system

Abstract

We provide the system. [Solution] A means of using generative artificial intelligence to analyze input data and generate individually optimized plans, A means of providing an intuitive interface for users to easily input their daily health status and activity records, A means of checking and receiving the generated plan in real time, A means of communication that enables information sharing among family members, A means of accumulating input care data and evaluating health status based on that data, A system that includes this.

Description

Technical Field

[0005] , , ,

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In an aging society, many families have concerns about caregiving, but the problem is that appropriate consultation sources and solutions are limited. In particular, the problem is that information sharing among family members is not smoothly carried out, and the quality of caregiving may decline. Also, it is difficult to create a care plan optimized for each individual user, and the burden on caregivers is increasing.

Means for Solving the Problems

[0005] This invention solves the aforementioned problems by providing a means for analyzing input data using generative artificial intelligence and generating individually optimized care plans. Furthermore, it addresses the lack of communication in caregiving by providing a communication means that enables information sharing among family members. Additionally, it realizes effective care support by providing a means for accumulating input care data and evaluating health status based on that data.

[0006] "Generative artificial intelligence" is an artificial intelligence technology that has the function of automatically generating optimal plans and proposals based on input data.

[0007] A "care plan" is a plan that outlines the daily care activities and support provided, based on the individual user's health condition and living environment.

[0008] "Communication methods" refer to methods and technologies for transmitting information between multiple distant terminals or devices, and in particular, to functions that facilitate information exchange among family members.

[0009] "Data analysis" is the process or technique of analyzing collected information and deriving useful patterns or meanings from it.

[0010] "Information sharing" is the act of providing data and knowledge to each other among individual users and systems to deepen a shared understanding.

[0011] "Health assessment" is the process of determining a user's current physical and mental health status based on accumulated data.

[0012] "Input data" refers to information provided by the user or other devices, which is used for analysis and evaluation. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0014] [[ID=??]] 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.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a numbered 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), or magnetic tapes, etc.

[0019] In the following embodiments, a numbered communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is a care support system that utilizes generative artificial intelligence and is mainly composed of three roles: server, terminal, and user. Specific examples are shown below.

[0035] Server Role

[0036] The server plays a central role in accumulating and analyzing data submitted by users. Using generative artificial intelligence, it analyzes input health data and care history to generate individually optimized care plans. For example, if a user submits records of meals and exercise, the server uses that information to evaluate nutritional balance and create an improvement plan. The server also sends the generated care plan and important notifications to the user's terminal, providing real-time information.

[0037] Terminal role

[0038] The terminal provides an interface for users to record caregiving activities and input information. Users input daily caregiving data into the terminal, and this information is automatically transmitted to the server. For example, the terminal includes fields for meal content, medication status, and activity levels; inputting this data contributes to optimizing the care plan. Furthermore, the terminal displays information transmitted from the server, supporting communication among family members.

[0039] User roles

[0040] Users utilize this system to record information related to caregiving and implement daily care according to suggestions from the server. For example, if a family member of an elderly person reports a loss of appetite, the user can input this information, review the meal plan generated by the server, and improve the diet according to the plan. Communication among users is also facilitated, enabling smooth information sharing.

[0041] As described above, this invention enables efficient and effective care support through the collaboration of a server, terminal, and user. This is expected to reduce the burden on caregivers and improve the quality of life for the elderly.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] Users use a device to input information about their daily care activities and health status. This includes information such as what they eat, whether they exercise, their medication status, and changes in their physical condition.

[0045] Step 2:

[0046] The terminal converts the information entered by the user into a standardized data format and sends it to the server. This conversion includes data integrity checks and processing to fill in any missing data.

[0047] Step 3:

[0048] The server stores the received data and saves it in a database. The stored data is used for later analysis and to generate feedback for users.

[0049] Step 4:

[0050] The server uses generative artificial intelligence to analyze the accumulated data. This analysis includes pattern recognition and anomaly detection to generate care plans tailored to each individual user.

[0051] Step 5:

[0052] The server sends the generated care plan and important notifications to the user's device. The transmitted information is immediately communicated to the user via the notification function.

[0053] Step 6:

[0054] Users review the care plan sent from their device and perform actual care activities according to its contents. They can approve or modify the plan as needed.

[0055] Step 7:

[0056] The terminal then sends the progress and results of the care activities back to the server. This allows the server to continuously optimize the care plan using the latest information.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] In elderly care, it is essential to provide optimal care plans tailored to each individual's health and living situation, and to ensure smooth information sharing among all parties involved. However, conventional systems require manual data collection and analysis, making it difficult to provide efficient care. This increases the burden on caregivers and hinders the improvement of the quality of life for the elderly.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server includes means for analyzing input information using generative artificial intelligence and generating individually optimized support plans, communication means for enabling data sharing among stakeholders, and means for accumulating input care information and evaluating health status based on that information. This makes it possible to efficiently manage the health status of the elderly and quickly provide optimal care plans. Furthermore, smooth information sharing among stakeholders is realized through the communication means, aiming to reduce the burden of caregiving work and improve the quality of life for the elderly.

[0062] "Generative artificial intelligence" is an information processing technology that can analyze input data and generate optimized information and plans based on given criteria.

[0063] A "support plan" is a plan designed to provide optimal care and services tailored to each user's health condition and living situation.

[0064] "Communication means" refers to a means of sending and receiving information bidirectionally, enabling data sharing and communication among stakeholders.

[0065] "Care information" refers to data about the health status and daily living conditions of the person receiving care, and is the basis for creating and adjusting care plans.

[0066] "Means of assessing health status" refers to methods for analyzing and evaluating an individual's health status based on collected care information, and for identifying necessary care and points of attention.

[0067] A "user information processing device" refers to a terminal that provides an information input / output interface and displays data and plans transmitted from a server.

[0068] This invention is a support system that utilizes generative artificial intelligence, and its main components include three roles: server, terminal, and user.

[0069] The server plays a central role in managing and performing advanced analysis of care information submitted by users. Specifically, the server uses generative AI models (such as the widely used natural language processing model GPT) to analyze the input information on health status and lifestyle. Based on the analysis, it generates individually optimized support plans. These plans include suggestions for diet and exercise to support the user's health improvement. The server also enables real-time information sharing by sending the generated plans and important announcements to the user's device.

[0070] The terminal provides an interface for users to input daily care information. Users input information such as diet, activity levels, and medication status into the terminal and send this data to the server. The terminal displays the support plan sent from the server on its screen, allowing users to implement appropriate care based on this data. The terminal also serves as a tool to support communication between family members and caregivers.

[0071] Users can utilize this system to provide care tailored to their individual needs. For example, if a family member of an elderly person reports loss of appetite to the terminal, the server will generate an appropriate meal plan based on analysis and notify the user through the terminal. This allows for improvements to the diet and supports the maintenance of the elderly person's health. Based on the input information, the server adjusts the support plan and provides continuous support.

[0072] One concrete example is using prompt statements to ask questions to the AI ​​model. For instance, "Assess the nutritional value of the meal for an elderly person. Please indicate the nutritional standards that the meal in this picture should meet and suggest improvements if necessary." By using such prompt statements, the server can leverage the insights provided by the generating AI model to deliver a fast and accurate care plan.

[0073] This system is expected to reduce the burden on caregivers while simultaneously improving the quality of life for the elderly.

[0074] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0075] Step 1:

[0076] The terminal receives care information entered by the user. Specifically, the user records data such as meal details, activity levels, and medication status through the terminal's interface. This input data is stored on the terminal in an organized format along with the date, and then sent to the server. The output is the organized care information data, which is then sent to the server.

[0077] Step 2:

[0078] The server receives care information sent from the terminal. The received data is stored in the server's internal database. Next, this data is preprocessed to be passed to the generating AI model. Specifically, it is converted to the required data format, and missing values ​​are imputed and invalid data is removed. As output, data formatted for analysis is sent to the generating AI model.

[0079] Step 3:

[0080] The server inputs the formatted data into a generative AI model and performs the analysis. Prompts are used to ask the AI ​​model specific questions. For example, it might instruct the model to "evaluate nutritional balance and suggest improvements based on recent meal content." Based on the input data and prompts, the generative AI model outputs analysis results optimized for each individual user. The output is received by the server as improvement suggestions and recommended action plans.

[0081] Step 4:

[0082] The server receives output from the generated AI model and creates a support plan for each individual user. The plan includes specific suggestions for diet and exercise. The support plan is formatted on the server and prepared for transmission to the terminal as a notification. The output is the completed support plan data.

[0083] Step 5:

[0084] The server delivers the support plan to the terminal. The user's terminal receives the notification from the server and displays its contents on the screen. The user adjusts their daily activities based on this information and improves the quality of care. The output is displayed to the user as the support plan and related information presented.

[0085] Step 6:

[0086] The user inputs the results of the care provided and any newly noticed information into the terminal and provides feedback to the server. The server uses this feedback information to re-evaluate the support plan and adjust it by performing additional analysis using a generative AI model if necessary. The output is then sent back to the terminal as the adjusted support plan.

[0087] (Application Example 1)

[0088] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0089] In modern society, the number of elderly people requiring care is increasing, and the burden of care on families is becoming a major problem. Caregivers are required to efficiently manage the health status of those requiring care and develop optimal care plans, but the tools and systems for this are still not sufficiently developed. In particular, sharing information among family members and keeping daily health records tends to be cumbersome, making smooth communication and management difficult.

[0090] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0091] This invention includes a server that uses generative artificial intelligence to analyze input data and generate individually optimized plans, a means to provide an intuitive interface for users to easily input their daily health status and activity records, and a means to check and receive the generated plans in real time. This enables the efficient and effective formulation of care plans and facilitates information sharing and communication among family members.

[0092] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to automatically analyze input data and generate optimal plans and information based on that analysis.

[0093] "Data analysis" is the process of thoroughly examining input information, finding meaning in it, and transforming it into useful information and knowledge.

[0094] An "individually optimized plan" refers to a care plan that has been tailored to the optimal content according to the individual circumstances and needs of each user.

[0095] "Providing an interface" means setting up a user interface or means for users to input data into the system.

[0096] "Real-time viewing" means being able to directly see the generated information and plans without delay.

[0097] "Communication methods that enable information sharing" refer to technologies and methods that allow family members and others to send and share data and messages for common use.

[0098] "Assessing health status" means judging and diagnosing an individual's physical condition and health level based on the health information entered.

[0099] The system that realizes this invention consists of three elements: a server, a terminal, and a user. The server utilizes generative artificial intelligence to receive input health data and activity records and generate a care plan optimized for each individual user. This involves data analysis and plan generation using generative AI models such as OpenAI's GPT. Specifically, it evaluates nutritional balance and exercise levels based on the dietary content and activity data submitted by the user and provides improvement plans as needed.

[0100] The device, through an interface built with React Native, allows users to easily record their daily health status and caregiving activities. It also displays care plans and notifications sent from the server in real time, facilitating information sharing among family members.

[0101] Users can use this system to input daily health data and check care plans provided by the server to optimize their daily care. For example, if an elderly person has recently complained of loss of appetite, the user inputs this information into their device, and the server generates a new meal plan based on that data and notifies the device. A specific plan such as, "Let's try a meal plan that includes vegetable soup," is provided.

[0102] As an example of a prompt for a generative AI model, text such as "Please suggest an optimal meal plan based on Mr. / Ms. Tanaka's recent health data" can be used. In this way, users can provide more effective and personalized care with the help of AI.

[0103] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0104] Step 1:

[0105] Users input health data and activity records from their devices. This data includes information such as diet, exercise levels, and medication status. The device automatically prepares to send this data to the server. The input data is formatted in JSON format, encrypted, and sent to the server.

[0106] Step 2:

[0107] The server analyzes the received data and activates the generating artificial intelligence. Based on the input health data, it calls up a generating AI model and generates a prompt message. The prompt message is created in the format of "Please suggest the optimal health plan based on the user's recent health data." The AI ​​then generates a care plan based on this prompt.

[0108] Step 3:

[0109] The server evaluates the generated care plan and performs further detailed analysis as needed. Here, the server checks nutritional balance and exercise plans, and adjusts the plan to suit the user. The server then formats the AI-generated output into a personalized message format for the user.

[0110] Step 4:

[0111] The refined care plan and related information are sent to the device. The device receives this information and prepares to display it through the user interface. The user receives notifications about new care plans and health status updates.

[0112] Step 5:

[0113] Users incorporate plans provided by the server via their devices into their daily lives. They can also provide feedback after executing the plan. User behavior data is sent back to the server and used to generate future plans.

[0114] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0115] This invention is a care support system that combines an emotion engine, enabling the server, terminal, and user to work together to improve the quality of care. This allows for care support that incorporates emotional information. Specific examples are shown below.

[0116] Server Role

[0117] The server has a central function of collecting and analyzing data sent from users and devices. While the generative artificial intelligence analyzes health status data and care history, the emotion engine analyzes the user's emotional data. Specifically, emotional data is extracted from the user's text input and voice data and analyzed on the server. This allows for an understanding of how changes in emotions affect care plans and enables dynamic adjustments to those plans.

[0118] Terminal role

[0119] The terminal is used to record the user's caregiving activities and input their emotional state. Through the terminal, users can report not only daily caregiving activities but also their emotions and stress levels at the time, and the terminal prepares to send this information to the server. For example, the terminal uses speech recognition or text recognition to identify emotions and extract the corresponding data. This allows emotion-based information to be transmitted to the server in real time.

[0120] User roles

[0121] By using this system, users can obtain care plans that take emotions into account and implement daily care activities. For example, if the emotion engine analyzes that the user's stress level is high, the server can incorporate relaxation-recommended activities into the plan in addition to the usual plan. This approach makes it easier for both the user and their family to recognize emotional changes and take appropriate actions.

[0122] As described above, the introduction of the emotion engine in this invention makes it possible for the care support system to comprehensively support not only physical health but also psychological health. This is expected to not only improve the user's QOL (quality of life) but also to foster closer communication with family members and caregivers.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] Users input daily care activities, health status, and emotional state into the device. This includes information such as meal details, activities, and changes in emotions, using text or voice input.

[0126] Step 2:

[0127] The terminal receives information entered by the user and extracts emotional data through text and voice analysis. It then formats the data and prepares it for transmission to the server.

[0128] Step 3:

[0129] The device transmits processed health and emotional data to the server. This data transmission is performed rapidly in real time.

[0130] Step 4:

[0131] The server stores the received health and emotional data in a database. After storage, it begins data analysis using generative artificial intelligence and an emotion engine.

[0132] Step 5:

[0133] The server generates care plans using generative artificial intelligence and analyzes emotional data with an emotion engine. For example, it adds activities including relaxation for users with high stress levels.

[0134] Step 6:

[0135] The server sends the generated care plan to the terminal and notifies the user. This plan includes adjustments based on the user's emotions.

[0136] Step 7:

[0137] The user reviews the care plan displayed on the device and performs the designated activities. As feedback, they re-enter their activities and emotional state for the day into the device.

[0138] Step 8:

[0139] The terminal sends the feedback information back to the server, preparing for the next data analysis. This allows the server to continuously adjust the care plan.

[0140] (Example 2)

[0141] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0142] In recent years, improving the quality of care requires comprehensive care that considers not only physical health but also psychological health. However, the current system makes it difficult to accurately grasp the emotional state of users and adjust care plans accordingly. Furthermore, insufficient information sharing among family members makes it difficult to fully understand the user's condition.

[0143] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0144] This invention includes a server that uses generative artificial intelligence to analyze input information and generate individually optimized plans, means for performing analysis based on emotional data and dynamically adjusting the plans, and communication means for enabling information sharing between relationships. This makes it possible to comprehensively understand the user's emotions and health condition and provide appropriately optimized care plans. Furthermore, sharing useful information among family members can further enhance the consistency and effectiveness of care.

[0145] "Generative artificial intelligence" is an artificial intelligence technology that analyzes input information and generates plans and proposals tailored to individual needs.

[0146] An "individually optimized plan" is a plan that aims to provide the most suitable services and activities for a particular user, based on their health and emotional state.

[0147] "Emotional data" refers to information about emotions extracted from user feedback, text, and other sources, and is data that indicates psychological health and stress levels.

[0148] "Dynamic adjustment" refers to modifying existing plans and settings in real time in response to newly obtained data and changes in circumstances.

[0149] "Communication methods" is a general term for the technologies and protocols used to send and receive data and information between servers, terminals, and users.

[0150] "Record data" refers to various types of data related to the user, such as care activities, health status, and daily events, and is used as the basis for evaluating their health and emotional state.

[0151] This invention is a system aimed at analyzing the health and emotional state of users and providing individually optimized care plans. This system is designed so that the server, terminals, and users each play specific roles and work together.

[0152] Server Role

[0153] The server acts as the central hub of the system, accumulating and analyzing data. Equipped with generative artificial intelligence, the server receives and stores voice and text data transmitted from terminals. Based on user-related health and emotional data, the generative AI generates personalized care plans tailored to individual needs. The emotion engine meticulously analyzes emotional data extracted from the user's voice and text, dynamically adjusting the plan accordingly.

[0154] Terminal role

[0155] The terminal refers to devices such as mobile phones and tablets that have the function of receiving user input and sending it to the server. Specifically, it has the function of converting the user's voice data into text using speech recognition technology and extracting emotional data. HTTPS is used as the communication protocol to evaluate the emotional state in real time and securely transmit the information to the server.

[0156] User roles

[0157] The user is the one who inputs their emotions and health status regarding caregiving and daily life into the terminal. The system allows the user to receive a generated care plan from the terminal and perform appropriate activities based on its instructions. For example, if the system analyzes that the user is experiencing high stress levels, the server will recommend relaxation activities, which the user can then view on the terminal.

[0158] Specific example

[0159] The user voice-inputs "I'm feeling a little stressed today" into the device. The device performs voice recognition and sends the data to the server. The server uses an emotion engine to analyze the stress level and adjusts the care plan to include relaxation activities. A prompt to the generated AI model might be, "Optimize the care plan based on the latest health data and emotion analysis."

[0160] Thus, this system is expected to improve the quality of care services by providing comprehensive care plans that include user emotional data.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] The device accepts voice and text input from the user. The user inputs their emotions and health status through the device's app. Specifically, speech recognition technology converts speech into text and captures it as input. This input data undergoes preliminary processing to identify emotions.

[0164] Step 2:

[0165] The device sends pre-processed emotional data and health information to the server. This involves error checking to ensure the data is transmitted accurately and transferring the data to the server using the secure communication protocol HTTPS. The output includes the processed emotional data and health information.

[0166] Step 3:

[0167] The server receives data from the terminal and stores it in a database. Generative artificial intelligence analyzes this data and uses an emotion engine to evaluate the user's emotional state and health status. In this step, a machine learning algorithm analyzes the user's psychological tendencies based on the emotional data. The analysis results are generated as output.

[0168] Step 4:

[0169] The server generates and dynamically adjusts care plans based on the analysis results. Specifically, a plan is formed that includes relaxation activities and recommendations for specific behaviors based on emotional changes. A generative AI model is involved in this process, outputting an optimal plan tailored to the user's characteristics.

[0170] Step 5:

[0171] The server sends the generated care plan to the terminal. The terminal displays the received plan to the user and, in some cases, can provide voice notifications. This care plan output includes specific guidelines to support daily care activities.

[0172] Step 6:

[0173] Users review the care plan provided through their device and take action accordingly. User feedback is sent back to the server via the device and used for further analysis. This feedback process continuously improves the accuracy of the care plan.

[0174] (Application Example 2)

[0175] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0176] Conventional care support systems failed to adequately consider users' emotions and had an insufficient understanding of their psychological health, making it difficult to fully optimize care plans. Furthermore, they were unable to dynamically adjust care plans based on real-time emotion analysis, making it difficult to improve users' quality of life (QOL).

[0177] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0178] In this invention, the server includes means for analyzing input data using generative artificial intelligence and generating individually optimized care plans, means for acquiring emotional data using emotion analysis technology and dynamically adjusting the care plan based on the acquired emotional information, and means for analyzing emotional data in real time via various measuring devices and storing it for generating suggestions. This makes it possible to reflect the user's emotional state in the care plan and provide corresponding care support.

[0179] "Generative artificial intelligence" refers to artificial intelligence technology that analyzes input data and generates optimal results tailored to a specific purpose.

[0180] An "individually optimized care plan" is a plan that is customized based on each user's health condition and emotional information, in order to provide the most appropriate care for each individual.

[0181] "Communication methods" refer to digital technologies and systems that enable the rapid and accurate sharing of information between people.

[0182] "Means of evaluating health status" refers to the processes and technologies used to analyze and evaluate a user's physical and mental health based on accumulated data.

[0183] "Emotional analysis technology" refers to the technology used to extract and analyze emotional information from data such as voice, text, and facial expressions.

[0184] A "dynamic adjustment mechanism" refers to a function that automatically adapts and optimizes plans and procedures in response to changes in acquired information and conditions.

[0185] "Various measuring devices" refers to a collection of sensors and devices used to collect information such as emotional data.

[0186] "Real-time analysis" refers to the technology of processing and analyzing data almost simultaneously with its generation.

[0187] "Storage means" refers to a digital storage system used to hold analysis results and proposals.

[0188] This invention is a care support system that combines an emotional engine and was built to improve the quality of care. Its details are described below.

[0189] The server plays a central role in this system, analyzing the input user data to generate individually optimized care plans. It utilizes generative artificial intelligence to comprehensively analyze the user's health status and care history, and further uses emotional data extracted from voice and text to dynamically adjust the care plan. This process employs an AI model built using Python and TENSORFLOW®. Furthermore, for emotional analysis, it utilizes Google® Cloud's Speech-to-Text API for voice data, and OpenCV is used for image processing.

[0190] The terminal functions as a device used by users and care staff in their daily work. Terminals such as smartphones and smart glasses acquire voice and facial expressions in real time and transmit this data to a server. Therefore, various measuring devices are used on the terminal, enabling real-time analysis of the acquired data. The analysis results are stored via Firebase in the cloud, and suggestions are generated as needed.

[0191] Users carry out care activities according to the care plan provided by the system. If the emotional engine analyzes that the stress level is high, for example, the system will suggest relaxation methods in addition to the normal plan. Through this process, users and their families can more easily recognize emotional changes and take appropriate actions.

[0192] For example, if a user indicates feelings of "anxiety" in their recorded situation, the server generates suggestions for additional relaxation activities and notifies the user's terminal accordingly. This allows caregivers to respond quickly, thereby improving the user's quality of life (QOL).

[0193] Example of a prompt:

[0194] "What relaxation methods would you suggest when a user shows signs of anxiety?"

[0195] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0196] Step 1:

[0197] The device collects the user's facial expressions and voice data. This is done using the camera and microphone of a smartphone or smart glasses. The input is the user's facial image and voice, and the output is this digital data. Image processing using OpenCV and speech-to-text conversion using Google Cloud Speech-to-Text are performed within the device.

[0198] Step 2:

[0199] The terminal collects data and sends it to the server. The input consists of facial expression image data and transcribed audio data, and the output is the transmission of data to the server. In this process, data is transferred to the server in real time using communication methods.

[0200] Step 3:

[0201] The server analyzes the received data and extracts emotional information. The input is the data sent in step 2, and the output is the emotional analysis result. On the server, a generative AI model using TensorFlow runs to determine the user's emotions from facial expression data and text data.

[0202] Step 4:

[0203] The server dynamically adjusts the care plan based on emotional information. The input is the result of the emotional analysis, and the output is the updated care plan proposal. The emotional engine takes this analysis result into consideration and adds relaxation activities as needed.

[0204] Step 5:

[0205] The server notifies the terminal of the updated care plan. The input is the updated care plan draft, and the output is the provision of information to the terminal. The proposal is sent to caregivers and users from Firebase in the cloud.

[0206] Step 6:

[0207] The user receives a notification and then performs specific caregiving activities. The input is notification data from the server, and the output is the actual caregiving action. An example prompt, "What relaxation method would you suggest when the user shows signs of anxiety?", is reflected in the caregiver's actions.

[0208] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0209] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0210] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0211] [Second Embodiment]

[0212] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0213] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0214] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0215] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0216] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0217] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0218] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0219] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0220] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0221] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0222] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0223] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0224] This invention is a care support system that utilizes generative artificial intelligence and is mainly composed of three roles: server, terminal, and user. Specific examples are shown below.

[0225] Server Role

[0226] The server plays a central role in accumulating and analyzing data submitted by users. Using generative artificial intelligence, it analyzes input health data and care history to generate individually optimized care plans. For example, if a user submits records of meals and exercise, the server uses that information to evaluate nutritional balance and create an improvement plan. The server also sends the generated care plan and important notifications to the user's terminal, providing real-time information.

[0227] Terminal role

[0228] The terminal provides an interface for users to record caregiving activities and input information. Users input daily caregiving data into the terminal, and this information is automatically transmitted to the server. For example, the terminal includes fields for meal content, medication status, and activity levels; inputting this data contributes to optimizing the care plan. Furthermore, the terminal displays information transmitted from the server, supporting communication among family members.

[0229] User roles

[0230] Users utilize this system to record information related to caregiving and implement daily care according to suggestions from the server. For example, if a family member of an elderly person reports a loss of appetite, the user can input this information, review the meal plan generated by the server, and improve the diet according to the plan. Communication among users is also facilitated, enabling smooth information sharing.

[0231] As described above, this invention enables efficient and effective care support through the collaboration of a server, terminal, and user. This is expected to reduce the burden on caregivers and improve the quality of life for the elderly.

[0232] The following describes the processing flow.

[0233] Step 1:

[0234] Users use a device to input information about their daily care activities and health status. This includes information such as what they eat, whether they exercise, their medication status, and changes in their physical condition.

[0235] Step 2:

[0236] The terminal converts the information entered by the user into a standardized data format and sends it to the server. This conversion includes data integrity checks and processing to fill in any missing data.

[0237] Step 3:

[0238] The server stores the received data and saves it in a database. The stored data is used for later analysis and to generate feedback for users.

[0239] Step 4:

[0240] The server uses generative artificial intelligence to analyze the accumulated data. This analysis includes pattern recognition and anomaly detection to generate care plans tailored to each individual user.

[0241] Step 5:

[0242] The server sends the generated care plan and important notifications to the user's device. The transmitted information is immediately communicated to the user via the notification function.

[0243] Step 6:

[0244] Users review the care plan sent from their device and perform actual care activities according to its contents. They can approve or modify the plan as needed.

[0245] Step 7:

[0246] The terminal then sends the progress and results of the care activities back to the server. This allows the server to continuously optimize the care plan using the latest information.

[0247] (Example 1)

[0248] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0249] In elderly care, it is essential to provide optimal care plans tailored to each individual's health and living situation, and to ensure smooth information sharing among all parties involved. However, conventional systems require manual data collection and analysis, making it difficult to provide efficient care. This increases the burden on caregivers and hinders the improvement of the quality of life for the elderly.

[0250] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0251] In this invention, the server includes means for analyzing input information using generative artificial intelligence and generating individually optimized support plans, communication means for enabling data sharing among stakeholders, and means for accumulating input care information and evaluating health status based on that information. This makes it possible to efficiently manage the health status of the elderly and quickly provide optimal care plans. Furthermore, smooth information sharing among stakeholders is realized through the communication means, aiming to reduce the burden of caregiving work and improve the quality of life for the elderly.

[0252] "Generative artificial intelligence" is an information processing technology that can analyze input data and generate optimized information and plans based on given criteria.

[0253] A "support plan" is a plan designed to provide optimal care and services tailored to each user's health condition and living situation.

[0254] "Communication means" refers to a means of sending and receiving information bidirectionally, enabling data sharing and communication among stakeholders.

[0255] "Care information" refers to data about the health status and daily living conditions of the person receiving care, and is the basis for creating and adjusting care plans.

[0256] "Means of assessing health status" refers to methods for analyzing and evaluating an individual's health status based on collected care information, and for identifying necessary care and points of attention.

[0257] A "user information processing device" refers to a terminal that provides an information input / output interface and displays data and plans transmitted from a server.

[0258] This invention is a support system that utilizes generative artificial intelligence, and its main components include three roles: server, terminal, and user.

[0259] The server plays a central role in managing and performing advanced analysis of care information submitted by users. Specifically, the server uses generative AI models (such as the widely used natural language processing model GPT) to analyze the input information on health status and lifestyle. Based on the analysis, it generates individually optimized support plans. These plans include suggestions for diet and exercise to support the user's health improvement. The server also enables real-time information sharing by sending the generated plans and important announcements to the user's device.

[0260] The terminal provides an interface for users to input daily care information. Users input information such as diet, activity levels, and medication status into the terminal and send this data to the server. The terminal displays the support plan sent from the server on its screen, allowing users to implement appropriate care based on this data. The terminal also serves as a tool to support communication between family members and caregivers.

[0261] Users can utilize this system to provide care tailored to their individual needs. For example, if a family member of an elderly person reports loss of appetite to the terminal, the server will generate an appropriate meal plan based on analysis and notify the user through the terminal. This allows for improvements to the diet and supports the maintenance of the elderly person's health. Based on the input information, the server adjusts the support plan and provides continuous support.

[0262] One concrete example is using prompt statements to ask questions to the AI ​​model. For instance, "Assess the nutritional value of the meal for an elderly person. Please indicate the nutritional standards that the meal in this picture should meet and suggest improvements if necessary." By using such prompt statements, the server can leverage the insights provided by the generating AI model to deliver a fast and accurate care plan.

[0263] This system is expected to reduce the burden on caregivers while simultaneously improving the quality of life for the elderly.

[0264] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0265] Step 1:

[0266] The terminal receives care information entered by the user. Specifically, the user records data such as meal details, activity levels, and medication status through the terminal's interface. This input data is stored on the terminal in an organized format along with the date, and then sent to the server. The output is the organized care information data, which is then sent to the server.

[0267] Step 2:

[0268] The server receives care information sent from the terminal. The received data is stored in the server's internal database. Next, this data is preprocessed to be passed to the generating AI model. Specifically, it is converted to the required data format, and missing values ​​are imputed and invalid data is removed. As output, data formatted for analysis is sent to the generating AI model.

[0269] Step 3:

[0270] The server inputs the formatted data into a generative AI model and performs the analysis. Prompts are used to ask the AI ​​model specific questions. For example, it might instruct the model to "evaluate nutritional balance and suggest improvements based on recent meal content." Based on the input data and prompts, the generative AI model outputs analysis results optimized for each individual user. The output is received by the server as improvement suggestions and recommended action plans.

[0271] Step 4:

[0272] The server receives output from the generated AI model and creates a support plan for each individual user. The plan includes specific suggestions for diet and exercise. The support plan is formatted on the server and prepared for transmission to the terminal as a notification. The output is the completed support plan data.

[0273] Step 5:

[0274] The server delivers the support plan to the terminal. The user's terminal receives the notification from the server and displays its contents on the screen. The user adjusts their daily activities based on this information and improves the quality of care. The output is displayed to the user as the support plan and related information presented.

[0275] Step 6:

[0276] The user inputs the results of the care provided and any newly noticed information into the terminal and provides feedback to the server. The server uses this feedback information to re-evaluate the support plan and adjust it by performing additional analysis using a generative AI model if necessary. The output is then sent back to the terminal as the adjusted support plan.

[0277] (Application Example 1)

[0278] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0279] In modern society, the number of elderly people requiring care is increasing, and the burden of care on families is becoming a major problem. Caregivers are required to efficiently manage the health status of those requiring care and develop optimal care plans, but the tools and systems for this are still not sufficiently developed. In particular, sharing information among family members and keeping daily health records tends to be cumbersome, making smooth communication and management difficult.

[0280] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0281] This invention includes a server that uses generative artificial intelligence to analyze input data and generate individually optimized plans, a means to provide an intuitive interface for users to easily input their daily health status and activity records, and a means to check and receive the generated plans in real time. This enables the efficient and effective formulation of care plans and facilitates information sharing and communication among family members.

[0282] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to automatically analyze input data and generate optimal plans and information based on that analysis.

[0283] "Analyzing data" is a process of investigating the input information in detail to find meaning or convert it into useful information or knowledge.

[0284] "Individually optimized plan" refers to a care plan adjusted to the optimal content according to the situation and needs of each user.

[0285] "Providing an interface" means setting up an operation screen or means for the user to input data into the system.

[0286] "Real-time confirmation" means that the generated information and plans can be directly viewed on the spot without delay.

[0287] "Communication means enabling information sharing" refers to technologies or methods that enable data and messages to be transmitted and shared among family members and others for common use.

[0288] "Evaluating the health status" means judging and diagnosing an individual's physical condition and health level based on the input health-related information.

[0289] The system for realizing this invention consists of three elements: a server, a terminal, and a user. The server utilizes a generative artificial intelligence to receive the input health data and activity records and generate a care plan optimized for each user. This involves performing data analysis and plan generation using a generative AI model such as GPT of OpenAI. Specifically, based on the diet content and activity data sent by the user, the nutritional balance and amount of exercise are evaluated, and an improvement plan is provided if necessary.

[0290] The terminal enables the user to easily record their daily health status and care activities through an interface built using React Native. It also displays the care plan and notifications sent from the server in real time and supports information sharing among family members.

[0291] Users can use this system to input daily health data and check care plans provided by the server to optimize their daily care. For example, if an elderly person has recently complained of loss of appetite, the user inputs this information into their device, and the server generates a new meal plan based on that data and notifies the device. A specific plan such as, "Let's try a meal plan that includes vegetable soup," is provided.

[0292] As an example of a prompt for a generative AI model, text such as "Please suggest an optimal meal plan based on Mr. / Ms. Tanaka's recent health data" can be used. In this way, users can provide more effective and personalized care with the help of AI.

[0293] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0294] Step 1:

[0295] Users input health data and activity records from their devices. This data includes information such as diet, exercise levels, and medication status. The device automatically prepares to send this data to the server. The input data is formatted in JSON format, encrypted, and sent to the server.

[0296] Step 2:

[0297] The server analyzes the received data and activates the generating artificial intelligence. Based on the input health data, it calls up a generating AI model and generates a prompt message. The prompt message is created in the format of "Please suggest the optimal health plan based on the user's recent health data." The AI ​​then generates a care plan based on this prompt.

[0298] Step 3:

[0299] The server evaluates the generated care plan and performs further detailed analysis as needed. Here, the server checks nutritional balance and exercise plans, and adjusts the plan to suit the user. The server then formats the AI-generated output into a personalized message format for the user.

[0300] Step 4:

[0301] The refined care plan and related information are sent to the device. The device receives this information and prepares to display it through the user interface. The user receives notifications about new care plans and health status updates.

[0302] Step 5:

[0303] Users incorporate plans provided by the server via their devices into their daily lives. They can also provide feedback after executing the plan. User behavior data is sent back to the server and used to generate future plans.

[0304] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0305] This invention is a care support system that combines an emotion engine, enabling the server, terminal, and user to work together to improve the quality of care. This allows for care support that incorporates emotional information. Specific examples are shown below.

[0306] Server Role

[0307] The server has a central function of aggregating and analyzing data sent from users and terminals. While the generated artificial intelligence analyzes health data and care history, the emotion engine analyzes the user's emotion data. Specifically, emotion data is extracted from the user's text input and voice data and analyzed on the server. This enables understanding of how changes in emotion affect the care plan and allows for dynamic adjustment of the plan.

[0308] Role of the Terminal

[0309] The terminal is used for recording the user's care activities and inputting the emotional state. Through the terminal, the user can report not only the daily care content but also their emotions and stress levels at that time, and the terminal prepares to send this information to the server. For example, the terminal uses voice recognition and text recognition to identify emotions and extract corresponding data. This enables real-time transmission of emotion-based information to the server.

[0310] Role of the User

[0311] By using this system, the user can obtain a care plan that takes emotions into account and carry out daily care activities. For example, when analyzed by the emotion engine as "having a high stress level", in addition to the normal plan, the server can incorporate activities that recommend relaxation into the plan. This approach enables the user themselves and their family to recognize emotional changes and facilitates corresponding actions.

[0312] As described above, by introducing the emotion engine in the present invention, the care support system can comprehensively support not only physical health but also mental health. This not only makes it easier to improve the user's QOL (quality of life) but also is expected to tighten communication between the family and caregivers.

[0313] The following describes the processing flow.

[0314] Step 1:

[0315] Users input daily care activities, health status, and emotional state into the device. This includes information such as meal details, activities, and changes in emotions, using text or voice input.

[0316] Step 2:

[0317] The terminal receives information entered by the user and extracts emotional data through text and voice analysis. It then formats the data and prepares it for transmission to the server.

[0318] Step 3:

[0319] The device transmits processed health and emotional data to the server. This data transmission is performed rapidly in real time.

[0320] Step 4:

[0321] The server stores the received health and emotional data in a database. After storage, it begins data analysis using generative artificial intelligence and an emotion engine.

[0322] Step 5:

[0323] The server generates care plans using generative artificial intelligence and analyzes emotional data with an emotion engine. For example, it adds activities including relaxation for users with high stress levels.

[0324] Step 6:

[0325] The server sends the generated care plan to the terminal and notifies the user. This plan includes adjustments based on the user's emotions.

[0326] Step 7:

[0327] The user reviews the care plan displayed on the device and performs the designated activities. As feedback, they re-enter their activities and emotional state for the day into the device.

[0328] Step 8:

[0329] The terminal sends the feedback information back to the server, preparing for the next data analysis. This allows the server to continuously adjust the care plan.

[0330] (Example 2)

[0331] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0332] In recent years, improving the quality of care requires comprehensive care that considers not only physical health but also psychological health. However, the current system makes it difficult to accurately grasp the emotional state of users and adjust care plans accordingly. Furthermore, insufficient information sharing among family members makes it difficult to fully understand the user's condition.

[0333] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0334] This invention includes a server that uses generative artificial intelligence to analyze input information and generate individually optimized plans, means for performing analysis based on emotional data and dynamically adjusting the plans, and communication means for enabling information sharing between relationships. This makes it possible to comprehensively understand the user's emotions and health condition and provide appropriately optimized care plans. Furthermore, sharing useful information among family members can further enhance the consistency and effectiveness of care.

[0335] "Generative artificial intelligence" is an artificial intelligence technology that analyzes input information and generates plans and proposals tailored to individual needs.

[0336] An "individually optimized plan" is a plan that aims to provide the most suitable services and activities for a particular user, based on their health and emotional state.

[0337] "Emotional data" refers to information about emotions extracted from user feedback, text, and other sources, and is data that indicates psychological health and stress levels.

[0338] "Dynamic adjustment" refers to modifying existing plans and settings in real time in response to newly obtained data and changes in circumstances.

[0339] "Communication methods" is a general term for the technologies and protocols used to send and receive data and information between servers, terminals, and users.

[0340] "Record data" refers to various types of data related to the user, such as care activities, health status, and daily events, and is used as the basis for evaluating their health and emotional state.

[0341] This invention is a system aimed at analyzing the health and emotional state of users and providing individually optimized care plans. This system is designed so that the server, terminals, and users each play specific roles and work together.

[0342] Server Role

[0343] The server acts as the central hub of the system, accumulating and analyzing data. Equipped with generative artificial intelligence, the server receives and stores voice and text data transmitted from terminals. Based on user-related health and emotional data, the generative AI generates personalized care plans tailored to individual needs. The emotion engine meticulously analyzes emotional data extracted from the user's voice and text, dynamically adjusting the plan accordingly.

[0344] Terminal role

[0345] The terminal refers to devices such as mobile phones and tablets that have the function of receiving user input and sending it to the server. Specifically, it has the function of converting the user's voice data into text using speech recognition technology and extracting emotional data. HTTPS is used as the communication protocol to evaluate the emotional state in real time and securely transmit the information to the server.

[0346] User roles

[0347] The user is the one who inputs their emotions and health status regarding caregiving and daily life into the terminal. The system allows the user to receive a generated care plan from the terminal and perform appropriate activities based on its instructions. For example, if the system analyzes that the user is experiencing high stress levels, the server will recommend relaxation activities, which the user can then view on the terminal.

[0348] Specific example

[0349] The user voice-inputs "I'm feeling a little stressed today" into the device. The device performs voice recognition and sends the data to the server. The server uses an emotion engine to analyze the stress level and adjusts the care plan to include relaxation activities. A prompt to the generated AI model might be, "Optimize the care plan based on the latest health data and emotion analysis."

[0350] Thus, this system is expected to improve the quality of care services by providing comprehensive care plans that include user emotional data.

[0351] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0352] Step 1:

[0353] The device accepts voice and text input from the user. The user inputs their emotions and health status through the device's app. Specifically, speech recognition technology converts speech into text and captures it as input. This input data undergoes preliminary processing to identify emotions.

[0354] Step 2:

[0355] The device sends pre-processed emotional data and health information to the server. This involves error checking to ensure the data is transmitted accurately and transferring the data to the server using the secure communication protocol HTTPS. The output includes the processed emotional data and health information.

[0356] Step 3:

[0357] The server receives data from the terminal and stores it in a database. Generative artificial intelligence analyzes this data and uses an emotion engine to evaluate the user's emotional state and health status. In this step, a machine learning algorithm analyzes the user's psychological tendencies based on the emotional data. The analysis results are generated as output.

[0358] Step 4:

[0359] The server generates and dynamically adjusts care plans based on the analysis results. Specifically, a plan is formed that includes relaxation activities and recommendations for specific behaviors based on emotional changes. A generative AI model is involved in this process, outputting an optimal plan tailored to the user's characteristics.

[0360] Step 5:

[0361] The server sends the generated care plan to the terminal. The terminal displays the received plan to the user and, in some cases, can provide voice notifications. This care plan output includes specific guidelines to support daily care activities.

[0362] Step 6:

[0363] Users review the care plan provided through their device and take action accordingly. User feedback is sent back to the server via the device and used for further analysis. This feedback process continuously improves the accuracy of the care plan.

[0364] (Application Example 2)

[0365] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0366] Conventional care support systems failed to adequately consider users' emotions and had an insufficient understanding of their psychological health, making it difficult to fully optimize care plans. Furthermore, they were unable to dynamically adjust care plans based on real-time emotion analysis, making it difficult to improve users' quality of life (QOL).

[0367] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0368] In this invention, the server includes means for analyzing input data using generative artificial intelligence and generating individually optimized care plans, means for acquiring emotional data using emotion analysis technology and dynamically adjusting the care plan based on the acquired emotional information, and means for analyzing emotional data in real time via various measuring devices and storing it for generating suggestions. This makes it possible to reflect the user's emotional state in the care plan and provide corresponding care support.

[0369] "Generative artificial intelligence" refers to artificial intelligence technology that analyzes input data and generates optimal results tailored to a specific purpose.

[0370] An "individually optimized care plan" is a plan that is customized based on each user's health condition and emotional information, in order to provide the most appropriate care for each individual.

[0371] "Communication methods" refer to digital technologies and systems that enable the rapid and accurate sharing of information between people.

[0372] "Means of evaluating health status" refers to the processes and technologies used to analyze and evaluate a user's physical and mental health based on accumulated data.

[0373] "Emotional analysis technology" refers to the technology used to extract and analyze emotional information from data such as voice, text, and facial expressions.

[0374] A "dynamic adjustment mechanism" refers to a function that automatically adapts and optimizes plans and procedures in response to changes in acquired information and conditions.

[0375] "Various measuring devices" refers to a collection of sensors and devices used to collect information such as emotional data.

[0376] "Real-time analysis" refers to the technology of processing and analyzing data almost simultaneously with its generation.

[0377] "Storage means" refers to a digital storage system used to hold analysis results and proposals.

[0378] This invention is a care support system that combines an emotional engine and was built to improve the quality of care. Its details are described below.

[0379] The server plays a central role in this system, analyzing the input user data to generate individually optimized care plans. It utilizes generative artificial intelligence to comprehensively analyze the user's health status and care history, and further uses emotional data extracted from voice and text to dynamically adjust the care plan. This process employs an AI model built using Python and TensorFlow. Furthermore, for emotional analysis, it utilizes Google Cloud's Speech-to-Text API for voice data, and OpenCV is used for image processing.

[0380] The terminal functions as a device used by users and care staff in their daily work. Terminals such as smartphones and smart glasses acquire voice and facial expressions in real time and transmit this data to a server. Therefore, various measuring devices are used on the terminal, enabling real-time analysis of the acquired data. The analysis results are stored via Firebase in the cloud, and suggestions are generated as needed.

[0381] Users carry out care activities according to the care plan provided by the system. If the emotional engine analyzes that the stress level is high, for example, the system will suggest relaxation methods in addition to the normal plan. Through this process, users and their families can more easily recognize emotional changes and take appropriate actions.

[0382] For example, if a user indicates feelings of "anxiety" in their recorded situation, the server generates suggestions for additional relaxation activities and notifies the user's terminal accordingly. This allows caregivers to respond quickly, thereby improving the user's quality of life (QOL).

[0383] Example of a prompt:

[0384] "What relaxation methods would you suggest when a user shows signs of anxiety?"

[0385] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0386] Step 1:

[0387] The device collects the user's facial expressions and voice data. This is done using the camera and microphone of a smartphone or smart glasses. The input is the user's facial image and voice, and the output is this digital data. Image processing using OpenCV and speech-to-text conversion using Google Cloud Speech-to-Text are performed within the device.

[0388] Step 2:

[0389] The terminal collects data and sends it to the server. The input consists of facial expression image data and transcribed audio data, and the output is the transmission of data to the server. In this process, data is transferred to the server in real time using communication methods.

[0390] Step 3:

[0391] The server analyzes the received data and extracts emotional information. The input is the data sent in step 2, and the output is the emotional analysis result. On the server, a generative AI model using TensorFlow runs to determine the user's emotions from facial expression data and text data.

[0392] Step 4:

[0393] The server dynamically adjusts the care plan based on emotional information. The input is the result of the emotional analysis, and the output is the updated care plan proposal. The emotional engine takes this analysis result into consideration and adds relaxation activities as needed.

[0394] Step 5:

[0395] The server notifies the terminal of the updated care plan. The input is the updated care plan draft, and the output is the provision of information to the terminal. The proposal is sent to caregivers and users from Firebase in the cloud.

[0396] Step 6:

[0397] The user receives a notification and then performs specific caregiving activities. The input is notification data from the server, and the output is the actual caregiving action. An example prompt, "What relaxation method would you suggest when the user shows signs of anxiety?", is reflected in the caregiver's actions.

[0398] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0399] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0400] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0401] [Third Embodiment]

[0402] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0403] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0404] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0405] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0406] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0407] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0408] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0409] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0410] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0411] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0412] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0413] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0414] This invention is a care support system that utilizes generative artificial intelligence and is mainly composed of three roles: server, terminal, and user. Specific examples are shown below.

[0415] Server Role

[0416] The server plays a central role in accumulating and analyzing data submitted by users. Using generative artificial intelligence, it analyzes input health data and care history to generate individually optimized care plans. For example, if a user submits records of meals and exercise, the server uses that information to evaluate nutritional balance and create an improvement plan. The server also sends the generated care plan and important notifications to the user's terminal, providing real-time information.

[0417] Terminal role

[0418] The terminal provides an interface for users to record caregiving activities and input information. Users input daily caregiving data into the terminal, and this information is automatically transmitted to the server. For example, the terminal includes fields for meal content, medication status, and activity levels; inputting this data contributes to optimizing the care plan. Furthermore, the terminal displays information transmitted from the server, supporting communication among family members.

[0419] User roles

[0420] Users utilize this system to record information related to caregiving and implement daily care according to suggestions from the server. For example, if a family member of an elderly person reports a loss of appetite, the user can input this information, review the meal plan generated by the server, and improve the diet according to the plan. Communication among users is also facilitated, enabling smooth information sharing.

[0421] As described above, this invention enables efficient and effective care support through the collaboration of a server, terminal, and user. This is expected to reduce the burden on caregivers and improve the quality of life for the elderly.

[0422] The following describes the processing flow.

[0423] Step 1:

[0424] Users use a device to input information about their daily care activities and health status. This includes information such as what they eat, whether they exercise, their medication status, and changes in their physical condition.

[0425] Step 2:

[0426] The terminal converts the information entered by the user into a standardized data format and sends it to the server. This conversion includes data integrity checks and processing to fill in any missing data.

[0427] Step 3:

[0428] The server stores the received data and saves it in a database. The stored data is used for later analysis and to generate feedback for users.

[0429] Step 4:

[0430] The server uses generative artificial intelligence to analyze the accumulated data. This analysis includes pattern recognition and anomaly detection to generate care plans tailored to each individual user.

[0431] Step 5:

[0432] The server sends the generated care plan and important notifications to the user's device. The transmitted information is immediately communicated to the user via the notification function.

[0433] Step 6:

[0434] Users review the care plan sent from their device and perform actual care activities according to its contents. They can approve or modify the plan as needed.

[0435] Step 7:

[0436] The terminal then sends the progress and results of the care activities back to the server. This allows the server to continuously optimize the care plan using the latest information.

[0437] (Example 1)

[0438] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0439] In elderly care, it is essential to provide optimal care plans tailored to each individual's health and living situation, and to ensure smooth information sharing among all parties involved. However, conventional systems require manual data collection and analysis, making it difficult to provide efficient care. This increases the burden on caregivers and hinders the improvement of the quality of life for the elderly.

[0440] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0441] In this invention, the server includes means for analyzing input information using generative artificial intelligence and generating individually optimized support plans, communication means for enabling data sharing among stakeholders, and means for accumulating input care information and evaluating health status based on that information. This makes it possible to efficiently manage the health status of the elderly and quickly provide optimal care plans. Furthermore, smooth information sharing among stakeholders is realized through the communication means, aiming to reduce the burden of caregiving work and improve the quality of life for the elderly.

[0442] "Generative artificial intelligence" is an information processing technology that can analyze input data and generate optimized information and plans based on given criteria.

[0443] A "support plan" is a plan designed to provide optimal care and services tailored to each user's health condition and living situation.

[0444] "Communication means" refers to a means of sending and receiving information bidirectionally, enabling data sharing and communication among stakeholders.

[0445] "Care information" refers to data about the health status and daily living conditions of the person receiving care, and is the basis for creating and adjusting care plans.

[0446] "Means of assessing health status" refers to methods for analyzing and evaluating an individual's health status based on collected care information, and for identifying necessary care and points of attention.

[0447] A "user information processing device" refers to a terminal that provides an information input / output interface and displays data and plans transmitted from a server.

[0448] This invention is a support system that utilizes generative artificial intelligence, and its main components include three roles: server, terminal, and user.

[0449] The server plays a central role in managing and performing advanced analysis of care information submitted by users. Specifically, the server uses generative AI models (such as the widely used natural language processing model GPT) to analyze the input information on health status and lifestyle. Based on the analysis, it generates individually optimized support plans. These plans include suggestions for diet and exercise to support the user's health improvement. The server also enables real-time information sharing by sending the generated plans and important announcements to the user's device.

[0450] The terminal provides an interface for users to input daily care information. Users input information such as diet, activity levels, and medication status into the terminal and send this data to the server. The terminal displays the support plan sent from the server on its screen, allowing users to implement appropriate care based on this data. The terminal also serves as a tool to support communication between family members and caregivers.

[0451] Users can utilize this system to provide care tailored to their individual needs. For example, if a family member of an elderly person reports loss of appetite to the terminal, the server will generate an appropriate meal plan based on analysis and notify the user through the terminal. This allows for improvements to the diet and supports the maintenance of the elderly person's health. Based on the input information, the server adjusts the support plan and provides continuous support.

[0452] One concrete example is using prompt statements to ask questions to the AI ​​model. For instance, "Assess the nutritional value of the meal for an elderly person. Please indicate the nutritional standards that the meal in this picture should meet and suggest improvements if necessary." By using such prompt statements, the server can leverage the insights provided by the generating AI model to deliver a fast and accurate care plan.

[0453] This system is expected to reduce the burden on caregivers while simultaneously improving the quality of life for the elderly.

[0454] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0455] Step 1:

[0456] The terminal receives care information entered by the user. Specifically, the user records data such as meal details, activity levels, and medication status through the terminal's interface. This input data is stored on the terminal in an organized format along with the date, and then sent to the server. The output is the organized care information data, which is then sent to the server.

[0457] Step 2:

[0458] The server receives care information sent from the terminal. The received data is stored in the server's internal database. Next, this data is preprocessed to be passed to the generating AI model. Specifically, it is converted to the required data format, and missing values ​​are imputed and invalid data is removed. As output, data formatted for analysis is sent to the generating AI model.

[0459] Step 3:

[0460] The server inputs the formatted data into a generative AI model and performs the analysis. Prompts are used to ask the AI ​​model specific questions. For example, it might instruct the model to "evaluate nutritional balance and suggest improvements based on recent meal content." Based on the input data and prompts, the generative AI model outputs analysis results optimized for each individual user. The output is received by the server as improvement suggestions and recommended action plans.

[0461] Step 4:

[0462] The server receives output from the generated AI model and creates a support plan for each individual user. The plan includes specific suggestions for diet and exercise. The support plan is formatted on the server and prepared for transmission to the terminal as a notification. The output is the completed support plan data.

[0463] Step 5:

[0464] The server delivers the support plan to the terminal. The user's terminal receives the notification from the server and displays its contents on the screen. The user adjusts their daily activities based on this information and improves the quality of care. The output is displayed to the user as the support plan and related information presented.

[0465] Step 6:

[0466] The user inputs the results of the care provided and any newly noticed information into the terminal and provides feedback to the server. The server uses this feedback information to re-evaluate the support plan and adjust it by performing additional analysis using a generative AI model if necessary. The output is then sent back to the terminal as the adjusted support plan.

[0467] (Application Example 1)

[0468] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0469] In modern society, the number of elderly people requiring care is increasing, and the burden of care on families is becoming a major problem. Caregivers are required to efficiently manage the health status of those requiring care and develop optimal care plans, but the tools and systems for this are still not sufficiently developed. In particular, sharing information among family members and keeping daily health records tends to be cumbersome, making smooth communication and management difficult.

[0470] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0471] This invention includes a server that uses generative artificial intelligence to analyze input data and generate individually optimized plans, a means to provide an intuitive interface for users to easily input their daily health status and activity records, and a means to check and receive the generated plans in real time. This enables the efficient and effective formulation of care plans and facilitates information sharing and communication among family members.

[0472] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to automatically analyze input data and generate optimal plans and information based on that analysis.

[0473] "Data analysis" is the process of thoroughly examining input information, finding meaning in it, and transforming it into useful information and knowledge.

[0474] An "individually optimized plan" refers to a care plan that has been tailored to the optimal content according to the individual circumstances and needs of each user.

[0475] "Providing an interface" means setting up a user interface or means for users to input data into the system.

[0476] "Real-time viewing" means being able to directly see the generated information and plans without delay.

[0477] "Communication methods that enable information sharing" refer to technologies and methods that allow family members and others to send and share data and messages for common use.

[0478] "Assessing health status" means judging and diagnosing an individual's physical condition and health level based on the health information entered.

[0479] The system that realizes this invention consists of three elements: a server, a terminal, and a user. The server utilizes generative artificial intelligence to receive input health data and activity records and generate a care plan optimized for each individual user. This involves data analysis and plan generation using generative AI models such as OpenAI's GPT. Specifically, it evaluates nutritional balance and exercise levels based on the dietary content and activity data submitted by the user and provides improvement plans as needed.

[0480] The device, through an interface built with React Native, allows users to easily record their daily health status and caregiving activities. It also displays care plans and notifications sent from the server in real time, facilitating information sharing among family members.

[0481] Users can use this system to input daily health data and check care plans provided by the server to optimize their daily care. For example, if an elderly person has recently complained of loss of appetite, the user inputs this information into their device, and the server generates a new meal plan based on that data and notifies the device. A specific plan such as, "Let's try a meal plan that includes vegetable soup," is provided.

[0482] As an example of a prompt for a generative AI model, text such as "Please suggest an optimal meal plan based on Mr. / Ms. Tanaka's recent health data" can be used. In this way, users can provide more effective and personalized care with the help of AI.

[0483] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0484] Step 1:

[0485] Users input health data and activity records from their devices. This data includes information such as diet, exercise levels, and medication status. The device automatically prepares to send this data to the server. The input data is formatted in JSON format, encrypted, and sent to the server.

[0486] Step 2:

[0487] The server analyzes the received data and activates the generating artificial intelligence. Based on the input health data, it calls up a generating AI model and generates a prompt message. The prompt message is created in the format of "Please suggest the optimal health plan based on the user's recent health data." The AI ​​then generates a care plan based on this prompt.

[0488] Step 3:

[0489] The server evaluates the generated care plan and performs further detailed analysis as needed. Here, the server checks nutritional balance and exercise plans, and adjusts the plan to suit the user. The server then formats the AI-generated output into a personalized message format for the user.

[0490] Step 4:

[0491] The refined care plan and related information are sent to the device. The device receives this information and prepares to display it through the user interface. The user receives notifications about new care plans and health status updates.

[0492] Step 5:

[0493] Users incorporate plans provided by the server via their devices into their daily lives. They can also provide feedback after executing the plan. User behavior data is sent back to the server and used to generate future plans.

[0494] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0495] This invention is a care support system that combines an emotion engine, enabling the server, terminal, and user to work together to improve the quality of care. This allows for care support that incorporates emotional information. Specific examples are shown below.

[0496] Server Role

[0497] The server has a central function of collecting and analyzing data sent from users and devices. While the generative artificial intelligence analyzes health status data and care history, the emotion engine analyzes the user's emotional data. Specifically, emotional data is extracted from the user's text input and voice data and analyzed on the server. This allows for an understanding of how changes in emotions affect care plans and enables dynamic adjustments to those plans.

[0498] Terminal role

[0499] The terminal is used to record the user's caregiving activities and input their emotional state. Through the terminal, users can report not only daily caregiving activities but also their emotions and stress levels at the time, and the terminal prepares to send this information to the server. For example, the terminal uses speech recognition or text recognition to identify emotions and extract the corresponding data. This allows emotion-based information to be transmitted to the server in real time.

[0500] User roles

[0501] By using this system, users can obtain care plans that take emotions into account and implement daily care activities. For example, if the emotion engine analyzes that the user's stress level is high, the server can incorporate relaxation-recommended activities into the plan in addition to the usual plan. This approach makes it easier for both the user and their family to recognize emotional changes and take appropriate actions.

[0502] As described above, the introduction of the emotion engine in this invention makes it possible for the care support system to comprehensively support not only physical health but also psychological health. This is expected to not only improve the user's QOL (quality of life) but also to foster closer communication with family members and caregivers.

[0503] The following describes the processing flow.

[0504] Step 1:

[0505] Users input daily care activities, health status, and emotional state into the device. This includes information such as meal details, activities, and changes in emotions, using text or voice input.

[0506] Step 2:

[0507] The terminal receives information entered by the user and extracts emotional data through text and voice analysis. It then formats the data and prepares it for transmission to the server.

[0508] Step 3:

[0509] The device transmits processed health and emotional data to the server. This data transmission is performed rapidly in real time.

[0510] Step 4:

[0511] The server stores the received health and emotional data in a database. After storage, it begins data analysis using generative artificial intelligence and an emotion engine.

[0512] Step 5:

[0513] The server generates care plans using generative artificial intelligence and analyzes emotional data with an emotion engine. For example, it adds activities including relaxation for users with high stress levels.

[0514] Step 6:

[0515] The server sends the generated care plan to the terminal and notifies the user. This plan includes adjustments based on the user's emotions.

[0516] Step 7:

[0517] The user reviews the care plan displayed on the device and performs the designated activities. As feedback, they re-enter their activities and emotional state for the day into the device.

[0518] Step 8:

[0519] The terminal sends the feedback information back to the server, preparing for the next data analysis. This allows the server to continuously adjust the care plan.

[0520] (Example 2)

[0521] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0522] In recent years, improving the quality of care requires comprehensive care that considers not only physical health but also psychological health. However, the current system makes it difficult to accurately grasp the emotional state of users and adjust care plans accordingly. Furthermore, insufficient information sharing among family members makes it difficult to fully understand the user's condition.

[0523] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0524] This invention includes a server that uses generative artificial intelligence to analyze input information and generate individually optimized plans, means for performing analysis based on emotional data and dynamically adjusting the plans, and communication means for enabling information sharing between relationships. This makes it possible to comprehensively understand the user's emotions and health condition and provide appropriately optimized care plans. Furthermore, sharing useful information among family members can further enhance the consistency and effectiveness of care.

[0525] "Generative artificial intelligence" is an artificial intelligence technology that analyzes input information and generates plans and proposals tailored to individual needs.

[0526] An "individually optimized plan" is a plan that aims to provide the most suitable services and activities for a particular user, based on their health and emotional state.

[0527] "Emotional data" refers to information about emotions extracted from user feedback, text, and other sources, and is data that indicates psychological health and stress levels.

[0528] "Dynamic adjustment" refers to modifying existing plans and settings in real time in response to newly obtained data and changes in circumstances.

[0529] "Communication methods" is a general term for the technologies and protocols used to send and receive data and information between servers, terminals, and users.

[0530] "Record data" refers to various types of data related to the user, such as care activities, health status, and daily events, and is used as the basis for evaluating their health and emotional state.

[0531] This invention is a system aimed at analyzing the health and emotional state of users and providing individually optimized care plans. This system is designed so that the server, terminals, and users each play specific roles and work together.

[0532] Server Role

[0533] The server acts as the central hub of the system, accumulating and analyzing data. Equipped with generative artificial intelligence, the server receives and stores voice and text data transmitted from terminals. Based on user-related health and emotional data, the generative AI generates personalized care plans tailored to individual needs. The emotion engine meticulously analyzes emotional data extracted from the user's voice and text, dynamically adjusting the plan accordingly.

[0534] Terminal role

[0535] The terminal refers to devices such as mobile phones and tablets that have the function of receiving user input and sending it to the server. Specifically, it has the function of converting the user's voice data into text using speech recognition technology and extracting emotional data. HTTPS is used as the communication protocol to evaluate the emotional state in real time and securely transmit the information to the server.

[0536] User roles

[0537] The user is the one who inputs their emotions and health status regarding caregiving and daily life into the terminal. The system allows the user to receive a generated care plan from the terminal and perform appropriate activities based on its instructions. For example, if the system analyzes that the user is experiencing high stress levels, the server will recommend relaxation activities, which the user can then view on the terminal.

[0538] Specific example

[0539] The user voice-inputs "I'm feeling a little stressed today" into the device. The device performs voice recognition and sends the data to the server. The server uses an emotion engine to analyze the stress level and adjusts the care plan to include relaxation activities. A prompt to the generated AI model might be, "Optimize the care plan based on the latest health data and emotion analysis."

[0540] Thus, this system is expected to improve the quality of care services by providing comprehensive care plans that include user emotional data.

[0541] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0542] Step 1:

[0543] The device accepts voice and text input from the user. The user inputs their emotions and health status through the device's app. Specifically, speech recognition technology converts speech into text and captures it as input. This input data undergoes preliminary processing to identify emotions.

[0544] Step 2:

[0545] The device sends pre-processed emotional data and health information to the server. This involves error checking to ensure the data is transmitted accurately and transferring the data to the server using the secure communication protocol HTTPS. The output includes the processed emotional data and health information.

[0546] Step 3:

[0547] The server receives data from the terminal and stores it in a database. Generative artificial intelligence analyzes this data and uses an emotion engine to evaluate the user's emotional state and health status. In this step, a machine learning algorithm analyzes the user's psychological tendencies based on the emotional data. The analysis results are generated as output.

[0548] Step 4:

[0549] The server generates and dynamically adjusts care plans based on the analysis results. Specifically, a plan is formed that includes relaxation activities and recommendations for specific behaviors based on emotional changes. A generative AI model is involved in this process, outputting an optimal plan tailored to the user's characteristics.

[0550] Step 5:

[0551] The server sends the generated care plan to the terminal. The terminal displays the received plan to the user and, in some cases, can provide voice notifications. This care plan output includes specific guidelines to support daily care activities.

[0552] Step 6:

[0553] Users review the care plan provided through their device and take action accordingly. User feedback is sent back to the server via the device and used for further analysis. This feedback process continuously improves the accuracy of the care plan.

[0554] (Application Example 2)

[0555] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0556] Conventional care support systems failed to adequately consider users' emotions and had an insufficient understanding of their psychological health, making it difficult to fully optimize care plans. Furthermore, they were unable to dynamically adjust care plans based on real-time emotion analysis, making it difficult to improve users' quality of life (QOL).

[0557] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0558] In this invention, the server includes means for analyzing input data using generative artificial intelligence and generating individually optimized care plans, means for acquiring emotional data using emotion analysis technology and dynamically adjusting the care plan based on the acquired emotional information, and means for analyzing emotional data in real time via various measuring devices and storing it for generating suggestions. This makes it possible to reflect the user's emotional state in the care plan and provide corresponding care support.

[0559] "Generative artificial intelligence" refers to artificial intelligence technology that analyzes input data and generates optimal results tailored to a specific purpose.

[0560] An "individually optimized care plan" is a plan that is customized based on each user's health condition and emotional information, in order to provide the most appropriate care for each individual.

[0561] "Communication methods" refer to digital technologies and systems that enable the rapid and accurate sharing of information between people.

[0562] "Means of evaluating health status" refers to the processes and technologies used to analyze and evaluate a user's physical and mental health based on accumulated data.

[0563] "Emotional analysis technology" refers to the technology used to extract and analyze emotional information from data such as voice, text, and facial expressions.

[0564] A "dynamic adjustment mechanism" refers to a function that automatically adapts and optimizes plans and procedures in response to changes in acquired information and conditions.

[0565] "Various measuring devices" refers to a collection of sensors and devices used to collect information such as emotional data.

[0566] "Real-time analysis" refers to the technology of processing and analyzing data almost simultaneously with its generation.

[0567] "Storage means" refers to a digital storage system used to hold analysis results and proposals.

[0568] This invention is a care support system that combines an emotional engine and was built to improve the quality of care. Its details are described below.

[0569] The server plays a central role in this system, analyzing the input user data to generate individually optimized care plans. It utilizes generative artificial intelligence to comprehensively analyze the user's health status and care history, and further uses emotional data extracted from voice and text to dynamically adjust the care plan. This process employs an AI model built using Python and TensorFlow. Furthermore, for emotional analysis, it utilizes Google Cloud's Speech-to-Text API for voice data, and OpenCV is used for image processing.

[0570] The terminal functions as a device used by users and care staff in their daily work. Terminals such as smartphones and smart glasses acquire voice and facial expressions in real time and transmit this data to a server. Therefore, various measuring devices are used on the terminal, enabling real-time analysis of the acquired data. The analysis results are stored via Firebase in the cloud, and suggestions are generated as needed.

[0571] Users carry out care activities according to the care plan provided by the system. If the emotional engine analyzes that the stress level is high, for example, the system will suggest relaxation methods in addition to the normal plan. Through this process, users and their families can more easily recognize emotional changes and take appropriate actions.

[0572] For example, if a user indicates feelings of "anxiety" in their recorded situation, the server generates suggestions for additional relaxation activities and notifies the user's terminal accordingly. This allows caregivers to respond quickly, thereby improving the user's quality of life (QOL).

[0573] Example of a prompt:

[0574] "What relaxation methods would you suggest when a user shows signs of anxiety?"

[0575] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0576] Step 1:

[0577] The device collects the user's facial expressions and voice data. This is done using the camera and microphone of a smartphone or smart glasses. The input is the user's facial image and voice, and the output is this digital data. Image processing using OpenCV and speech-to-text conversion using Google Cloud Speech-to-Text are performed within the device.

[0578] Step 2:

[0579] The terminal collects data and sends it to the server. The input consists of facial expression image data and transcribed audio data, and the output is the transmission of data to the server. In this process, data is transferred to the server in real time using communication methods.

[0580] Step 3:

[0581] The server analyzes the received data and extracts emotional information. The input is the data sent in step 2, and the output is the emotional analysis result. On the server, a generative AI model using TensorFlow runs to determine the user's emotions from facial expression data and text data.

[0582] Step 4:

[0583] The server dynamically adjusts the care plan based on emotional information. The input is the result of the emotional analysis, and the output is the updated care plan proposal. The emotional engine takes this analysis result into consideration and adds relaxation activities as needed.

[0584] Step 5:

[0585] The server notifies the terminal of the updated care plan. The input is the updated care plan draft, and the output is the provision of information to the terminal. The proposal is sent to caregivers and users from Firebase in the cloud.

[0586] Step 6:

[0587] The user receives a notification and then performs specific caregiving activities. The input is notification data from the server, and the output is the actual caregiving action. An example prompt, "What relaxation method would you suggest when the user shows signs of anxiety?", is reflected in the caregiver's actions.

[0588] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0589] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0590] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0591] [Fourth Embodiment]

[0592] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0593] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0594] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0595] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0596] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0597] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0598] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0599] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0600] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0601] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0602] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0603] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0604] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0605] This invention is a care support system that utilizes generative artificial intelligence and is mainly composed of three roles: server, terminal, and user. Specific examples are shown below.

[0606] Server Role

[0607] The server plays a central role in accumulating and analyzing data submitted by users. Using generative artificial intelligence, it analyzes input health data and care history to generate individually optimized care plans. For example, if a user submits records of meals and exercise, the server uses that information to evaluate nutritional balance and create an improvement plan. The server also sends the generated care plan and important notifications to the user's terminal, providing real-time information.

[0608] Terminal role

[0609] The terminal provides an interface for users to record caregiving activities and input information. Users input daily caregiving data into the terminal, and this information is automatically transmitted to the server. For example, the terminal includes fields for meal content, medication status, and activity levels; inputting this data contributes to optimizing the care plan. Furthermore, the terminal displays information transmitted from the server, supporting communication among family members.

[0610] User roles

[0611] Users utilize this system to record information related to caregiving and implement daily care according to suggestions from the server. For example, if a family member of an elderly person reports a loss of appetite, the user can input this information, review the meal plan generated by the server, and improve the diet according to the plan. Communication among users is also facilitated, enabling smooth information sharing.

[0612] As described above, this invention enables efficient and effective care support through the collaboration of a server, terminal, and user. This is expected to reduce the burden on caregivers and improve the quality of life for the elderly.

[0613] The following describes the processing flow.

[0614] Step 1:

[0615] Users use a device to input information about their daily care activities and health status. This includes information such as what they eat, whether they exercise, their medication status, and changes in their physical condition.

[0616] Step 2:

[0617] The terminal converts the information entered by the user into a standardized data format and sends it to the server. This conversion includes data integrity checks and processing to fill in any missing data.

[0618] Step 3:

[0619] The server stores the received data and saves it in a database. The stored data is used for later analysis and to generate feedback for users.

[0620] Step 4:

[0621] The server uses generative artificial intelligence to analyze the accumulated data. This analysis includes pattern recognition and anomaly detection to generate care plans tailored to each individual user.

[0622] Step 5:

[0623] The server sends the generated care plan and important notifications to the user's device. The transmitted information is immediately communicated to the user via the notification function.

[0624] Step 6:

[0625] Users review the care plan sent from their device and perform actual care activities according to its contents. They can approve or modify the plan as needed.

[0626] Step 7:

[0627] The terminal then sends the progress and results of the care activities back to the server. This allows the server to continuously optimize the care plan using the latest information.

[0628] (Example 1)

[0629] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0630] In elderly care, it is essential to provide optimal care plans tailored to each individual's health and living situation, and to ensure smooth information sharing among all parties involved. However, conventional systems require manual data collection and analysis, making it difficult to provide efficient care. This increases the burden on caregivers and hinders the improvement of the quality of life for the elderly.

[0631] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0632] In this invention, the server includes means for analyzing input information using generative artificial intelligence and generating individually optimized support plans, communication means for enabling data sharing among stakeholders, and means for accumulating input care information and evaluating health status based on that information. This makes it possible to efficiently manage the health status of the elderly and quickly provide optimal care plans. Furthermore, smooth information sharing among stakeholders is realized through the communication means, aiming to reduce the burden of caregiving work and improve the quality of life for the elderly.

[0633] "Generative artificial intelligence" is an information processing technology that can analyze input data and generate optimized information and plans based on given criteria.

[0634] A "support plan" is a plan designed to provide optimal care and services tailored to each user's health condition and living situation.

[0635] "Communication means" refers to a means of sending and receiving information bidirectionally, enabling data sharing and communication among stakeholders.

[0636] "Care information" refers to data about the health status and daily living conditions of the person receiving care, and is the basis for creating and adjusting care plans.

[0637] "Means of assessing health status" refers to methods for analyzing and evaluating an individual's health status based on collected care information, and for identifying necessary care and points of attention.

[0638] A "user information processing device" refers to a terminal that provides an information input / output interface and displays data and plans transmitted from a server.

[0639] This invention is a support system that utilizes generative artificial intelligence, and its main components include three roles: server, terminal, and user.

[0640] The server plays a central role in managing and performing advanced analysis of care information submitted by users. Specifically, the server uses generative AI models (such as the widely used natural language processing model GPT) to analyze the input information on health status and lifestyle. Based on the analysis, it generates individually optimized support plans. These plans include suggestions for diet and exercise to support the user's health improvement. The server also enables real-time information sharing by sending the generated plans and important announcements to the user's device.

[0641] The terminal provides an interface for users to input daily care information. Users input information such as diet, activity levels, and medication status into the terminal and send this data to the server. The terminal displays the support plan sent from the server on its screen, allowing users to implement appropriate care based on this data. The terminal also serves as a tool to support communication between family members and caregivers.

[0642] Users can utilize this system to provide care tailored to their individual needs. For example, if a family member of an elderly person reports loss of appetite to the terminal, the server will generate an appropriate meal plan based on analysis and notify the user through the terminal. This allows for improvements to the diet and supports the maintenance of the elderly person's health. Based on the input information, the server adjusts the support plan and provides continuous support.

[0643] One concrete example is using prompt statements to ask questions to the AI ​​model. For instance, "Assess the nutritional value of the meal for an elderly person. Please indicate the nutritional standards that the meal in this picture should meet and suggest improvements if necessary." By using such prompt statements, the server can leverage the insights provided by the generating AI model to deliver a fast and accurate care plan.

[0644] This system is expected to reduce the burden on caregivers while simultaneously improving the quality of life for the elderly.

[0645] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0646] Step 1:

[0647] The terminal receives care information entered by the user. Specifically, the user records data such as meal details, activity levels, and medication status through the terminal's interface. This input data is stored on the terminal in an organized format along with the date, and then sent to the server. The output is the organized care information data, which is then sent to the server.

[0648] Step 2:

[0649] The server receives care information sent from the terminal. The received data is stored in the server's internal database. Next, this data is preprocessed to be passed to the generating AI model. Specifically, it is converted to the required data format, and missing values ​​are imputed and invalid data is removed. As output, data formatted for analysis is sent to the generating AI model.

[0650] Step 3:

[0651] The server inputs the formatted data into a generative AI model and performs the analysis. Prompts are used to ask the AI ​​model specific questions. For example, it might instruct the model to "evaluate nutritional balance and suggest improvements based on recent meal content." Based on the input data and prompts, the generative AI model outputs analysis results optimized for each individual user. The output is received by the server as improvement suggestions and recommended action plans.

[0652] Step 4:

[0653] The server receives output from the generated AI model and creates a support plan for each individual user. The plan includes specific suggestions for diet and exercise. The support plan is formatted on the server and prepared for transmission to the terminal as a notification. The output is the completed support plan data.

[0654] Step 5:

[0655] The server delivers the support plan to the terminal. The user's terminal receives the notification from the server and displays its contents on the screen. The user adjusts their daily activities based on this information and improves the quality of care. The output is displayed to the user as the support plan and related information presented.

[0656] Step 6:

[0657] The user inputs the results of the care provided and any newly noticed information into the terminal and provides feedback to the server. The server uses this feedback information to re-evaluate the support plan and adjust it by performing additional analysis using a generative AI model if necessary. The output is then sent back to the terminal as the adjusted support plan.

[0658] (Application Example 1)

[0659] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0660] In modern society, the number of elderly people requiring care is increasing, and the burden of care on families is becoming a major problem. Caregivers are required to efficiently manage the health status of those requiring care and develop optimal care plans, but the tools and systems for this are still not sufficiently developed. In particular, sharing information among family members and keeping daily health records tends to be cumbersome, making smooth communication and management difficult.

[0661] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0662] This invention includes a server that uses generative artificial intelligence to analyze input data and generate individually optimized plans, a means to provide an intuitive interface for users to easily input their daily health status and activity records, and a means to check and receive the generated plans in real time. This enables the efficient and effective formulation of care plans and facilitates information sharing and communication among family members.

[0663] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to automatically analyze input data and generate optimal plans and information based on that analysis.

[0664] "Data analysis" is the process of thoroughly examining input information, finding meaning in it, and transforming it into useful information and knowledge.

[0665] An "individually optimized plan" refers to a care plan that has been tailored to the optimal content according to the individual circumstances and needs of each user.

[0666] "Providing an interface" means setting up a user interface or means for users to input data into the system.

[0667] "Real-time viewing" means being able to directly see the generated information and plans without delay.

[0668] "Communication methods that enable information sharing" refer to technologies and methods that allow family members and others to send and share data and messages for common use.

[0669] "Assessing health status" means judging and diagnosing an individual's physical condition and health level based on the health information entered.

[0670] The system that realizes this invention consists of three elements: a server, a terminal, and a user. The server utilizes generative artificial intelligence to receive input health data and activity records and generate a care plan optimized for each individual user. This involves data analysis and plan generation using generative AI models such as OpenAI's GPT. Specifically, it evaluates nutritional balance and exercise levels based on the dietary content and activity data submitted by the user and provides improvement plans as needed.

[0671] The device, through an interface built with React Native, allows users to easily record their daily health status and caregiving activities. It also displays care plans and notifications sent from the server in real time, facilitating information sharing among family members.

[0672] Users can use this system to input daily health data and check care plans provided by the server to optimize their daily care. For example, if an elderly person has recently complained of loss of appetite, the user inputs this information into their device, and the server generates a new meal plan based on that data and notifies the device. A specific plan such as, "Let's try a meal plan that includes vegetable soup," is provided.

[0673] As an example of a prompt for a generative AI model, text such as "Please suggest an optimal meal plan based on Mr. / Ms. Tanaka's recent health data" can be used. In this way, users can provide more effective and personalized care with the help of AI.

[0674] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0675] Step 1:

[0676] Users input health data and activity records from their devices. This data includes information such as diet, exercise levels, and medication status. The device automatically prepares to send this data to the server. The input data is formatted in JSON format, encrypted, and sent to the server.

[0677] Step 2:

[0678] The server analyzes the received data and activates the generating artificial intelligence. Based on the input health data, it calls up a generating AI model and generates a prompt message. The prompt message is created in the format of "Please suggest the optimal health plan based on the user's recent health data." The AI ​​then generates a care plan based on this prompt.

[0679] Step 3:

[0680] The server evaluates the generated care plan and performs further detailed analysis as needed. Here, the server checks nutritional balance and exercise plans, and adjusts the plan to suit the user. The server then formats the AI-generated output into a personalized message format for the user.

[0681] Step 4:

[0682] The refined care plan and related information are sent to the device. The device receives this information and prepares to display it through the user interface. The user receives notifications about new care plans and health status updates.

[0683] Step 5:

[0684] Users incorporate plans provided by the server via their devices into their daily lives. They can also provide feedback after executing the plan. User behavior data is sent back to the server and used to generate future plans.

[0685] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0686] This invention is a care support system that combines an emotion engine, enabling the server, terminal, and user to work together to improve the quality of care. This allows for care support that incorporates emotional information. Specific examples are shown below.

[0687] Server Role

[0688] The server has a central function of collecting and analyzing data sent from users and devices. While the generative artificial intelligence analyzes health status data and care history, the emotion engine analyzes the user's emotional data. Specifically, emotional data is extracted from the user's text input and voice data and analyzed on the server. This allows for an understanding of how changes in emotions affect care plans and enables dynamic adjustments to those plans.

[0689] Terminal role

[0690] The terminal is used to record the user's caregiving activities and input their emotional state. Through the terminal, users can report not only daily caregiving activities but also their emotions and stress levels at the time, and the terminal prepares to send this information to the server. For example, the terminal uses speech recognition or text recognition to identify emotions and extract the corresponding data. This allows emotion-based information to be transmitted to the server in real time.

[0691] User roles

[0692] By using this system, users can obtain care plans that take emotions into account and implement daily care activities. For example, if the emotion engine analyzes that the user's stress level is high, the server can incorporate relaxation-recommended activities into the plan in addition to the usual plan. This approach makes it easier for both the user and their family to recognize emotional changes and take appropriate actions.

[0693] As described above, the introduction of the emotion engine in this invention makes it possible for the care support system to comprehensively support not only physical health but also psychological health. This is expected to not only improve the user's QOL (quality of life) but also to foster closer communication with family members and caregivers.

[0694] The following describes the processing flow.

[0695] Step 1:

[0696] Users input daily care activities, health status, and emotional state into the device. This includes information such as meal details, activities, and changes in emotions, using text or voice input.

[0697] Step 2:

[0698] The terminal receives information entered by the user and extracts emotional data through text and voice analysis. It then formats the data and prepares it for transmission to the server.

[0699] Step 3:

[0700] The device transmits processed health and emotional data to the server. This data transmission is performed rapidly in real time.

[0701] Step 4:

[0702] The server stores the received health and emotional data in a database. After storage, it begins data analysis using generative artificial intelligence and an emotion engine.

[0703] Step 5:

[0704] The server generates care plans using generative artificial intelligence and analyzes emotional data with an emotion engine. For example, it adds activities including relaxation for users with high stress levels.

[0705] Step 6:

[0706] The server sends the generated care plan to the terminal and notifies the user. This plan includes adjustments based on the user's emotions.

[0707] Step 7:

[0708] The user reviews the care plan displayed on the device and performs the designated activities. As feedback, they re-enter their activities and emotional state for the day into the device.

[0709] Step 8:

[0710] The terminal sends the feedback information back to the server, preparing for the next data analysis. This allows the server to continuously adjust the care plan.

[0711] (Example 2)

[0712] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0713] In recent years, improving the quality of care requires comprehensive care that considers not only physical health but also psychological health. However, the current system makes it difficult to accurately grasp the emotional state of users and adjust care plans accordingly. Furthermore, insufficient information sharing among family members makes it difficult to fully understand the user's condition.

[0714] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0715] This invention includes a server that uses generative artificial intelligence to analyze input information and generate individually optimized plans, means for performing analysis based on emotional data and dynamically adjusting the plans, and communication means for enabling information sharing between relationships. This makes it possible to comprehensively understand the user's emotions and health condition and provide appropriately optimized care plans. Furthermore, sharing useful information among family members can further enhance the consistency and effectiveness of care.

[0716] "Generative artificial intelligence" is an artificial intelligence technology that analyzes input information and generates plans and proposals tailored to individual needs.

[0717] An "individually optimized plan" is a plan that aims to provide the most suitable services and activities for a particular user, based on their health and emotional state.

[0718] "Emotional data" refers to information about emotions extracted from user feedback, text, and other sources, and is data that indicates psychological health and stress levels.

[0719] "Dynamic adjustment" refers to modifying existing plans and settings in real time in response to newly obtained data and changes in circumstances.

[0720] "Communication methods" is a general term for the technologies and protocols used to send and receive data and information between servers, terminals, and users.

[0721] "Record data" refers to various types of data related to the user, such as care activities, health status, and daily events, and is used as the basis for evaluating their health and emotional state.

[0722] This invention is a system aimed at analyzing the health and emotional state of users and providing individually optimized care plans. This system is designed so that the server, terminals, and users each play specific roles and work together.

[0723] Server Role

[0724] The server acts as the central hub of the system, accumulating and analyzing data. Equipped with generative artificial intelligence, the server receives and stores voice and text data transmitted from terminals. Based on user-related health and emotional data, the generative AI generates personalized care plans tailored to individual needs. The emotion engine meticulously analyzes emotional data extracted from the user's voice and text, dynamically adjusting the plan accordingly.

[0725] Terminal role

[0726] The terminal refers to devices such as mobile phones and tablets that have the function of receiving user input and sending it to the server. Specifically, it has the function of converting the user's voice data into text using speech recognition technology and extracting emotional data. HTTPS is used as the communication protocol to evaluate the emotional state in real time and securely transmit the information to the server.

[0727] User roles

[0728] The user is the one who inputs their emotions and health status regarding caregiving and daily life into the terminal. The system allows the user to receive a generated care plan from the terminal and perform appropriate activities based on its instructions. For example, if the system analyzes that the user is experiencing high stress levels, the server will recommend relaxation activities, which the user can then view on the terminal.

[0729] Specific example

[0730] The user voice-inputs "I'm feeling a little stressed today" into the device. The device performs voice recognition and sends the data to the server. The server uses an emotion engine to analyze the stress level and adjusts the care plan to include relaxation activities. A prompt to the generated AI model might be, "Optimize the care plan based on the latest health data and emotion analysis."

[0731] Thus, this system is expected to improve the quality of care services by providing comprehensive care plans that include user emotional data.

[0732] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0733] Step 1:

[0734] The device accepts voice and text input from the user. The user inputs their emotions and health status through the device's app. Specifically, speech recognition technology converts speech into text and captures it as input. This input data undergoes preliminary processing to identify emotions.

[0735] Step 2:

[0736] The device sends pre-processed emotional data and health information to the server. This involves error checking to ensure the data is transmitted accurately and transferring the data to the server using the secure communication protocol HTTPS. The output includes the processed emotional data and health information.

[0737] Step 3:

[0738] The server receives data from the terminal and stores it in a database. Generative artificial intelligence analyzes this data and uses an emotion engine to evaluate the user's emotional state and health status. In this step, a machine learning algorithm analyzes the user's psychological tendencies based on the emotional data. The analysis results are generated as output.

[0739] Step 4:

[0740] The server generates and dynamically adjusts care plans based on the analysis results. Specifically, a plan is formed that includes relaxation activities and recommendations for specific behaviors based on emotional changes. A generative AI model is involved in this process, outputting an optimal plan tailored to the user's characteristics.

[0741] Step 5:

[0742] The server sends the generated care plan to the terminal. The terminal displays the received plan to the user and, in some cases, can provide voice notifications. This care plan output includes specific guidelines to support daily care activities.

[0743] Step 6:

[0744] Users review the care plan provided through their device and take action accordingly. User feedback is sent back to the server via the device and used for further analysis. This feedback process continuously improves the accuracy of the care plan.

[0745] (Application Example 2)

[0746] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0747] Conventional care support systems failed to adequately consider users' emotions and had an insufficient understanding of their psychological health, making it difficult to fully optimize care plans. Furthermore, they were unable to dynamically adjust care plans based on real-time emotion analysis, making it difficult to improve users' quality of life (QOL).

[0748] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0749] In this invention, the server includes means for analyzing input data using generative artificial intelligence and generating individually optimized care plans, means for acquiring emotional data using emotion analysis technology and dynamically adjusting the care plan based on the acquired emotional information, and means for analyzing emotional data in real time via various measuring devices and storing it for generating suggestions. This makes it possible to reflect the user's emotional state in the care plan and provide corresponding care support.

[0750] "Generative artificial intelligence" refers to artificial intelligence technology that analyzes input data and generates optimal results tailored to a specific purpose.

[0751] An "individually optimized care plan" is a plan that is customized based on each user's health condition and emotional information, in order to provide the most appropriate care for each individual.

[0752] "Communication methods" refer to digital technologies and systems that enable the rapid and accurate sharing of information between people.

[0753] "Means of evaluating health status" refers to the processes and technologies used to analyze and evaluate a user's physical and mental health based on accumulated data.

[0754] "Emotional analysis technology" refers to the technology used to extract and analyze emotional information from data such as voice, text, and facial expressions.

[0755] A "dynamic adjustment mechanism" refers to a function that automatically adapts and optimizes plans and procedures in response to changes in acquired information and conditions.

[0756] "Various measuring devices" refers to a collection of sensors and devices used to collect information such as emotional data.

[0757] "Real-time analysis" refers to the technology of processing and analyzing data almost simultaneously with its generation.

[0758] "Storage means" refers to a digital storage system used to hold analysis results and proposals.

[0759] This invention is a care support system that combines an emotional engine and was built to improve the quality of care. Its details are described below.

[0760] The server plays a central role in this system, analyzing the input user data to generate individually optimized care plans. It utilizes generative artificial intelligence to comprehensively analyze the user's health status and care history, and further uses emotional data extracted from voice and text to dynamically adjust the care plan. This process employs an AI model built using Python and TensorFlow. Furthermore, for emotional analysis, it utilizes Google Cloud's Speech-to-Text API for voice data, and OpenCV is used for image processing.

[0761] The terminal functions as a device used by users and care staff in their daily work. Terminals such as smartphones and smart glasses acquire voice and facial expressions in real time and transmit this data to a server. Therefore, various measuring devices are used on the terminal, enabling real-time analysis of the acquired data. The analysis results are stored via Firebase in the cloud, and suggestions are generated as needed.

[0762] Users carry out care activities according to the care plan provided by the system. If the emotional engine analyzes that the stress level is high, for example, the system will suggest relaxation methods in addition to the normal plan. Through this process, users and their families can more easily recognize emotional changes and take appropriate actions.

[0763] For example, if a user indicates feelings of "anxiety" in their recorded situation, the server generates suggestions for additional relaxation activities and notifies the user's terminal accordingly. This allows caregivers to respond quickly, thereby improving the user's quality of life (QOL).

[0764] Example of a prompt:

[0765] "What relaxation methods would you suggest when a user shows signs of anxiety?"

[0766] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0767] Step 1:

[0768] The device collects the user's facial expressions and voice data. This is done using the camera and microphone of a smartphone or smart glasses. The input is the user's facial image and voice, and the output is this digital data. Image processing using OpenCV and speech-to-text conversion using Google Cloud Speech-to-Text are performed within the device.

[0769] Step 2:

[0770] The terminal collects data and sends it to the server. The input consists of facial expression image data and transcribed audio data, and the output is the transmission of data to the server. In this process, data is transferred to the server in real time using communication methods.

[0771] Step 3:

[0772] The server analyzes the received data and extracts emotional information. The input is the data sent in step 2, and the output is the emotional analysis result. On the server, a generative AI model using TensorFlow runs to determine the user's emotions from facial expression data and text data.

[0773] Step 4:

[0774] The server dynamically adjusts the care plan based on emotional information. The input is the result of the emotional analysis, and the output is the updated care plan proposal. The emotional engine takes this analysis result into consideration and adds relaxation activities as needed.

[0775] Step 5:

[0776] The server notifies the terminal of the updated care plan. The input is the updated care plan draft, and the output is the provision of information to the terminal. The proposal is sent to caregivers and users from Firebase in the cloud.

[0777] Step 6:

[0778] The user receives a notification and then performs specific caregiving activities. The input is notification data from the server, and the output is the actual caregiving action. An example prompt, "What relaxation method would you suggest when the user shows signs of anxiety?", is reflected in the caregiver's actions.

[0779] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0780] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0781] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0782] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0783] Figure 9 shows an emotion map 400 in 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 the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0784] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0785] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0786] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0787] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it 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 emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0788] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0789] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0790] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0791] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0792] 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.

[0793] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0794] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0795] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0796] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0797] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0798] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0799] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0800] The following is further disclosed regarding the embodiments described above.

[0801] (Claim 1)

[0802] A means of generating an individually optimized care plan by analyzing input data using generative artificial intelligence,

[0803] A means of communication that enables information sharing among family members,

[0804] A means of accumulating input care data and evaluating health status based on that data,

[0805] A system that includes this.

[0806] (Claim 2)

[0807] The system according to claim 1, further comprising means for notifying a user terminal of a care plan generated by artificial intelligence.

[0808] (Claim 3)

[0809] The system according to claim 1, comprising means for receiving data necessary for implementing a care plan from a user and recording that information.

[0810] "Example 1"

[0811] (Claim 1)

[0812] A means of generating an individually optimized support plan by analyzing input information using generative artificial intelligence,

[0813] A communication method that enables data sharing among stakeholders,

[0814] A means of accumulating input care information and evaluating health status based on that information,

[0815] A means for distributing the generated support plan to the user's information processing device,

[0816] A means of receiving user feedback and adjusting the plan,

[0817] A system that includes this.

[0818] (Claim 2)

[0819] The system according to claim 1, further comprising means for notifying the user's information processing device of a support plan generated by a generating artificial intelligence.

[0820] (Claim 3)

[0821] The system according to claim 1, comprising means for receiving information necessary for the implementation of a support plan from a user and recording that information.

[0822] "Application Example 1"

[0823] (Claim 1)

[0824] A means of using generative artificial intelligence to analyze input data and generate individually optimized plans,

[0825] A means of providing an intuitive interface for users to easily input their daily health status and activity records,

[0826] A means of checking and receiving the generated plan in real time,

[0827] A means of communication that enables information sharing among family members,

[0828] A means of accumulating input care data and evaluating health status based on that data,

[0829] A system that includes this.

[0830] (Claim 2)

[0831] The system according to claim 1, further comprising means for notifying a user terminal of a plan generated by artificial intelligence.

[0832] (Claim 3)

[0833] The system according to claim 1, comprising means for receiving data necessary for the implementation of a plan from a user and recording that information.

[0834] "Example 2 of combining an emotion engine"

[0835] (Claim 1)

[0836] A means of using generative artificial intelligence to analyze input information and generate individually optimized plans,

[0837] A means of dynamically adjusting plans based on analysis using emotional data,

[0838] Communication methods that enable information sharing between people,

[0839] A means for accumulating input record data and evaluating health status based on that data,

[0840] A means of collecting information using a terminal and sending it to a server,

[0841] A system that includes this.

[0842] (Claim 2)

[0843] The system according to claim 1, further comprising means for notifying a user terminal of a plan generated by artificial intelligence.

[0844] (Claim 3)

[0845] The system according to claim 1, comprising means for receiving information necessary for the implementation of a plan from a user and recording that information.

[0846] "Application example 2 when combining with an emotional engine"

[0847] (Claim 1)

[0848] A means of generating an individually optimized care plan by analyzing input data using generative artificial intelligence,

[0849] Communication methods that enable information sharing between people,

[0850] A means of accumulating input care data and evaluating health status based on that data,

[0851] A means for acquiring emotional data using emotion analysis technology and dynamically adjusting the care plan based on the acquired emotional information,

[0852] A means for analyzing emotional data in real time via various measuring devices and storing it to generate suggestions,

[0853] A system that includes this.

[0854] (Claim 2)

[0855] The system according to claim 1, further comprising means for notifying a user device of a care plan generated by artificial intelligence.

[0856] (Claim 3)

[0857] The system according to claim 1, comprising means for receiving data from a user necessary for implementing a care plan and recording that information. [Explanation of Symbols]

[0858] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of using generative artificial intelligence to analyze input data and generate individually optimized plans, A means to provide an intuitive interface for users to easily input their daily health status and activity records, A means of checking and receiving the generated plan in real time, A means of communication that enables information sharing among family members, A means of accumulating input care data and evaluating health status based on that data, A system that includes this.

2. The system according to claim 1, further comprising means for notifying a user terminal of a plan generated by artificial intelligence.

3. The system according to claim 1, comprising means for receiving data necessary for the implementation of a plan from a user and recording that information.

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