition, the shopping support provision unit uses AI to suggest products that suit the elderly's preferences and health condition. As a result, the care support system according to the embodiment can improve the quality of life of the elderly and revitalize the entire region. For example, by creating an environment where the elderly can live safely and creating jobs for young people, it is expected that the entire region will achieve sustainable development.

[0047] The Vacant Facility Renovation Department can analyze design data and propose barrier-free designs or energy-efficient equipment layouts. For example, AI can analyze a facility's design data and propose barrier-free designs. For example, it can propose eliminating steps or installing handrails. The Vacant Facility Renovation Department can also propose energy-efficient equipment layouts. For example, it can propose introducing solar power generation or using insulation materials. The Vacant Facility Renovation Department can also propose installing energy-efficient lighting. This can provide an environment where elderly people can live comfortably.

[0048] The communication support unit can act as a conversation partner for the elderly and respond to everyday conversations or consultations. For example, the communication support unit uses AI to act as a conversation partner for the elderly and respond to everyday conversations. For example, the AI ​​will ask questions such as "What did you do today?" and listen to what the elderly has to say. The communication support unit also uses AI to respond to consultations from the elderly. For example, it can provide health and lifestyle consultations. This can help reduce the sense of loneliness felt by the elderly.

[0049] The day service provision unit can monitor the health condition of the elderly and suggest an exercise program or rehabilitation. For example, AI can monitor the health condition of the elderly and suggest an exercise program. For example, AI can analyze the walking data of the elderly and suggest balance training. The day service provision unit can also suggest rehabilitation. For example, AI can suggest strength training for the elderly. The day service provision unit can also use AI to manage the dietary content of the elderly and provide nutritionally balanced meals. This can help maintain and improve the health of the elderly.

[0050] The housing facility providing unit can automatically adjust the room temperature or lighting to create an environment that suits the elderly person's lifestyle rhythm. In the housing facility providing unit, for example, AI automatically adjusts the room temperature. For example, AI adjusts the room temperature to suit the elderly person's lifestyle rhythm. In addition, the housing facility providing unit automatically adjusts the lighting. For example, AI adjusts the lighting to suit the elderly person's lifestyle rhythm. This makes it possible to provide an environment where the elderly can live comfortably.

[0051] The transportation service provider can analyze the transportation needs of the elderly and suggest the optimal means of transportation. For example, AI can manage the schedules of the elderly and arrange for self-driving cars when necessary. The transportation service provider can also use AI to analyze traffic conditions in real time and suggest the optimal route. This can efficiently support the transportation of the elderly.

[0052] The shopping support unit can analyze the consumption patterns of the elderly and automatically order the necessary items. For example, AI can analyze the consumption patterns of the elderly and automatically order the necessary items. For example, AI can analyze the consumption patterns of the elderly and periodically order the necessary items. The shopping support unit can also use AI to suggest products that suit the preferences and health condition of the elderly. For example, AI can suggest health foods that suit the health condition of the elderly. This can efficiently support shopping for the elderly.

[0053] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0054] The care support system can further include a hobby activity support unit that supports elderly people in their hobby activities. The hobby activity support unit analyzes the elderly's hobbies and interests and suggests appropriate hobby activities. For example, the hobby activity support unit uses AI to analyze the elderly's past hobby activity data and suggest hobby activities such as painting classes or music classes. The hobby activity support unit also uses AI to consider the elderly's physical strength and health condition and suggest hobby activities that are within their reasonable range. Furthermore, the hobby activity support unit can also use AI to find common hobbies between elderly people and suggest group activities. This can improve the quality of life of elderly people and reduce their sense of loneliness.

[0055] The care support system can also be equipped with a health monitoring unit that monitors the health status of elderly people in real time. The health monitoring unit constantly monitors the elderly's vital signs, such as heart rate, blood pressure, and body temperature, and responds promptly if an abnormality is detected. For example, the health monitoring unit uses AI to analyze the elderly's vital signs and notify a medical institution if an abnormality is detected. The health monitoring unit can also use AI to analyze the elderly's health status and provide advice on daily life and health management. Furthermore, the health monitoring unit can use AI to accumulate the elderly's health data and propose long-term health management plans. This can help maintain and improve the health of the elderly.

[0056] The care support system can further include an emotional support unit that estimates the emotions of the elderly and provides support based on those emotions. The emotional support unit estimates emotions from the elderly's facial expressions, tone of voice, choice of words, etc., and responds appropriately. For example, the emotional support unit uses AI to analyze the elderly's facial expressions and, if they look sad, offer words of encouragement. The emotional support unit also uses AI to analyze the elderly's tone of voice and, if they are feeling stressed, suggest relaxing music. Furthermore, the emotional support unit can analyze the elderly's choice of words and, if they are feeling lonely, suggest activities to promote communication. This can support the mental health of the elderly.

[0057] The care support system can further include a meal support unit that supports the elderly with their meals. The meal support unit analyzes the elderly's nutritional status and preferences and proposes an appropriate meal plan. For example, the meal support unit uses AI to analyze the elderly's nutritional status and propose a nutritionally balanced meal menu. The meal support unit can also use AI to analyze the elderly's preferences and provide meals tailored to their tastes. Furthermore, the meal support unit can use AI to take the elderly's health status into consideration and propose a meal plan that addresses specific health issues. This helps maintain the health of the elderly and provide them with the enjoyment of eating.

[0058] The care support system can also be equipped with a safety monitoring unit to ensure the safety of the elderly. The safety monitoring unit constantly monitors the elderly's living environment and responds quickly if an abnormality occurs. For example, the safety monitoring unit uses AI to analyze the elderly's movements and notify emergency contacts if an accident such as a fall occurs. The safety monitoring unit can also use AI to analyze the elderly's living environment and issue an alarm if it detects a risk such as a fire or gas leak. Furthermore, the safety monitoring unit can also use AI to analyze the elderly's living patterns and issue a warning if abnormal behavior is detected. This ensures the safety of the elderly and provides an environment where they can live with peace of mind.

[0059] The care support system can further include a social participation support unit that promotes social participation among the elderly. The social participation support unit analyzes the interests and skills of the elderly and suggests appropriate social activities. For example, the social participation support unit uses AI to analyze the elderly's past work history and hobbies and suggest volunteer activities or participation in local events. The social participation support unit can also use AI to analyze the elderly's skills and suggest mentoring and educational activities for local young people. Furthermore, the social participation support unit can use AI to analyze the elderly's interests and suggest participation in online communities. This can promote social participation among the elderly and reduce feelings of isolation.

[0060] The care support system can further include a relaxation support unit that supports relaxation for the elderly. The relaxation support unit analyzes the stress level of the elderly and suggests appropriate relaxation methods. For example, the relaxation support unit uses AI to analyze the stress level of the elderly and suggest relaxation music or meditation programs. The relaxation support unit can also use AI to analyze the elderly's preferences and suggest relaxation methods such as aromatherapy or massage. Furthermore, the relaxation support unit can use AI to analyze the elderly's daily rhythm and suggest appropriate rest times. This helps reduce stress for the elderly and maintain their physical and mental health.

[0061] The care support system can further include a learning support unit that supports the elderly's learning. The learning support unit analyzes the elderly's interests and learning needs and suggests appropriate learning programs. For example, the learning support unit uses AI to analyze the elderly's interests and suggest online courses or workshops. The learning support unit can also use AI to analyze the elderly's learning pace and suggest learning programs that are within their reasonable range. Furthermore, the learning support unit can use AI to analyze the elderly's past learning history and suggest continuous learning plans. This can improve the elderly's knowledge and skills and support lifelong learning.

[0062] The care support system can further include an entertainment provider that estimates the emotions of the elderly person and provides entertainment based on those emotions. The entertainment provider analyzes the emotions of the elderly person and suggests appropriate entertainment. For example, the entertainment provider uses AI to analyze the emotions of the elderly person and suggest movies or music if they want to relax. The entertainment provider can also analyze the emotions of the elderly person and suggest comedy shows or games if they want to cheer up. Furthermore, the entertainment provider can analyze the emotions of the elderly person and suggest moving stories if they want to be moved. This allows entertainment to be provided according to the emotions of the elderly person, improving their quality of life.

[0063] The care support system can further include a pet care support unit that supports elderly people in caring for their pets. The pet care support unit analyzes the health status and needs of elderly people's pets and proposes appropriate care methods. For example, the pet care support unit uses AI to analyze the pet's health status and propose appropriate diet and exercise plans. The pet care support unit can also use AI to analyze the pet's behavior and propose ways to reduce stress. Furthermore, the pet care support unit can use AI to accumulate pet health data and propose long-term health management plans. This can provide an environment where elderly people can live with their pets with peace of mind.

[0064] The processing flow of the second embodiment will be briefly explained below.

[0065] Step 1: The Vacant Facility Renovation Department renovates vacant facilities. For example, it uses AI technology to smartly renovate vacant facilities such as abandoned schools and elementary schools, optimizing the layout and equipment within the facility. This creates an environment where elderly people can live comfortably. Specifically, the AI ​​analyzes the facility's design data and proposes barrier-free designs and energy-efficient equipment layouts. Step 2: The communication support unit supports communication between elderly people. For example, the AI ​​can act as a conversation partner for elderly people, providing everyday conversation and answering questions. The AI ​​can also analyze the emotions of elderly people and take appropriate measures to reduce feelings of loneliness. Step 3: The day care service provider provides day care services. For example, AI monitors the health of the elderly and suggests appropriate exercise programs and rehabilitation. AI also manages the elderly's diet and provides nutritionally balanced meals. Step 4: The Housing Facility Provision Department provides housing facilities. For example, AI manages the housing facilities and provides an environment where the elderly can live comfortably. AI also automatically adjusts the room temperature and lighting, creating an environment that suits the elderly's lifestyle. Step 5: The transportation service provider provides transportation services. For example, AI analyzes the mobility needs of elderly people and suggests the most suitable means of transportation. AI also manages the elderly people's schedules and arranges for self-driving cars when needed. Step 6: The shopping assistance provider provides shopping assistance. For example, AI manages the elderly person's shopping list and automatically orders the necessary items. AI also suggests products tailored to the elderly person's preferences and health condition.

[0066] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0067] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0068] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0069] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0070] 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.

[0071] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0072] 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.

[0073] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0074] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0075] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0076] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0077] 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.

[0078] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0079] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0080] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0081] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0082] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0083] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0084] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0085] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0086] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0087] 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.

[0088] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0089] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0090] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0091] 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.

[0092] 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.

[0093] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0094] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0095] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0096] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0097] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0098] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0099] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0100] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0101] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0102] 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.

[0103] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0104] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0105] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0106] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0107] 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.

[0108] 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.

[0109] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0110] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0111] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0112] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0113] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0114] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0115] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0116] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0117] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0118] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0119] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0120] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0121] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0122] 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.

[0123] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0124] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0125] 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.

[0126] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0127] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0128] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0129] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0130] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0131] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0132] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0133] 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. The Vacant Facilities Renovation Department, which renovates vacant facilities, A communication support department that supports communication among the elderly, A day service department that provides day services; a housing facility provision department that provides housing facilities; a transportation service provider that provides transportation services; a shopping assistance providing unit that provides shopping assistance; A system characterized by:

2. The vacant facility renovation department Analyzing design data and proposing barrier-free designs or energy-efficient facility layouts 2. The system of claim 1.

3. The communication support unit To be a conversation partner for the elderly person and provide daily conversation or advice 2. The system of claim 1.

4. The day service providing unit Monitor the health status of the elderly person and suggest an exercise program or rehabilitation program.

2. The system of claim 1.

5. The housing facility providing department Automatically adjust room temperature or lighting to create an environment that matches the elderly person's lifestyle.

2. The system of claim 1.

6. The transportation service providing unit Analyze the mobility needs of the elderly and propose the most suitable means of transportation 2. The system of claim 1.

7. The shopping support providing unit Analyze the elderly person's consumption patterns and automatically order the necessary items.

2. The system of claim 1.

8. The vacant facility renovation department Analyze the historical background or local culture of the facility and make design proposals based on that.

2. The system of claim 1.

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