system

Abstract

We provide the system. [Solution] A means of processing data using an artificial intelligence agent finely tuned with specialized knowledge, A means including an information retrieval configuration that obtains laws and regulations and past cases and provides information necessary for decision-making, A means by which multiple artificial intelligence agents engage in discussions with each other and make decisions based on the integrated results, Data management methods for managing highly confidential information and protecting personal information, A system that includes this.

Description

【Technical Field】 【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 character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 <当該システムは、被介護者の要介護認定等級を決定する際の会議において専門家の負担を軽減しつつ、高度で統一された意思決定を提供する議論システムを構築することで、これらの課題を解決しようとするものであるという問題がある。 【0004】 <00当該システムはどのようにしてこれらの課題を解決しようとするものであるという問題がある。 <There is a problem that in a meeting where multiple experts gather to determine the care-required certification level of a care recipient, the burden on the experts is large and there are variations in the quality of discussions. In such a situation, time constraints affect the quality, making it difficult to make appropriate decisions. The present invention aims to solve these problems by constructing a discussion system that provides a high-level and unified decision-making while reducing the burden on experts. 【Means for Solving the Problems】 【0005】 This invention provides a system equipped with an information retrieval configuration that processes data using an artificial intelligence agent finely tuned with specialized knowledge, acquiring laws and past cases to provide information necessary for decision-making. Furthermore, multiple artificial intelligence agents engage in discussions with each other in natural language and make integrated decisions based on the results. This system also has strict data management means to manage highly confidential information and protect personal information. In this way, it reduces the burden on experts and enables efficient, consistent, and highly accurate certification. 【0006】 "Fine-tuning specialized knowledge" refers to optimizing artificial intelligence that possesses the necessary information and know-how in a specific specialized field using detailed datasets. 【0007】 An "artificial intelligence agent" refers to a computer program that analyzes data and makes decisions according to a specific purpose. 【0008】 An "information retrieval configuration" refers to a system for retrieving relevant information from a database, aggregating the necessary information, and providing it to users. 【0009】 "Discussing in natural language" refers to the process by which artificial intelligence agents exchange opinions and make decisions using human language. 【0010】 "Managing highly confidential information" refers to measures taken to protect highly sensitive information from being leaked when it is stored, accessed, or used. 【0011】 "Data management means" refers to the methods and processes for comprehensively acquiring, storing, accessing, and protecting data. [Brief explanation of the drawing] 【0012】 [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]This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, when an emotion engine is combined. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention] 【0013】 Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings. 【0014】 First, the terms used in the following description will be explained. 【0015】 In the following embodiments, the 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. 【0016】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0017】 In the following embodiments, the 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, and the like. 【0018】 In the following embodiments, the 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), and the like. 【0019】 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." 【0020】 [First Embodiment] 【0021】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0022】 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. 【0023】 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). 【0024】 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. 【0025】 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. 【0026】 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. 【0027】 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. 【0028】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0029】 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. 【0030】 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. 【0031】 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. 【0032】 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". 【0033】 This invention provides a system that supports efficient and highly accurate decision-making in long-term care certification review committees, and a specific embodiment thereof is described below. 【0034】 First, the user inputs basic information about the person receiving care, medical records, and care history via a terminal. This data is then incorporated into the system as information necessary for care certification. The server receives the data sent from the user and performs standardization and normalization to process it in a unified format. This makes the data suitable for processing by the artificial intelligence agent. 【0035】 Next, the server utilizes finely tuned expert AI agents to perform an initial analysis based on the input data. These AI agents include expert AIs from various fields, such as physician AI, public health nurse AI, and nutritionist AI. These agents analyze the data using their respective expertise and generate hypotheses and diagnoses. 【0036】 Furthermore, the terminal instructs the server to search for information on laws and past cases in response to user requests. This utilizes RAG (Retrieval-Augmented Generation) to acquire and analyze relevant information in real time. The server then incorporates this information into discussions among artificial intelligence agents to support evidence-based decision-making. 【0037】 Multiple artificial intelligence agents engage in discussions on a server using natural language processing technology, integrating opinions from multiple perspectives. The discussions among the AIs involve repeated processes of evaluation, counterargument, and revision, and based on the results, the most appropriate care needs assessment level is determined. 【0038】 Ultimately, the server makes a decision based on the discussion and sends the certification result to the terminal. The user can then review the result on the terminal and, if necessary, enter additional information or provide feedback. 【0039】 This system also takes into consideration the protection of highly confidential and personal information during processing, and the servers strictly manage data in accordance with security policies. This reduces the burden on experts and enables a highly reliable certification process. 【0040】 The following describes the processing flow. 【0041】 Step 1: 【0042】 The user uses a terminal to input necessary data such as the care recipient's basic information, medical records, and care history. The input data is then transmitted to the system in digital format as information necessary for care certification. 【0043】 Step 2: 【0044】 The server receives data sent from users and performs preprocessing to standardize the format. This process also includes detecting and correcting missing or outlier data to improve data quality. 【0045】 Step 3: 【0046】 The server passes the pre-processed data to various specialized artificial intelligence agents. These include AI doctors, AI public health nurses, and AI nutritionists, each of which begins analyzing the data based on their respective expertise. 【0047】 Step 4: 【0048】 In response to requests from terminals, the server utilizes a RAG configuration to retrieve information on laws and past cases from the database. The retrieved information is then organized as evidence necessary for discussions and decision-making. 【0049】 Step 5: 【0050】 The server initiates a discussion session using natural language processing among the artificial intelligence agents. The AIs exchange opinions and engage in discussions to make decisions, reflecting different perspectives. 【0051】 Step 6: 【0052】 The server integrates the views gathered from the discussion and determines the final care needs assessment level based on specific evaluation criteria. The decision-making process reflects a consensus among multiple expert AIs. 【0053】 Step 7: 【0054】 The server sends the determined certification result to the terminal. The user can then review the result through the terminal, enter feedback and additional information into the system as needed, and use this information for the next assessment process. 【0055】 Step 8: 【0056】 The server properly stores and manages the data used during the process. It ensures the protection of highly confidential information and personal data based on the highest level of security measures. 【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】 Traditional care needs assessment processes rely heavily on subjective judgments by various specialists, leading to challenges in consistency and accuracy. Furthermore, there is a need to handle data from diverse sources and establish a swift and secure decision-making process. Therefore, a system is needed that supports objective and efficient decision-making based on expert knowledge. 【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 users to input information through a terminal and convert it into a unified format, means for entrusting specialized knowledge to an optimized intelligent system to perform basic analysis, and means for using an information acquisition configuration that associates relevant laws and past cases and obtains information necessary for decision-making. This makes it possible to reduce the burden on experts and improve the consistency and accuracy of judgments in the care certification process. 【0062】 A "user" is a person who uses a computer terminal to input information into the system and participates in the care certification process. 【0063】 A "terminal" is a computer device used by users to input information and receive information from a system. 【0064】 "Means of converting information into a unified format" refers to the process of standardizing and normalizing input data to create a unified format. 【0065】 A "specialized, optimized intelligent system" refers to an artificial intelligence model that specializes in a particular field, and is finely tuned to suit the fields of medicine and nursing care. 【0066】 "Means of conducting basic analysis" refers to the process by which an optimized intelligent system performs initial analysis based on input data and generates hypotheses and diagnoses. 【0067】 "Means of using information acquisition configurations" refers to techniques for searching relevant laws and past cases to obtain information necessary for decision-making. 【0068】 "Supporting the decision-making of intelligent systems" refers to the process of assisting intelligent systems in making more accurate decisions based on acquired information. 【0069】 "Dialogue" is a form of communication in which multiple intelligent systems exchange information and share opinions with each other. 【0070】 First, the user uses a terminal to input information about the person receiving care. The terminal provides the user's input interface and accepts basic information, medical records, care history, etc. Software such as a browser or dedicated application is often used in this process. 【0071】 The entered information is sent to the server via the terminal. The server receives this data and begins the process of converting it into a unified format. Database management systems and data processing software are used for data standardization and normalization, ensuring consistency in format. 【0072】 Next, the server uses an optimized intelligent system, or fine-tuned AI agent, to perform basic analysis of the data. Machine learning libraries and cloud-based AI platforms are used here. For example, a physician AI assesses a patient's health status based on input medical records, while a public health nurse AI and a nutritionist AI leverage their respective expertise to generate insights into care needs and nutritional management. 【0073】 The terminal requests information from the server regarding laws and past cases. The server utilizes RAG (Retrieval-Augmented Generation) technology to retrieve relevant information from databases and external sources. This information is used as important evidence in AI-driven discussions to support the decision-making process. 【0074】 A concrete example would be a case like, "An 85-year-old male with diabetes and a recent history of hospitalization." When the user enters this information into the terminal, the server's physician AI performs an assessment of the diabetes, and the public health nurse AI and nutritionist AI provide advice on care and nutrition. The server then searches for relevant past cases and conducts discussions among the AIs to derive the optimal care level. 【0075】 An example of a prompt for a generating AI model is: "An 85-year-old male with diabetes and a recent hospitalization history. Begin the initial assessment in the care needs assessment process, and have the AI ​​agent conduct a discussion based on relevant laws and past case information. Derive the optimal care needs assessment level." 【0076】 In this way, the burden on experts can be reduced, and efficient and highly accurate decision-making can be achieved. 【0077】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0078】 Step 1: 【0079】 Users input basic information, medical records, and care history of the person receiving care through a terminal. The entered data is organized within the terminal according to a basic input format and prepared for transmission to the server. Guidance and auto-completion functions are used during the input stage to minimize input errors. 【0080】 Step 2: 【0081】 The terminal sends the data received from the user to the server. The server first verifies the received data, unifying and normalizing its format. In this process, a database management system is used to standardize, for example, date formats and medical terminology. The output is standardized data. 【0082】 Step 3: 【0083】 The server performs initial analysis using AI agents, which are optimized intelligent systems based on standardized data. Specifically, a physician AI assesses health status, a public health nurse AI analyzes the need for care, and a nutritionist AI suggests meals. Using the input data, each agent derives a professional diagnosis or hypothesis, which is then sent to the next discussion process. 【0084】 Step 4: 【0085】 The terminal instructs the server to search for laws and past case information based on user commands. The server uses RAG technology to acquire this information in real time. The information collected from databases and external sources is output as evidence necessary for discussions between AI agents. 【0086】 Step 5: 【0087】 On the server, multiple AI agents discuss the acquired information. Using natural language processing technology, each agent contributes their opinions, and the AIs evaluate, refute, and revise these opinions. Through this process, the optimal care needs assessment level is determined, and the final decision is output. 【0088】 Step 6: 【0089】 The server sends the final decision result to the terminal. The user reviews the result through the terminal and is given the opportunity to provide feedback and additional information as needed. The feedback received will be used to improve future processing. 【0090】 (Application Example 1) 【0091】 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." 【0092】 With the aging of society, demand for care facilities and home care is increasing. However, there is a lack of appropriate means of providing information to reduce the burden on care workers and improve the quality of services. In particular, there is a need for technology that can utilize the knowledge of multiple different experts in real time and provide concrete and appropriate countermeasures immediately on-site. 【0093】 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. 【0094】 In this invention, the server includes means for processing data using an artificial intelligence agent finely tuned with specialized knowledge; means for including an information retrieval configuration that acquires laws and regulations and past cases and provides information necessary for decision-making; and means for providing information to the user in real time via a visual device and visualizing and displaying suggestions. This enables care workers to immediately acquire appropriate countermeasures according to the condition of the person being cared for, thereby improving the efficiency and quality of care services. 【0095】 A "finely tuned artificial intelligence agent" is an artificial intelligence system that has been adjusted to deeply learn information in a specific domain and perform advanced analysis and decision-making based on that learning. 【0096】 An "information retrieval configuration for acquiring laws and past cases" refers to a system component for retrieving necessary information based on legal regulations and relevant past cases and providing it to users. 【0097】 "Means of providing information to users in real time via visual devices" refers to technologies that visually display useful information to users instantly through devices such as smart glasses and head-mounted displays. 【0098】 "Means of visualizing and displaying proposals" refers to methods of visually displaying solutions and guidelines derived by artificial intelligence in a way that is easy for users to understand. 【0099】 A "server" is a central computing system that receives, analyzes, stores, and provides data, and refers to a device that communicates with other devices over a network. 【0100】 The system for realizing this invention consists of a cloud server, a smart device, and an artificial intelligence agent. The server receives data about the care recipient entered by the user and acts as a pacemaker. Smart glasses are primarily envisioned as the terminal used by the user, and these serve as the interface for providing real-time information. 【0101】 The server analyzes the received data using AI agents written in Python. These AI agents include, for example, medical AI, nutrition AI, and nursing AI, and generate appropriate care methods based on the data. A database management system built on the cloud (e.g., MongoDB) also acquires and integrates information on laws and regulations and past care cases. 【0102】 Smart glasses visualize suggestions from a server for the user and display the information through an intuitive interface. To achieve this, each piece of information is converted into a user-friendly format using OCR and natural language processing technologies. Furthermore, the visual device utilizes short-circuit switching technology, enabling rapid information switching. 【0103】 For example, when a care recipient's condition suddenly changes, the smart glasses immediately display first aid procedures and past response examples, allowing caregivers to take swift action based on this information. Furthermore, an example of a prompt message generated using the AI ​​model is, "Please tell me the most appropriate care method for the care recipient's recent health changes. Please include similar past cases and recommendations based on relevant laws and regulations." 【0104】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0105】 Step 1: 【0106】 The server receives basic information and medical history about the care recipient entered by the user via a terminal. This input data is mainly in text format and sensor data, and is standardized and normalized for subsequent processing. This makes the data suitable for analysis by the AI ​​agent. 【0107】 Step 2: 【0108】 The server processes the received data using various AI agents that run on Python. Expert AIs, such as medical AI and nutritional AI, analyze the data within their respective fields and generate appropriate hypotheses and diagnostic results. This process utilizes data mining and pattern recognition techniques. 【0109】 Step 3: 【0110】 The server communicates with the visual device and sends analyzed information to the smart glasses. This includes caregiving suggestions and first-aid procedures. The glasses visualize the information and display it in the user's field of vision. In this step, data is output in a concise and easy-to-read format through the interface with the device. 【0111】 Step 4: 【0112】 The server retrieves laws and past cases from a database and supplements them with relevant information using an AI agent. Users can request this information as needed through the smart glasses interface. Relevant laws and past cases are retrieved in real time through information retrieval based on prompt messages. 【0113】 Step 5: 【0114】 Users provide care based on the information presented. They can take appropriate action immediately by referring to real-time information obtained through the glasses. User feedback and new data are returned to the server, enabling continuous learning and improvement of the system. 【0115】 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. 【0116】 This invention incorporates an emotion engine into a system for supporting effective decision-making in long-term care certification review committees, and a specific embodiment thereof is described below. 【0117】 First, the user inputs basic information and medical records of the person being cared for into the system via a terminal. This input is done through a user-friendly interface. At this time, the emotion engine analyzes parameters such as the user's voice tone and input speed, recognizing the user's emotional state in real time. 【0118】 The server receives data sent by the user and emotional information provided by the emotion engine, and performs data preprocessing. This process includes data standardization as well as metadata about the user's emotional state. This allows the specialized artificial intelligence agent to more accurately understand the user's needs. 【0119】 Next, the server passes the pre-processed data to finely tuned expert AIs for analysis. Each expert AI, such as a doctor, public health nurse, or nutritionist, generates hypotheses and diagnoses based on the input data and emotional information. The generated opinions reflect their respective professional perspectives and serve as a basis for careful decision-making. 【0120】 Furthermore, based on user actions, the server searches for relevant laws and past cases using a RAG (Regional Aggregation) configuration. The server provides interactive responses that take sentiment into account, presenting information to aid user understanding. 【0121】 The emotion engine on the server also takes into account factors related to the user's emotions during discussions between artificial intelligence agents. For example, if a user is feeling anxious, the AI ​​can provide a careful explanation to alleviate that anxiety. 【0122】 Ultimately, the server determines the certification level based on consensus from multiple perspectives and sends the result to the terminal. Users can review the received result and provide feedback and comments. This feedback is analyzed by an emotion engine and used to improve the interface in the future. 【0123】 This system also takes into consideration the analysis and management of emotional data, and the servers are protected by a strict security policy, ensuring thorough data protection. This makes it possible to achieve highly accurate diagnoses while reducing the psychological burden on the user. 【0124】 The following describes the processing flow. 【0125】 Step 1: 【0126】 The user uses a terminal to input necessary data such as the care recipient's basic information, medical records, and care history. Simultaneously, the emotion engine analyzes the user's voice tone and input speed to recognize the user's emotional state in real time. 【0127】 Step 2: 【0128】 The server receives data sent by the user and performs data normalization and standardization. During this process, it adds emotional information analyzed by the emotion engine, generating metadata that takes the user's emotional state into account. 【0129】 Step 3: 【0130】 The server passes pre-processed data to finely tuned artificial intelligence agents, and expert AIs begin data analysis. Doctor AI, public health nurse AI, and nutritionist AI generate opinions based on their respective expertise. In this process, decisions are formed that take into account the user's emotional information. 【0131】 Step 4: 【0132】 In response to requests from the terminal, the server uses a RAG configuration to search for laws and past cases and collect relevant information. The sentiment engine then adjusts the retrieved information before presenting it to the user, generating a response that aids user understanding. 【0133】 Step 5: 【0134】 The server initiates a process in which multiple expert AIs engage in discussions with each other. The emotion engine considers the user's emotions during the discussion, supporting the AI ​​in providing thoughtful explanations, such as those aimed at reducing anxiety. 【0135】 Step 6: 【0136】 The server integrates the results of the discussion with the user's emotional information to determine the final care needs assessment level. High-precision decision-making is achieved by reflecting the consensus of multiple expert AIs and insights from the emotional engine. 【0137】 Step 7: 【0138】 The server sends the determined certification result to the terminal. The user can review the result through the terminal and enter their feedback and additional information. User feedback is again analyzed by the emotion engine and used to improve the user interface for future use. 【0139】 Step 8: 【0140】 The server manages all data under strict security standards. We thoroughly protect acquired emotional data and personal information, maintaining a system that safeguards user privacy. 【0141】 (Example 2) 【0142】 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". 【0143】 In nursing care and medical settings, making swift and accurate decisions based on specialized knowledge is crucial. However, it is not easy to integrate the opinions of multiple experts and make consistent judgments while also considering the emotional state of the service users. Furthermore, it is necessary to ensure the secure management of information and provide accurate information to service users. Therefore, there is a need for a system that comprehensively addresses these challenges. 【0144】 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. 【0145】 In this invention, the server includes means for processing information using an intelligent agent finely tuned with specialized knowledge; means for including an information retrieval configuration that acquires laws and past cases and provides information necessary for decision-making; and means for recognizing the user's emotional state and integrating the analysis results to reflect in decision-making. This enables efficient and accurate decision-making that reflects the user's needs. 【0146】 "Specialized knowledge" refers to having a deep understanding and skills in a particular field, which are used to solve problems and make judgments in that field. 【0147】 A "finely tuned intelligent agent" refers to an artificial intelligence program that has been adjusted to be optimized for a specific task or purpose, and is designed to achieve higher accuracy and efficiency. 【0148】 An "information retrieval configuration" refers to a system for quickly searching for relevant information from large amounts of data and providing it to users. This configuration is used to support efficient decision-making. 【0149】 "Emotional state" refers to a user's psychological or emotional response or condition, and is a factor that influences their behavior and decision-making. 【0150】 "Decision-making based on discussion and integrated conclusions" refers to a decision-making process in which multiple intelligent agents exchange opinions with each other and ultimately make decisions based on a consensus reached. 【0151】 "Data management means" refers to methods and technologies for storing, preserving, and controlling access to information, and is particularly used to protect confidential information and personal information. 【0152】 In this system, users input data such as basic information and medical records of the person receiving care through a terminal. This input is done through a user-friendly interface, prioritizing ease of use. For example, a user might input information such as "70-year-old male, difficulty walking, suspected of having diabetes according to recent diagnosis." At this point, the emotion engine analyzes the user's tone of voice and input speed to recognize their emotional state in real time. 【0153】 The server receives data sent by the user and emotional information provided by the emotion engine, and preprocesses the data. Through a data standardization process, metadata about the user's emotional state is added while maintaining the integrity of the materials, enabling the intelligent agent to more accurately understand the user's needs. This prepares the server to provide more appropriate care plans. 【0154】 Next, the server passes the pre-processed data to finely tuned, specialized intelligent agents for analysis. These intelligent agents evaluate the data from perspectives based on medical knowledge, health, and nutrition, respectively, and generate hypotheses and diagnoses. The results of these specialized perspectives are then used by the care certification review committee to make appropriate decisions regarding the user. 【0155】 Furthermore, in response to user actions, the server searches for relevant laws and past cases using a RAG (Regional Aggregation) configuration and provides relevant information. For example, it can create a prompt message such as "nursing support plan based on specific diagnostic results" and input it into a generating AI model, which can then suggest appropriate diagnostic results as support measures. In this way, a situation is created where users can receive support with peace of mind. 【0156】 The system's emotion engine can design conversations by considering the user's emotional information and reflect that influence in discussions between AI agents. This makes it possible to provide more careful and empathetic explanations and a sense of security when users feel anxious or doubtful. 【0157】 Ultimately, the server determines the agreed-upon care needs assessment level based on all professional perspectives and emotional information, and sends the result to the terminal. This allows the user to review the assessment result and provide feedback as needed. This feedback is analyzed by the emotional engine and used to improve the system in the future. 【0158】 This system incorporates the latest security measures for the analysis and management of emotional data, and the servers are protected under a strict security policy. This makes it possible to reduce the psychological burden on users while enabling accurate diagnosis and effective care support. 【0159】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0160】 Step 1: 【0161】 Users input basic information and medical records of the person receiving care through their device. This input includes name, age, symptoms, and diagnosis. Specifically, the user enters information into a form on the screen and presses the submit button, sending the data to the system. The input data is temporarily stored on the device before being sent to the server. 【0162】 Step 2: 【0163】 The device sends the entered data to the server, where an emotion engine analyzes the user's voice tone and input speed in the background. During this process, the user's input actions (clicks, keyboard typing speed, etc.) are also monitored to generate data that infers their emotional state. This emotional data then influences decision-making in subsequent processes. 【0164】 Step 3: 【0165】 The server receives data sent from the terminal and performs data preprocessing. Preprocessing includes data standardization, noise reduction, and metadata creation of sentiment information. Standardization converts numerical data into a unified format and adjusts for irregularities in text data. This generates a consistent dataset. 【0166】 Step 4: 【0167】 The server passes pre-processed data to fine-tuned intelligent agents, where expert AIs perform analysis. Specifically, a medical AI assesses symptoms, a nutrition AI provides dietary recommendations, and a health AI develops care plans. The analysis results integrate opinions from multiple perspectives. For data processing, a generative AI model based on prompt text is used to generate detailed analysis results and recommendations. 【0168】 Step 5: 【0169】 The terminal retrieves analysis results provided by the server and searches for information on laws and past cases using a RAG (Retrieval-Augmented Generation) configuration. This presents the user with legal grounds and similar case studies to support the AI's judgment. The terminal organizes this information and displays it as material for the user to make a decision. 【0170】 Step 6: 【0171】 The server utilizes an emotion engine to interact with users and generate responses that reflect emotional information. For example, it provides a thorough explanation to an anxious user, reassuring them. The feedback obtained as a result of the interaction is analyzed on the server to inform future suggestions and improve the interface. 【0172】 Step 7: 【0173】 The server determines the final care needs assessment level based on multiple perspectives and emotional information, and sends the result to the terminal. Users can review this result through the terminal and input their opinions and feedback. This feedback is compiled by the server and used to improve the system. 【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】 In modern care settings, staff are required to process large amounts of information and make quick and accurate decisions in order to appropriately respond to the condition and needs of those receiving care. However, traditional systems have made it difficult to accurately grasp the emotional state of residents and plan care that takes this into account. Furthermore, the psychological burden on staff tends to increase, and staff shortages are a problem. It is necessary to solve these problems and provide a better care environment. 【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 processing means for recognizing and analyzing emotional states, means for processing data using an artificial intelligence agent finely tuned with specialized knowledge, and means including an information retrieval configuration that acquires laws and regulations and past cases and provides information necessary for decision-making. This makes it possible to propose appropriate care responses that take into account the emotional states of the care recipient and staff. 【0179】 "Emotional state" refers to an individual's internal emotional state, including emotions such as happiness, anxiety, and anger. 【0180】 An "artificial intelligence agent" is a program designed to achieve a specific purpose and operates autonomously using specialized knowledge and algorithms. 【0181】 "Data processing" refers to a series of tasks that involve organizing, analyzing, and converting collected information into a usable format. 【0182】 An "information retrieval configuration" refers to the functions and mechanisms for efficiently searching for and obtaining necessary data and information. 【0183】 "Interactive response" refers to a response mechanism that presents appropriate and relevant information in response to user input. 【0184】 "Data management" refers to the management processes related to the security, storage, retrieval, and deletion of information. 【0185】 "Fine-tuning" is the process of optimizing existing models or systems to meet specific needs and requirements. 【0186】 The system realizing this invention is a complex platform for analyzing emotional states and supporting decision-making in care settings. The server is equipped with dedicated software for emotion recognition and can acquire and analyze emotional data from voice and text input. The server further operates a finely tuned artificial intelligence agent that analyzes the received data based on its expertise to optimize care responses and planning. 【0187】 On the other hand, the terminal is equipped with a user interface and is designed to allow nursing home staff to easily input basic information and health records of those receiving care. The terminal also has a function to search and present laws and past cases in real time based on user operations. This allows staff to quickly and easily obtain relevant information and use it to take appropriate action. 【0188】 Through the coordinated operation of the server and terminal, users can receive interactive responses based on emotional data, enabling less stressful communication with the care recipient. The server then sends the resulting care plan and diagnosis to the terminal, providing direct feedback to the user and facilitating the rapid implementation of appropriate measures. 【0189】 For example, if a person receiving care shows signs of anxiety during communication, the device detects this and sends the information to the server. The server quickly analyzes the information and recommends specific actions to the staff to alleviate the anxiety. 【0190】 An example of a prompt message generated using an AI model is: "Please input the resident's health data and analyze their current emotional state. Then, based on the analysis results, please suggest appropriate care measures." 【0191】 This invention will enable nursing care facilities to provide more humane and efficient care to those receiving care. 【0192】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0193】 Step 1: 【0194】 The user uses a terminal to input basic information and health data of the person being cared for. This information is sent to the server in text format. The entered data is received by the server and organized in preparation for the next analysis step. 【0195】 Step 2: 【0196】 The server analyzes the user's voice data using emotion recognition software. The user's emotional state is analyzed from the voice data, and emotional information such as feelings of reassurance or anxiety is extracted. The resulting emotional data is then used for processing by the artificial intelligence agent. 【0197】 Step 3: 【0198】 The server uses a finely tuned artificial intelligence agent to analyze the input health and emotional data. This process involves data processing and calculations to assess the care recipient's condition and generate appropriate care plans and countermeasures. As a result, care-appropriate guidelines are generated and reported in the next step. 【0199】 Step 4: 【0200】 The server sends appropriate care response measures to the terminal. The terminal displays the guidelines received from the server on the user interface, providing staff with a standard for taking specific actions. The outputted response measures can be used by users when making decisions on-site. 【0201】 Step 5: 【0202】 The terminal accepts user feedback and additional input. This feedback is sent to the server as valuable data for improving the overall system's responsiveness and interface, and is used for analysis in the next cycle. 【0203】 In this way, emotional data can be utilized to enable efficient and humane responses in caregiving settings. 【0204】 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. 【0205】 Data generation model 58 is a 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. 【0206】 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. 【0207】 [Second Embodiment] 【0208】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0209】 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. 【0210】 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). 【0211】 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. 【0212】 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. 【0213】 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). 【0214】 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. 【0215】 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. 【0216】 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. 【0217】 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. 【0218】 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. 【0219】 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". 【0220】 This invention provides a system that supports efficient and highly accurate decision-making in long-term care certification review committees, and a specific embodiment thereof is described below. 【0221】 First, the user inputs basic information about the person receiving care, medical records, and care history via a terminal. This data is then incorporated into the system as information necessary for care certification. The server receives the data sent from the user and performs standardization and normalization to process it in a unified format. This makes the data suitable for processing by the artificial intelligence agent. 【0222】 Next, the server utilizes finely tuned expert AI agents to perform an initial analysis based on the input data. These AI agents include expert AIs from various fields, such as physician AI, public health nurse AI, and nutritionist AI. These agents analyze the data using their respective expertise and generate hypotheses and diagnoses. 【0223】 Furthermore, the terminal instructs the server to search for information on laws and past cases in response to user requests. This utilizes RAG (Retrieval-Augmented Generation) to acquire and analyze relevant information in real time. The server then incorporates this information into discussions among artificial intelligence agents to support evidence-based decision-making. 【0224】 Multiple artificial intelligence agents engage in discussions on a server using natural language processing technology, integrating opinions from multiple perspectives. The discussions among the AIs involve repeated processes of evaluation, counterargument, and revision, and based on the results, the most appropriate care needs assessment level is determined. 【0225】 Ultimately, the server makes a decision based on the discussion and sends the certification result to the terminal. The user can then review the result on the terminal and, if necessary, enter additional information or provide feedback. 【0226】 This system also takes into consideration the protection of highly confidential and personal information during processing, and the servers strictly manage data in accordance with security policies. This reduces the burden on experts and enables a highly reliable certification process. 【0227】 The following describes the processing flow. 【0228】 Step 1: 【0229】 The user uses a terminal to input necessary data such as the care recipient's basic information, medical records, and care history. The input data is then transmitted to the system in digital format as information necessary for care certification. 【0230】 Step 2: 【0231】 The server receives data sent from users and performs preprocessing to standardize the format. This process also includes detecting and correcting missing or outlier data to improve data quality. 【0232】 Step 3: 【0233】 The server passes the pre-processed data to various specialized artificial intelligence agents. These include AI doctors, AI public health nurses, and AI nutritionists, each of which begins analyzing the data based on their respective expertise. 【0234】 Step 4: 【0235】 In response to requests from terminals, the server utilizes a RAG configuration to retrieve information on laws and past cases from the database. The retrieved information is then organized as evidence necessary for discussions and decision-making. 【0236】 Step 5: 【0237】 The server initiates a discussion session using natural language processing among the artificial intelligence agents. The AIs exchange opinions and engage in discussions to make decisions, reflecting different perspectives. 【0238】 Step 6: 【0239】 The server integrates the views gathered from the discussion and determines the final care needs assessment level based on specific evaluation criteria. The decision-making process reflects a consensus among multiple expert AIs. 【0240】 Step 7: 【0241】 The server sends the determined certification result to the terminal. The user can then review the result through the terminal, enter feedback and additional information into the system as needed, and use this information for the next assessment process. 【0242】 Step 8: 【0243】 The server properly stores and manages the data used during the process. It ensures the protection of highly confidential information and personal data based on the highest level of security measures. 【0244】 (Example 1) 【0245】 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." 【0246】 Traditional care needs assessment processes rely heavily on subjective judgments by various specialists, leading to challenges in consistency and accuracy. Furthermore, there is a need to handle data from diverse sources and establish a swift and secure decision-making process. Therefore, a system is needed that supports objective and efficient decision-making based on expert knowledge. 【0247】 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. 【0248】 In this invention, the server includes means for users to input information through a terminal and convert it into a unified format, means for entrusting specialized knowledge to an optimized intelligent system to perform basic analysis, and means for using an information acquisition configuration that associates relevant laws and past cases and obtains information necessary for decision-making. This makes it possible to reduce the burden on experts and improve the consistency and accuracy of judgments in the care certification process. 【0249】 A "user" is a person who uses a computer terminal to input information into the system and participates in the care certification process. 【0250】 A "terminal" is a computer device used by users to input information and receive information from a system. 【0251】 "Means of converting information into a unified format" refers to the process of standardizing and normalizing input data to create a unified format. 【0252】 A "specialized, optimized intelligent system" refers to an artificial intelligence model that specializes in a particular field, and is finely tuned to suit the fields of medicine and nursing care. 【0253】 "Means of conducting basic analysis" refers to the process by which an optimized intelligent system performs initial analysis based on input data and generates hypotheses and diagnoses. 【0254】 "Means of using information acquisition configurations" refers to techniques for searching relevant laws and past cases to obtain information necessary for decision-making. 【0255】 "Supporting the decision-making of intelligent systems" refers to the process of assisting intelligent systems in making more accurate decisions based on acquired information. 【0256】 "Dialogue" is a form of communication in which multiple intelligent systems exchange information and share opinions with each other. 【0257】 First, the user uses a terminal to input information about the person receiving care. The terminal provides the user's input interface and accepts basic information, medical records, care history, etc. Software such as a browser or dedicated application is often used in this process. 【0258】 The entered information is sent to the server via the terminal. The server receives this data and begins the process of converting it into a unified format. Database management systems and data processing software are used for data standardization and normalization, ensuring consistency in format. 【0259】 Next, the server uses an optimized intelligent system, or fine-tuned AI agent, to perform basic analysis of the data. Machine learning libraries and cloud-based AI platforms are used here. For example, a physician AI assesses a patient's health status based on input medical records, while a public health nurse AI and a nutritionist AI leverage their respective expertise to generate insights into care needs and nutritional management. 【0260】 The terminal requests information from the server regarding laws and past cases. The server utilizes RAG (Retrieval-Augmented Generation) technology to retrieve relevant information from databases and external sources. This information is used as important evidence in AI-driven discussions to support the decision-making process. 【0261】 A concrete example would be a case like, "An 85-year-old male with diabetes and a recent history of hospitalization." When the user enters this information into the terminal, the server's physician AI performs an assessment of the diabetes, and the public health nurse AI and nutritionist AI provide advice on care and nutrition. The server then searches for relevant past cases and conducts discussions among the AIs to derive the optimal care level. 【0262】 An example of a prompt for a generating AI model is: "An 85-year-old male with diabetes and a recent hospitalization history. Begin the initial assessment in the care needs assessment process, and have the AI ​​agent conduct a discussion based on relevant laws and past case information. Derive the optimal care needs assessment level." 【0263】 In this way, the burden on experts can be reduced, and efficient and highly accurate decision-making can be achieved. 【0264】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0265】 Step 1: 【0266】 Users input basic information, medical records, and care history of the person receiving care through a terminal. The entered data is organized within the terminal according to a basic input format and prepared for transmission to the server. Guidance and auto-completion functions are used during the input stage to minimize input errors. 【0267】 Step 2: 【0268】 The terminal sends the data received from the user to the server. The server first verifies the received data, unifying and normalizing its format. In this process, a database management system is used to standardize, for example, date formats and medical terminology. The output is standardized data. 【0269】 Step 3: 【0270】 The server performs initial analysis using AI agents, which are optimized intelligent systems based on standardized data. Specifically, a physician AI assesses health status, a public health nurse AI analyzes the need for care, and a nutritionist AI suggests meals. Using the input data, each agent derives a professional diagnosis or hypothesis, which is then sent to the next discussion process. 【0271】 Step 4: 【0272】 The terminal instructs the server to search for laws and past case information based on user commands. The server uses RAG technology to acquire this information in real time. The information collected from databases and external sources is output as evidence necessary for discussions between AI agents. 【0273】 Step 5: 【0274】 On the server, multiple AI agents discuss the acquired information. Using natural language processing technology, each agent contributes their opinions, and the AIs evaluate, refute, and revise these opinions. Through this process, the optimal care needs assessment level is determined, and the final decision is output. 【0275】 Step 6: 【0276】 The server sends the final decision result to the terminal. The user reviews the result through the terminal and is given the opportunity to provide feedback and additional information as needed. The feedback received will be used to improve future processing. 【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】 With the aging of society, demand for care facilities and home care is increasing. However, there is a lack of appropriate means of providing information to reduce the burden on care workers and improve the quality of services. In particular, there is a need for technology that can utilize the knowledge of multiple different experts in real time and provide concrete and appropriate countermeasures immediately on-site. 【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】 In this invention, the server includes means for processing data using an artificial intelligence agent finely tuned with specialized knowledge; means for including an information retrieval configuration that acquires laws and regulations and past cases and provides information necessary for decision-making; and means for providing information to the user in real time via a visual device and visualizing and displaying suggestions. This enables care workers to immediately acquire appropriate countermeasures according to the condition of the person being cared for, thereby improving the efficiency and quality of care services. 【0282】 A "specially tuned artificial intelligence agent with specialized knowledge" is an artificial intelligence system that deeply learns information in a specific area and is adjusted to perform advanced analysis and judgment based on it. 【0283】 An "information retrieval configuration for obtaining laws and past cases" is a component of a system for retrieving necessary information based on legal rules and past related cases and providing it to users. 【0284】 A "means for providing information to users in real time via a visual device" is a technology for visually displaying useful information to users immediately through devices such as smart glasses and head-mounted displays. 【0285】 A "means for visualizing and displaying proposals" is a method for visually displaying solutions and guidelines derived by artificial intelligence in a form that is easy for users to understand. 【0286】 A "server" is a central computer system that receives, analyzes, stores, and provides data, and refers to a device that communicates with other devices via a network. 【0287】 The system for realizing this invention is composed of a cloud server, smart devices, and artificial intelligence agents. The server receives data on the cared-for person input by the user and acts as a pacemaker. The main terminal assumed to be used by the user is smart glasses, which serve as an interface for real-time information provision. 【0288】 The server analyzes the received data with AI agents using Python. These AI agents include, for example, medical AI, nutrition AI, nursing AI, etc., and generate appropriate care methods based on the data. Information on laws and past care cases is also obtained and integrated by a database management system (e.g., MongoDB) built on the cloud. 【0289】 Smart glasses visualize suggestions from a server for the user and display the information through an intuitive interface. To achieve this, each piece of information is converted into a user-friendly format using OCR and natural language processing technologies. Furthermore, the visual device utilizes short-circuit switching technology, enabling rapid information switching. 【0290】 For example, when a care recipient's condition suddenly changes, the smart glasses immediately display first aid procedures and past response examples, allowing caregivers to take swift action based on this information. Furthermore, an example of a prompt message generated using the AI ​​model is, "Please tell me the most appropriate care method for the care recipient's recent health changes. Please include similar past cases and recommendations based on relevant laws and regulations." 【0291】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0292】 Step 1: 【0293】 The server receives basic information and medical history about the care recipient entered by the user via a terminal. This input data is mainly in text format and sensor data, and is standardized and normalized for subsequent processing. This makes the data suitable for analysis by the AI ​​agent. 【0294】 Step 2: 【0295】 The server processes the received data using various AI agents that run on Python. Expert AIs, such as medical AI and nutritional AI, analyze the data within their respective fields and generate appropriate hypotheses and diagnostic results. This process utilizes data mining and pattern recognition techniques. 【0296】 Step 3: 【0297】 The server communicates with the visual device and sends analyzed information to the smart glasses. This includes caregiving suggestions and first-aid procedures. The glasses visualize the information and display it in the user's field of vision. In this step, data is output in a concise and easy-to-read format through the interface with the device. 【0298】 Step 4: 【0299】 The server retrieves laws and past cases from a database and supplements them with relevant information using an AI agent. Users can request this information as needed through the smart glasses interface. Relevant laws and past cases are retrieved in real time through information retrieval based on prompt messages. 【0300】 Step 5: 【0301】 Users provide care based on the information presented. They can take appropriate action immediately by referring to real-time information obtained through the glasses. User feedback and new data are returned to the server, enabling continuous learning and improvement of the system. 【0302】 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. 【0303】 This invention incorporates an emotion engine into a system for supporting effective decision-making in long-term care certification review committees, and a specific embodiment thereof is described below. 【0304】 First, the user inputs basic information and medical records of the person being cared for into the system via a terminal. This input is done through a user-friendly interface. At this time, the emotion engine analyzes parameters such as the user's voice tone and input speed, recognizing the user's emotional state in real time. 【0305】 The server receives the data sent by the user and the emotion information provided by the emotion engine, and performs preprocessing on the data. In this process, in addition to normalizing the data, metadata regarding the user's emotional state is also added. This enables specialized artificial intelligence agents to more accurately grasp the user's needs. 【0306】 Next, the server passes the preprocessed data to the fine-tuned expert AI for analysis. Each expert AI such as doctors, nurses, and dietitians generates hypotheses and diagnoses based on the input data and emotion information. The generated opinions reflect their respective specialized perspectives and serve as detailed judgment materials. 【0307】 Furthermore, based on the user's operation, the terminal causes the server to search for relevant laws and past cases in the RAG configuration. The server provides an interactive response considering the emotion information and presents information to assist the user's understanding. 【0308】 The emotion engine on the server also considers factors arising from the user's emotions in the discussions conducted among artificial intelligence agents. For example, when the user is feeling anxious, it is also possible for the AI to provide a detailed explanation to soothe it. 【0309】 Finally, the server determines the certification level based on the consensus from multiple perspectives and sends the result to the terminal. The user can confirm the received result and provide comments and feedback. The feedback is analyzed by the emotion engine and used to improve future interfaces. 【0310】 This system also takes into account the analysis and management of emotion data, and the server thoroughly conducts data protection under strict security policies. This makes it possible to achieve highly accurate diagnosis while reducing the user's psychological burden. 【0311】 The processing flow will be described below. 【0312】 Step 1: 【0313】 The user uses a terminal to input necessary data such as the care recipient's basic information, medical records, and care history. Simultaneously, the emotion engine analyzes the user's voice tone and input speed to recognize the user's emotional state in real time. 【0314】 Step 2: 【0315】 The server receives data sent by the user and performs data normalization and standardization. During this process, it adds emotional information analyzed by the emotion engine, generating metadata that takes the user's emotional state into account. 【0316】 Step 3: 【0317】 The server passes pre-processed data to finely tuned artificial intelligence agents, and expert AIs begin data analysis. Doctor AI, public health nurse AI, and nutritionist AI generate opinions based on their respective expertise. In this process, decisions are formed that take into account the user's emotional information. 【0318】 Step 4: 【0319】 In response to requests from the terminal, the server uses a RAG configuration to search for laws and past cases and collect relevant information. The sentiment engine then adjusts the retrieved information before presenting it to the user, generating a response that aids user understanding. 【0320】 Step 5: 【0321】 The server initiates a process in which multiple expert AIs engage in discussions with each other. The emotion engine considers the user's emotions during the discussion, supporting the AI ​​in providing thoughtful explanations, such as those aimed at reducing anxiety. 【0322】 Step 6: 【0323】 The server integrates the results of the discussion with the user's emotional information to determine the final care needs assessment level. High-precision decision-making is achieved by reflecting the consensus of multiple expert AIs and insights from the emotional engine. 【0324】 Step 7: 【0325】 The server sends the determined certification result to the terminal. The user can review the result through the terminal and enter their feedback and additional information. User feedback is again analyzed by the emotion engine and used to improve the user interface for future use. 【0326】 Step 8: 【0327】 The server manages all data under strict security standards. We thoroughly protect acquired emotional data and personal information, maintaining a system that safeguards user privacy. 【0328】 (Example 2) 【0329】 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". 【0330】 In nursing care and medical settings, making swift and accurate decisions based on specialized knowledge is crucial. However, it is not easy to integrate the opinions of multiple experts and make consistent judgments while also considering the emotional state of the service users. Furthermore, it is necessary to ensure the secure management of information and provide accurate information to service users. Therefore, there is a need for a system that comprehensively addresses these challenges. 【0331】 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. 【0332】 In this invention, the server includes means for processing information using an intelligent agent finely tuned with specialized knowledge; means for including an information retrieval configuration that acquires laws and past cases and provides information necessary for decision-making; and means for recognizing the user's emotional state and integrating the analysis results to reflect in decision-making. This enables efficient and accurate decision-making that reflects the user's needs. 【0333】 "Specialized knowledge" refers to having a deep understanding and skills in a particular field, which are used to solve problems and make judgments in that field. 【0334】 A "finely tuned intelligent agent" refers to an artificial intelligence program that has been adjusted to be optimized for a specific task or purpose, and is designed to achieve higher accuracy and efficiency. 【0335】 An "information retrieval configuration" refers to a system for quickly searching for relevant information from large amounts of data and providing it to users. This configuration is used to support efficient decision-making. 【0336】 "Emotional state" refers to a user's psychological or emotional response or condition, and is a factor that influences their behavior and decision-making. 【0337】 "Decision-making based on discussion and integrated conclusions" refers to a decision-making process in which multiple intelligent agents exchange opinions with each other and ultimately make decisions based on a consensus reached. 【0338】 "Data management means" refers to methods and technologies for storing, preserving, and controlling access to information, and is particularly used to protect confidential information and personal information. 【0339】 In this system, users input data such as basic information and medical records of the person receiving care through a terminal. This input is done through a user-friendly interface, prioritizing ease of use. For example, a user might input information such as "70-year-old male, difficulty walking, suspected of having diabetes according to recent diagnosis." At this point, the emotion engine analyzes the user's tone of voice and input speed to recognize their emotional state in real time. 【0340】 The server receives data sent by the user and emotional information provided by the emotion engine, and preprocesses the data. Through a data standardization process, metadata about the user's emotional state is added while maintaining the integrity of the materials, enabling the intelligent agent to more accurately understand the user's needs. This prepares the server to provide more appropriate care plans. 【0341】 Next, the server passes the pre-processed data to finely tuned, specialized intelligent agents for analysis. These intelligent agents evaluate the data from perspectives based on medical knowledge, health, and nutrition, respectively, and generate hypotheses and diagnoses. The results of these specialized perspectives are then used by the care certification review committee to make appropriate decisions regarding the user. 【0342】 Furthermore, in response to user actions, the server searches for relevant laws and past cases using a RAG (Regional Aggregation) configuration and provides relevant information. For example, it can create a prompt message such as "nursing support plan based on specific diagnostic results" and input it into a generating AI model, which can then suggest appropriate diagnostic results as support measures. In this way, a situation is created where users can receive support with peace of mind. 【0343】 The system's emotion engine can design conversations by considering the user's emotional information and reflect that influence in discussions between AI agents. This makes it possible to provide more careful and empathetic explanations and a sense of security when users feel anxious or doubtful. 【0344】 Ultimately, the server determines the agreed-upon care needs assessment level based on all professional perspectives and emotional information, and sends the result to the terminal. This allows the user to review the assessment result and provide feedback as needed. This feedback is analyzed by the emotional engine and used to improve the system in the future. 【0345】 This system incorporates the latest security measures for the analysis and management of emotional data, and the servers are protected under a strict security policy. This makes it possible to reduce the psychological burden on users while enabling accurate diagnosis and effective care support. 【0346】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0347】 Step 1: 【0348】 Users input basic information and medical records of the person receiving care through their device. This input includes name, age, symptoms, and diagnosis. Specifically, the user enters information into a form on the screen and presses the submit button, sending the data to the system. The input data is temporarily stored on the device before being sent to the server. 【0349】 Step 2: 【0350】 The device sends the entered data to the server, where an emotion engine analyzes the user's voice tone and input speed in the background. During this process, the user's input actions (clicks, keyboard typing speed, etc.) are also monitored to generate data that infers their emotional state. This emotional data then influences decision-making in subsequent processes. 【0351】 Step 3: 【0352】 The server receives data sent from the terminal and performs data preprocessing. Preprocessing includes data standardization, noise reduction, and metadata creation of sentiment information. Standardization converts numerical data into a unified format and adjusts for irregularities in text data. This generates a consistent dataset. 【0353】 Step 4: 【0354】 The server passes pre-processed data to fine-tuned intelligent agents, where expert AIs perform analysis. Specifically, a medical AI assesses symptoms, a nutrition AI provides dietary recommendations, and a health AI develops care plans. The analysis results integrate opinions from multiple perspectives. For data processing, a generative AI model based on prompt text is used to generate detailed analysis results and recommendations. 【0355】 Step 5: 【0356】 The terminal retrieves analysis results provided by the server and searches for information on laws and past cases using a RAG (Retrieval-Augmented Generation) configuration. This presents the user with legal grounds and similar case studies to support the AI's judgment. The terminal organizes this information and displays it as material for the user to make a decision. 【0357】 Step 6: 【0358】 The server utilizes an emotion engine to interact with users and generate responses that reflect emotional information. For example, it provides a thorough explanation to an anxious user, reassuring them. The feedback obtained as a result of the interaction is analyzed on the server to inform future suggestions and improve the interface. 【0359】 Step 7: 【0360】 The server determines the final care needs assessment level based on multiple perspectives and emotional information, and sends the result to the terminal. Users can review this result through the terminal and input their opinions and feedback. This feedback is compiled by the server and used to improve the system. 【0361】 (Application Example 2) 【0362】 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." 【0363】 In modern care settings, staff are required to process large amounts of information and make quick and accurate decisions in order to appropriately respond to the condition and needs of those receiving care. However, traditional systems have made it difficult to accurately grasp the emotional state of residents and plan care that takes this into account. Furthermore, the psychological burden on staff tends to increase, and staff shortages are a problem. It is necessary to solve these problems and provide a better care environment. 【0364】 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. 【0365】 In this invention, the server includes processing means for recognizing and analyzing emotional states, means for processing data using an artificial intelligence agent finely tuned with specialized knowledge, and means including an information retrieval configuration that acquires laws and regulations and past cases and provides information necessary for decision-making. This makes it possible to propose appropriate care responses that take into account the emotional states of the care recipient and staff. 【0366】 "Emotional state" refers to an individual's internal emotional state, including emotions such as happiness, anxiety, and anger. 【0367】 An "artificial intelligence agent" is a program designed to achieve a specific purpose and operates autonomously using specialized knowledge and algorithms. 【0368】 "Data processing" refers to a series of tasks that involve organizing, analyzing, and converting collected information into a usable format. 【0369】 An "information retrieval configuration" refers to the functions and mechanisms for efficiently searching for and obtaining necessary data and information. 【0370】 "Interactive response" refers to a response mechanism that presents appropriate and relevant information in response to user input. 【0371】 "Data management" refers to the management processes related to the security, storage, retrieval, and deletion of information. 【0372】 "Fine-tuning" is the process of optimizing existing models or systems to meet specific needs and requirements. 【0373】 The system realizing this invention is a complex platform for analyzing emotional states and supporting decision-making in care settings. The server is equipped with dedicated software for emotion recognition and can acquire and analyze emotional data from voice and text input. The server further operates a finely tuned artificial intelligence agent that analyzes the received data based on its expertise to optimize care responses and planning. 【0374】 On the other hand, the terminal is equipped with a user interface and is designed to allow nursing home staff to easily input basic information and health records of those receiving care. The terminal also has a function to search and present laws and past cases in real time based on user operations. This allows staff to quickly and easily obtain relevant information and use it to take appropriate action. 【0375】 Through the coordinated operation of the server and terminal, users can receive interactive responses based on emotional data, enabling less stressful communication with the care recipient. The server then sends the resulting care plan and diagnosis to the terminal, providing direct feedback to the user and facilitating the rapid implementation of appropriate measures. 【0376】 For example, if a person receiving care shows signs of anxiety during communication, the device detects this and sends the information to the server. The server quickly analyzes the information and recommends specific actions to the staff to alleviate the anxiety. 【0377】 An example of a prompt message generated using an AI model is: "Please input the resident's health data and analyze their current emotional state. Then, based on the analysis results, please suggest appropriate care measures." 【0378】 This invention will enable nursing care facilities to provide more humane and efficient care to those receiving care. 【0379】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0380】 Step 1: 【0381】 The user uses a terminal to input basic information and health data of the person being cared for. This information is sent to the server in text format. The entered data is received by the server and organized in preparation for the next analysis step. 【0382】 Step 2: 【0383】 The server analyzes the user's voice data using emotion recognition software. The user's emotional state is analyzed from the voice data, and emotional information such as feelings of reassurance or anxiety is extracted. The resulting emotional data is then used for processing by the artificial intelligence agent. 【0384】 Step 3: 【0385】 The server uses a finely tuned artificial intelligence agent to analyze the input health and emotional data. This process involves data processing and calculations to assess the care recipient's condition and generate appropriate care plans and countermeasures. As a result, care-appropriate guidelines are generated and reported in the next step. 【0386】 Step 4: 【0387】 The server sends appropriate care response measures to the terminal. The terminal displays the guidelines received from the server on the user interface, providing staff with a standard for taking specific actions. The outputted response measures can be used by users when making decisions on-site. 【0388】 Step 5: 【0389】 The terminal accepts user feedback and additional input. This feedback is sent to the server as valuable data for improving the overall system's responsiveness and interface, and is used for analysis in the next cycle. 【0390】 In this way, emotional data can be utilized to enable efficient and humane responses in caregiving settings. 【0391】 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. 【0392】 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. 【0393】 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. 【0394】 [Third Embodiment] 【0395】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0396】 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. 【0397】 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). 【0398】 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. 【0399】 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. 【0400】 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). 【0401】 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. 【0402】 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. 【0403】 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. 【0404】 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. 【0405】 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. 【0406】 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". 【0407】 This invention provides a system that supports efficient and highly accurate decision-making in long-term care certification review committees, and a specific embodiment thereof is described below. 【0408】 First, the user inputs basic information about the person receiving care, medical records, and care history via a terminal. This data is then incorporated into the system as information necessary for care certification. The server receives the data sent from the user and performs standardization and normalization to process it in a unified format. This makes the data suitable for processing by the artificial intelligence agent. 【0409】 Next, the server utilizes finely tuned expert AI agents to perform an initial analysis based on the input data. These AI agents include expert AIs from various fields, such as physician AI, public health nurse AI, and nutritionist AI. These agents analyze the data using their respective expertise and generate hypotheses and diagnoses. 【0410】 Furthermore, the terminal instructs the server to search for information on laws and past cases in response to user requests. This utilizes RAG (Retrieval-Augmented Generation) to acquire and analyze relevant information in real time. The server then incorporates this information into discussions among artificial intelligence agents to support evidence-based decision-making. 【0411】 Multiple artificial intelligence agents engage in discussions on a server using natural language processing technology, integrating opinions from multiple perspectives. The discussions among the AIs involve repeated processes of evaluation, counterargument, and revision, and based on the results, the most appropriate care needs assessment level is determined. 【0412】 Ultimately, the server makes a decision based on the discussion and sends the certification result to the terminal. The user can then review the result on the terminal and, if necessary, enter additional information or provide feedback. 【0413】 This system also takes into consideration the protection of highly confidential and personal information during processing, and the servers strictly manage data in accordance with security policies. This reduces the burden on experts and enables a highly reliable certification process. 【0414】 The following describes the processing flow. 【0415】 Step 1: 【0416】 The user uses a terminal to input necessary data such as the care recipient's basic information, medical records, and care history. The input data is then transmitted to the system in digital format as information necessary for care certification. 【0417】 Step 2: 【0418】 The server receives data sent from users and performs preprocessing to standardize the format. This process also includes detecting and correcting missing or outlier data to improve data quality. 【0419】 Step 3: 【0420】 The server passes the pre-processed data to various specialized artificial intelligence agents. These include AI doctors, AI public health nurses, and AI nutritionists, each of which begins analyzing the data based on their respective expertise. 【0421】 Step 4: 【0422】 In response to requests from terminals, the server utilizes a RAG configuration to retrieve information on laws and past cases from the database. The retrieved information is then organized as evidence necessary for discussions and decision-making. 【0423】 Step 5: 【0424】 The server initiates a discussion session using natural language processing among the artificial intelligence agents. The AIs exchange opinions and engage in discussions to make decisions, reflecting different perspectives. 【0425】 Step 6: 【0426】 The server integrates the views gathered from the discussion and determines the final care needs assessment level based on specific evaluation criteria. The decision-making process reflects a consensus among multiple expert AIs. 【0427】 Step 7: 【0428】 The server sends the determined certification result to the terminal. The user can then review the result through the terminal, enter feedback and additional information into the system as needed, and use this information for the next assessment process. 【0429】 Step 8: 【0430】 The server properly stores and manages the data used during the process. It ensures the protection of highly confidential information and personal data based on the highest level of security measures. 【0431】 (Example 1) 【0432】 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." 【0433】 Traditional care needs assessment processes rely heavily on subjective judgments by various specialists, leading to challenges in consistency and accuracy. Furthermore, there is a need to handle data from diverse sources and establish a swift and secure decision-making process. Therefore, a system is needed that supports objective and efficient decision-making based on expert knowledge. 【0434】 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. 【0435】 In this invention, the server includes means for users to input information through a terminal and convert it into a unified format, means for entrusting specialized knowledge to an optimized intelligent system to perform basic analysis, and means for using an information acquisition configuration that associates relevant laws and past cases and obtains information necessary for decision-making. This makes it possible to reduce the burden on experts and improve the consistency and accuracy of judgments in the care certification process. 【0436】 A "user" is a person who uses a computer terminal to input information into the system and participates in the care certification process. 【0437】 A "terminal" is a computer device used by users to input information and receive information from a system. 【0438】 "Means of converting information into a unified format" refers to the process of standardizing and normalizing input data to create a unified format. 【0439】 A "specialized, optimized intelligent system" refers to an artificial intelligence model that specializes in a particular field, and is finely tuned to suit the fields of medicine and nursing care. 【0440】 "Means of conducting basic analysis" refers to the process by which an optimized intelligent system performs initial analysis based on input data and generates hypotheses and diagnoses. 【0441】 "Means of using information acquisition configurations" refers to techniques for searching relevant laws and past cases to obtain information necessary for decision-making. 【0442】 "Supporting the decision-making of intelligent systems" refers to the process of assisting intelligent systems in making more accurate decisions based on acquired information. 【0443】 "Dialogue" is a form of communication in which multiple intelligent systems exchange information and share opinions with each other. 【0444】 First, the user uses a terminal to input information about the person receiving care. The terminal provides the user's input interface and accepts basic information, medical records, care history, etc. Software such as a browser or dedicated application is often used in this process. 【0445】 The entered information is sent to the server via the terminal. The server receives this data and begins the process of converting it into a unified format. Database management systems and data processing software are used for data standardization and normalization, ensuring consistency in format. 【0446】 Next, the server uses an optimized intelligent system, or fine-tuned AI agent, to perform basic analysis of the data. Machine learning libraries and cloud-based AI platforms are used here. For example, a physician AI assesses a patient's health status based on input medical records, while a public health nurse AI and a nutritionist AI leverage their respective expertise to generate insights into care needs and nutritional management. 【0447】 The terminal requests information from the server regarding laws and past cases. The server utilizes RAG (Retrieval-Augmented Generation) technology to retrieve relevant information from databases and external sources. This information is used as important evidence in AI-driven discussions to support the decision-making process. 【0448】 A concrete example would be a case like, "An 85-year-old male with diabetes and a recent history of hospitalization." When the user enters this information into the terminal, the server's physician AI performs an assessment of the diabetes, and the public health nurse AI and nutritionist AI provide advice on care and nutrition. The server then searches for relevant past cases and conducts discussions among the AIs to derive the optimal care level. 【0449】 An example of a prompt for a generating AI model is: "An 85-year-old male with diabetes and a recent hospitalization history. Begin the initial assessment in the care needs assessment process, and have the AI ​​agent conduct a discussion based on relevant laws and past case information. Derive the optimal care needs assessment level." 【0450】 In this way, the burden on experts can be reduced, and efficient and highly accurate decision-making can be achieved. 【0451】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0452】 Step 1: 【0453】 Users input basic information, medical records, and care history of the person receiving care through a terminal. The entered data is organized within the terminal according to a basic input format and prepared for transmission to the server. Guidance and auto-completion functions are used during the input stage to minimize input errors. 【0454】 Step 2: 【0455】 The terminal sends the data received from the user to the server. The server first verifies the received data, unifying and normalizing its format. In this process, a database management system is used to standardize, for example, date formats and medical terminology. The output is standardized data. 【0456】 Step 3: 【0457】 The server performs initial analysis using AI agents, which are optimized intelligent systems based on standardized data. Specifically, a physician AI assesses health status, a public health nurse AI analyzes the need for care, and a nutritionist AI suggests meals. Using the input data, each agent derives a professional diagnosis or hypothesis, which is then sent to the next discussion process. 【0458】 Step 4: 【0459】 The terminal instructs the server to search for laws and past case information based on user commands. The server uses RAG technology to acquire this information in real time. The information collected from databases and external sources is output as evidence necessary for discussions between AI agents. 【0460】 Step 5: 【0461】 On the server, multiple AI agents discuss the acquired information. Using natural language processing technology, each agent contributes their opinions, and the AIs evaluate, refute, and revise these opinions. Through this process, the optimal care needs assessment level is determined, and the final decision is output. 【0462】 Step 6: 【0463】 The server sends the final decision result to the terminal. The user reviews the result through the terminal and is given the opportunity to provide feedback and additional information as needed. The feedback received will be used to improve future processing. 【0464】 (Application Example 1) 【0465】 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." 【0466】 With the aging of society, demand for care facilities and home care is increasing. However, there is a lack of appropriate means of providing information to reduce the burden on care workers and improve the quality of services. In particular, there is a need for technology that can utilize the knowledge of multiple different experts in real time and provide concrete and appropriate countermeasures immediately on-site. 【0467】 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. 【0468】 In this invention, the server includes means for processing data using an artificial intelligence agent finely tuned with specialized knowledge; means for including an information retrieval configuration that acquires laws and regulations and past cases and provides information necessary for decision-making; and means for providing information to the user in real time via a visual device and visualizing and displaying suggestions. This enables care workers to immediately acquire appropriate countermeasures according to the condition of the person being cared for, thereby improving the efficiency and quality of care services. 【0469】 A "finely tuned artificial intelligence agent" is an artificial intelligence system that has been adjusted to deeply learn information in a specific domain and perform advanced analysis and decision-making based on that learning. 【0470】 An "information retrieval configuration for acquiring laws and past cases" refers to a system component for retrieving necessary information based on legal regulations and relevant past cases and providing it to users. 【0471】 "Means of providing information to users in real time via visual devices" refers to technologies that visually display useful information to users instantly through devices such as smart glasses and head-mounted displays. 【0472】 "Means of visualizing and displaying proposals" refers to methods of visually displaying solutions and guidelines derived by artificial intelligence in a way that is easy for users to understand. 【0473】 A "server" is a central computing system that receives, analyzes, stores, and provides data, and refers to a device that communicates with other devices via a network. 【0474】 The system for realizing this invention consists of a cloud server, a smart device, and an artificial intelligence agent. The server receives data about the care recipient entered by the user and acts as a pacemaker. Smart glasses are primarily envisioned as the terminal used by the user, and these serve as the interface for providing real-time information. 【0475】 The server analyzes the received data using AI agents written in Python. These AI agents include, for example, medical AI, nutrition AI, and nursing AI, and generate appropriate care methods based on the data. A database management system built on the cloud (e.g., MongoDB) also acquires and integrates information on laws and regulations and past care cases. 【0476】 Smart glasses visualize suggestions from a server for the user and display the information through an intuitive interface. To achieve this, each piece of information is converted into a user-friendly format using OCR and natural language processing technologies. Furthermore, the visual device utilizes short-circuit switching technology, enabling rapid information switching. 【0477】 For example, when a care recipient's condition suddenly changes, the smart glasses immediately display first aid procedures and past response examples, allowing caregivers to take swift action based on this information. Furthermore, an example of a prompt message generated using the AI ​​model is, "Please tell me the most appropriate care method for the care recipient's recent health changes. Please include similar past cases and recommendations based on relevant laws and regulations." 【0478】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0479】 Step 1: 【0480】 The server receives basic information and medical history about the care recipient entered by the user via a terminal. This input data is mainly in text format and sensor data, and is standardized and normalized for subsequent processing. This makes the data suitable for analysis by the AI ​​agent. 【0481】 Step 2: 【0482】 The server processes the received data using various AI agents that run on Python. Expert AIs, such as medical AI and nutritional AI, analyze the data within their respective fields and generate appropriate hypotheses and diagnostic results. This process utilizes data mining and pattern recognition techniques. 【0483】 Step 3: 【0484】 The server communicates with the visual device and sends analyzed information to the smart glasses. This includes caregiving suggestions and first-aid procedures. The glasses visualize the information and display it in the user's field of vision. In this step, data is output in a concise and easy-to-read format through the interface with the device. 【0485】 Step 4: 【0486】 The server retrieves laws and past cases from a database and supplements them with relevant information using an AI agent. Users can request this information as needed through the smart glasses interface. Relevant laws and past cases are retrieved in real time through information retrieval based on prompt messages. 【0487】 Step 5: 【0488】 Users provide care based on the information presented. They can take appropriate action immediately by referring to real-time information obtained through the glasses. User feedback and new data are returned to the server, enabling continuous learning and improvement of the system. 【0489】 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. 【0490】 This invention incorporates an emotion engine into a system for supporting effective decision-making in long-term care certification review committees, and a specific embodiment thereof is described below. 【0491】 First, the user inputs basic information and medical records of the person being cared for into the system via a terminal. This input is done through a user-friendly interface. At this time, the emotion engine analyzes parameters such as the user's voice tone and input speed, recognizing the user's emotional state in real time. 【0492】 The server receives data sent by the user and emotional information provided by the emotion engine, and performs data preprocessing. This process includes data standardization as well as metadata about the user's emotional state. This allows the specialized artificial intelligence agent to more accurately understand the user's needs. 【0493】 Next, the server passes the pre-processed data to finely tuned expert AIs for analysis. Each expert AI, such as a doctor, public health nurse, or nutritionist, generates hypotheses and diagnoses based on the input data and emotional information. The generated opinions reflect their respective professional perspectives and serve as a basis for careful decision-making. 【0494】 Furthermore, based on user actions, the server searches for relevant laws and past cases using a RAG (Regional Aggregation) configuration. The server provides interactive responses that take sentiment into account, presenting information to aid user understanding. 【0495】 The emotion engine on the server also takes into account factors related to the user's emotions during discussions between artificial intelligence agents. For example, if a user is feeling anxious, the AI ​​can provide a careful explanation to alleviate that anxiety. 【0496】 Ultimately, the server determines the certification level based on consensus from multiple perspectives and sends the result to the terminal. Users can review the received result and provide feedback and comments. This feedback is analyzed by an emotion engine and used to improve the interface in the future. 【0497】 This system also takes into consideration the analysis and management of emotional data, and the servers are protected by a strict security policy, ensuring thorough data protection. This makes it possible to achieve highly accurate diagnoses while reducing the psychological burden on the user. 【0498】 The following describes the processing flow. 【0499】 Step 1: 【0500】 The user uses a terminal to input necessary data such as the care recipient's basic information, medical records, and care history. Simultaneously, the emotion engine analyzes the user's voice tone and input speed to recognize the user's emotional state in real time. 【0501】 Step 2: 【0502】 The server receives data sent by the user and performs data normalization and standardization. During this process, it adds emotional information analyzed by the emotion engine, generating metadata that takes the user's emotional state into account. 【0503】 Step 3: 【0504】 The server passes pre-processed data to finely tuned artificial intelligence agents, and expert AIs begin data analysis. Doctor AI, public health nurse AI, and nutritionist AI generate opinions based on their respective expertise. In this process, decisions are formed that take into account the user's emotional information. 【0505】 Step 4: 【0506】 In response to requests from the terminal, the server uses a RAG configuration to search for laws and past cases and collect relevant information. The sentiment engine then adjusts the retrieved information before presenting it to the user, generating a response that aids user understanding. 【0507】 Step 5: 【0508】 The server initiates a process in which multiple expert AIs engage in discussions with each other. The emotion engine considers the user's emotions during the discussion, supporting the AI ​​in providing thoughtful explanations, such as those aimed at reducing anxiety. 【0509】 Step 6: 【0510】 The server integrates the results of the discussion with the user's emotional information to determine the final care needs assessment level. High-precision decision-making is achieved by reflecting the consensus of multiple expert AIs and insights from the emotional engine. 【0511】 Step 7: 【0512】 The server sends the determined certification result to the terminal. The user can review the result through the terminal and enter their feedback and additional information. User feedback is again analyzed by the emotion engine and used to improve the user interface for future use. 【0513】 Step 8: 【0514】 The server manages all data under strict security standards. We thoroughly protect acquired emotional data and personal information, maintaining a system that safeguards user privacy. 【0515】 (Example 2) 【0516】 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." 【0517】 In nursing care and medical settings, making swift and accurate decisions based on specialized knowledge is crucial. However, it is not easy to integrate the opinions of multiple experts and make consistent judgments while also considering the emotional state of the service users. Furthermore, it is necessary to ensure the secure management of information and provide accurate information to service users. Therefore, there is a need for a system that comprehensively addresses these challenges. 【0518】 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. 【0519】 In this invention, the server includes means for processing information using an intelligent agent finely tuned with specialized knowledge; means for including an information retrieval configuration that acquires laws and past cases and provides information necessary for decision-making; and means for recognizing the user's emotional state and integrating the analysis results to reflect in decision-making. This enables efficient and accurate decision-making that reflects the user's needs. 【0520】 "Specialized knowledge" refers to having a deep understanding and skills in a particular field, which are used to solve problems and make judgments in that field. 【0521】 A "finely tuned intelligent agent" refers to an artificial intelligence program that has been adjusted to be optimized for a specific task or purpose, and is designed to achieve higher accuracy and efficiency. 【0522】 An "information retrieval configuration" refers to a system for quickly searching for relevant information from large amounts of data and providing it to users. This configuration is used to support efficient decision-making. 【0523】 "Emotional state" refers to a user's psychological or emotional response or condition, and is a factor that influences their behavior and decision-making. 【0524】 "Decision-making based on discussion and integrated conclusions" refers to a decision-making process in which multiple intelligent agents exchange opinions with each other and ultimately make decisions based on a consensus reached. 【0525】 "Data management means" refers to methods and technologies for storing, preserving, and controlling access to information, and is particularly used to protect confidential information and personal information. 【0526】 In this system, users input data such as basic information and medical records of the person receiving care through a terminal. This input is done through a user-friendly interface, prioritizing ease of use. For example, a user might input information such as "70-year-old male, difficulty walking, suspected of having diabetes according to recent diagnosis." At this point, the emotion engine analyzes the user's tone of voice and input speed to recognize their emotional state in real time. 【0527】 The server receives data sent by the user and emotional information provided by the emotion engine, and preprocesses the data. Through a data standardization process, metadata about the user's emotional state is added while maintaining the integrity of the materials, enabling the intelligent agent to more accurately understand the user's needs. This prepares the server to provide more appropriate care plans. 【0528】 Next, the server passes the pre-processed data to finely tuned, specialized intelligent agents for analysis. These intelligent agents evaluate the data from perspectives based on medical knowledge, health, and nutrition, respectively, and generate hypotheses and diagnoses. The results of these specialized perspectives are then used by the care certification review committee to make appropriate decisions regarding the user. 【0529】 Furthermore, in response to user actions, the server searches for relevant laws and past cases using a RAG (Regional Aggregation) configuration and provides relevant information. For example, it can create a prompt message such as "nursing support plan based on specific diagnostic results" and input it into a generating AI model, which can then suggest appropriate diagnostic results as support measures. In this way, a situation is created where users can receive support with peace of mind. 【0530】 The system's emotion engine can design conversations by considering the user's emotional information and reflect that influence in discussions between AI agents. This makes it possible to provide more careful and empathetic explanations and a sense of security when users feel anxious or doubtful. 【0531】 Ultimately, the server determines the agreed-upon care needs assessment level based on all professional perspectives and emotional information, and sends the result to the terminal. This allows the user to review the assessment result and provide feedback as needed. This feedback is analyzed by the emotional engine and used to improve the system in the future. 【0532】 This system incorporates the latest security measures for the analysis and management of emotional data, and the servers are protected under a strict security policy. This makes it possible to reduce the psychological burden on users while enabling accurate diagnosis and effective care support. 【0533】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0534】 Step 1: 【0535】 Users input basic information and medical records of the person receiving care through their device. This input includes name, age, symptoms, and diagnosis. Specifically, the user enters information into a form on the screen and presses the submit button, sending the data to the system. The input data is temporarily stored on the device before being sent to the server. 【0536】 Step 2: 【0537】 The device sends the entered data to the server, where an emotion engine analyzes the user's voice tone and input speed in the background. During this process, the user's input actions (clicks, keyboard typing speed, etc.) are also monitored to generate data that infers their emotional state. This emotional data then influences decision-making in subsequent processes. 【0538】 Step 3: 【0539】 The server receives data sent from the terminal and performs data preprocessing. Preprocessing includes data standardization, noise reduction, and metadata creation of sentiment information. Standardization converts numerical data into a unified format and adjusts for irregularities in text data. This generates a consistent dataset. 【0540】 Step 4: 【0541】 The server passes pre-processed data to fine-tuned intelligent agents, where expert AIs perform analysis. Specifically, a medical AI assesses symptoms, a nutrition AI provides dietary recommendations, and a health AI develops care plans. The analysis results integrate opinions from multiple perspectives. For data processing, a generative AI model based on prompt text is used to generate detailed analysis results and recommendations. 【0542】 Step 5: 【0543】 The terminal retrieves analysis results provided by the server and searches for information on laws and past cases using a RAG (Retrieval-Augmented Generation) configuration. This presents the user with legal grounds and similar case studies to support the AI's judgment. The terminal organizes this information and displays it as material for the user to make a decision. 【0544】 Step 6: 【0545】 The server utilizes an emotion engine to interact with users and generate responses that reflect emotional information. For example, it provides a thorough explanation to an anxious user, reassuring them. The feedback obtained as a result of the interaction is analyzed on the server to inform future suggestions and improve the interface. 【0546】 Step 7: 【0547】 The server determines the final care needs assessment level based on multiple perspectives and emotional information, and sends the result to the terminal. Users can review this result through the terminal and input their opinions and feedback. This feedback is compiled by the server and used to improve the system. 【0548】 (Application Example 2) 【0549】 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." 【0550】 In modern care settings, staff are required to process large amounts of information and make quick and accurate decisions in order to appropriately respond to the condition and needs of those receiving care. However, traditional systems have made it difficult to accurately grasp the emotional state of residents and plan care that takes this into account. Furthermore, the psychological burden on staff tends to increase, and staff shortages are a problem. It is necessary to solve these problems and provide a better care environment. 【0551】 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. 【0552】 In this invention, the server includes processing means for recognizing and analyzing emotional states, means for processing data using an artificial intelligence agent finely tuned with specialized knowledge, and means including an information retrieval configuration that acquires laws and regulations and past cases and provides information necessary for decision-making. This makes it possible to propose appropriate care responses that take into account the emotional states of the care recipient and staff. 【0553】 "Emotional state" refers to an individual's internal emotional state, including emotions such as happiness, anxiety, and anger. 【0554】 An "artificial intelligence agent" is a program designed to achieve a specific purpose and operates autonomously using specialized knowledge and algorithms. 【0555】 "Data processing" refers to a series of tasks that involve organizing, analyzing, and converting collected information into a usable format. 【0556】 An "information retrieval configuration" refers to the functions and mechanisms for efficiently searching for and obtaining necessary data and information. 【0557】 "Interactive response" refers to a response mechanism that presents appropriate and relevant information in response to user input. 【0558】 "Data management" refers to the management processes related to the security, storage, retrieval, and deletion of information. 【0559】 "Fine-tuning" is the process of optimizing existing models or systems to meet specific needs and requirements. 【0560】 The system realizing this invention is a complex platform for analyzing emotional states and supporting decision-making in care settings. The server is equipped with dedicated software for emotion recognition and can acquire and analyze emotional data from voice and text input. The server further operates a finely tuned artificial intelligence agent that analyzes the received data based on its expertise to optimize care responses and planning. 【0561】 On the other hand, the terminal is equipped with a user interface and is designed to allow nursing home staff to easily input basic information and health records of those receiving care. The terminal also has a function to search and present laws and past cases in real time based on user operations. This allows staff to quickly and easily obtain relevant information and use it to take appropriate action. 【0562】 Through the coordinated operation of the server and terminal, users can receive interactive responses based on emotional data, enabling less stressful communication with the care recipient. The server then sends the resulting care plan and diagnosis to the terminal, providing direct feedback to the user and facilitating the rapid implementation of appropriate measures. 【0563】 For example, if a person receiving care shows signs of anxiety during communication, the device detects this and sends the information to the server. The server quickly analyzes the information and recommends specific actions to the staff to alleviate the anxiety. 【0564】 An example of a prompt message generated using an AI model is: "Please input the resident's health data and analyze their current emotional state. Then, based on the analysis results, please suggest appropriate care measures." 【0565】 This invention will enable nursing care facilities to provide more humane and efficient care to those receiving care. 【0566】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0567】 Step 1: 【0568】 The user uses a terminal to input basic information and health data of the person being cared for. This information is sent to the server in text format. The entered data is received by the server and organized in preparation for the next analysis step. 【0569】 Step 2: 【0570】 The server analyzes the user's voice data using emotion recognition software. The user's emotional state is analyzed from the voice data, and emotional information such as feelings of reassurance or anxiety is extracted. The resulting emotional data is then used for processing by the artificial intelligence agent. 【0571】 Step 3: 【0572】 The server uses a finely tuned artificial intelligence agent to analyze the input health and emotional data. This process involves data processing and calculations to assess the care recipient's condition and generate appropriate care plans and countermeasures. As a result, care-appropriate guidelines are generated and reported in the next step. 【0573】 Step 4: 【0574】 The server sends appropriate care response measures to the terminal. The terminal displays the guidelines received from the server on the user interface, providing staff with a standard for taking specific actions. The outputted response measures can be used by users when making decisions on-site. 【0575】 Step 5: 【0576】 The terminal accepts user feedback and additional input. This feedback is sent to the server as valuable data for improving the overall system's responsiveness and interface, and is used for analysis in the next cycle. 【0577】 In this way, emotional data can be utilized to enable efficient and humane responses in caregiving settings. 【0578】 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. 【0579】 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. 【0580】 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. 【0581】 [Fourth Embodiment] 【0582】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0583】 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. 【0584】 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). 【0585】 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. 【0586】 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. 【0587】 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). 【0588】 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. 【0589】 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. 【0590】 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. 【0591】 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. 【0592】 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. 【0593】 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. 【0594】 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". 【0595】 This invention provides a system that supports efficient and highly accurate decision-making in long-term care certification review committees, and a specific embodiment thereof is described below. 【0596】 First, the user inputs basic information about the person receiving care, medical records, and care history via a terminal. This data is then incorporated into the system as information necessary for care certification. The server receives the data sent from the user and performs standardization and normalization to process it in a unified format. This makes the data suitable for processing by the artificial intelligence agent. 【0597】 Next, the server utilizes finely tuned expert AI agents to perform an initial analysis based on the input data. These AI agents include expert AIs from various fields, such as physician AI, public health nurse AI, and nutritionist AI. These agents analyze the data using their respective expertise and generate hypotheses and diagnoses. 【0598】 Furthermore, the terminal instructs the server to search for information on laws and past cases in response to user requests. This utilizes RAG (Retrieval-Augmented Generation) to acquire and analyze relevant information in real time. The server then incorporates this information into discussions among artificial intelligence agents to support evidence-based decision-making. 【0599】 Multiple artificial intelligence agents engage in discussions on a server using natural language processing technology, integrating opinions from multiple perspectives. The discussions among the AIs involve repeated processes of evaluation, counterargument, and revision, and based on the results, the most appropriate care needs assessment level is determined. 【0600】 Ultimately, the server makes a decision based on the discussion and sends the certification result to the terminal. The user can then review the result on the terminal and, if necessary, enter additional information or provide feedback. 【0601】 This system also takes into consideration the protection of highly confidential and personal information during processing, and the servers strictly manage data in accordance with security policies. This reduces the burden on experts and enables a highly reliable certification process. 【0602】 The following describes the processing flow. 【0603】 Step 1: 【0604】 The user uses a terminal to input necessary data such as the care recipient's basic information, medical records, and care history. The input data is then transmitted to the system in digital format as information necessary for care certification. 【0605】 Step 2: 【0606】 The server receives data sent from users and performs preprocessing to standardize the format. This process also includes detecting and correcting missing or outlier data to improve data quality. 【0607】 Step 3: 【0608】 The server passes the pre-processed data to various specialized artificial intelligence agents. These include AI doctors, AI public health nurses, and AI nutritionists, each of which begins analyzing the data based on their respective expertise. 【0609】 Step 4: 【0610】 In response to requests from terminals, the server utilizes a RAG configuration to retrieve information on laws and past cases from the database. The retrieved information is then organized as evidence necessary for discussions and decision-making. 【0611】 Step 5: 【0612】 The server initiates a discussion session using natural language processing among the artificial intelligence agents. The AIs exchange opinions and engage in discussions to make decisions, reflecting different perspectives. 【0613】 Step 6: 【0614】 The server integrates the views gathered from the discussion and determines the final care needs assessment level based on specific evaluation criteria. The decision-making process reflects a consensus among multiple expert AIs. 【0615】 Step 7: 【0616】 The server sends the determined certification result to the terminal. The user can then review the result through the terminal, enter feedback and additional information into the system as needed, and use this information for the next assessment process. 【0617】 Step 8: 【0618】 The server properly stores and manages the data used during the process. It ensures the protection of highly confidential information and personal data based on the highest level of security measures. 【0619】 (Example 1) 【0620】 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". 【0621】 Traditional care needs assessment processes rely heavily on subjective judgments by various specialists, leading to challenges in consistency and accuracy. Furthermore, there is a need to handle data from diverse sources and establish a swift and secure decision-making process. Therefore, a system is needed that supports objective and efficient decision-making based on expert knowledge. 【0622】 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. 【0623】 In this invention, the server includes means for users to input information through a terminal and convert it into a unified format, means for entrusting specialized knowledge to an optimized intelligent system to perform basic analysis, and means for using an information acquisition configuration that associates relevant laws and past cases and obtains information necessary for decision-making. This makes it possible to reduce the burden on experts and improve the consistency and accuracy of judgments in the care certification process. 【0624】 A "user" is a person who uses a computer terminal to input information into the system and participates in the care certification process. 【0625】 A "terminal" is a computer device used by users to input information and receive information from a system. 【0626】 "Means of converting information into a unified format" refers to the process of standardizing and normalizing input data to create a unified format. 【0627】 A "specialized, optimized intelligent system" refers to an artificial intelligence model that specializes in a particular field, and is finely tuned to suit the fields of medicine and nursing care. 【0628】 "Means of conducting basic analysis" refers to the process by which an optimized intelligent system performs initial analysis based on input data and generates hypotheses and diagnoses. 【0629】 "Means of using information acquisition configurations" refers to techniques for searching relevant laws and past cases to obtain information necessary for decision-making. 【0630】 "Supporting the decision-making of intelligent systems" refers to the process of assisting intelligent systems in making more accurate decisions based on acquired information. 【0631】 "Dialogue" is a form of communication in which multiple intelligent systems exchange information and share opinions with each other. 【0632】 First, the user uses a terminal to input information about the person receiving care. The terminal provides the user's input interface and accepts basic information, medical records, care history, etc. Software such as a browser or dedicated application is often used in this process. 【0633】 The entered information is sent to the server via the terminal. The server receives this data and begins the process of converting it into a unified format. Database management systems and data processing software are used for data standardization and normalization, ensuring consistency in format. 【0634】 Next, the server uses an optimized intelligent system, or fine-tuned AI agent, to perform basic analysis of the data. Machine learning libraries and cloud-based AI platforms are used here. For example, a physician AI assesses a patient's health status based on input medical records, while a public health nurse AI and a nutritionist AI leverage their respective expertise to generate insights into care needs and nutritional management. 【0635】 The terminal requests information from the server regarding laws and past cases. The server utilizes RAG (Retrieval-Augmented Generation) technology to retrieve relevant information from databases and external sources. This information is used as important evidence in AI-driven discussions to support the decision-making process. 【0636】 A concrete example would be a case like, "An 85-year-old male with diabetes and a recent history of hospitalization." When the user enters this information into the terminal, the server's physician AI performs an assessment of the diabetes, and the public health nurse AI and nutritionist AI provide advice on care and nutrition. The server then searches for relevant past cases and conducts discussions among the AIs to derive the optimal care level. 【0637】 An example of a prompt for a generating AI model is: "An 85-year-old male with diabetes and a recent hospitalization history. Begin the initial assessment in the care needs assessment process, and have the AI ​​agent conduct a discussion based on relevant laws and past case information. Derive the optimal care needs assessment level." 【0638】 In this way, the burden on experts can be reduced, and efficient and highly accurate decision-making can be achieved. 【0639】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0640】 Step 1: 【0641】 Users input basic information, medical records, and care history of the person receiving care through a terminal. The entered data is organized within the terminal according to a basic input format and prepared for transmission to the server. Guidance and auto-completion functions are used during the input stage to minimize input errors. 【0642】 Step 2: 【0643】 The terminal sends the data received from the user to the server. The server first verifies the received data, unifying and normalizing its format. In this process, a database management system is used to standardize, for example, date formats and medical terminology. The output is standardized data. 【0644】 Step 3: 【0645】 The server performs initial analysis using AI agents, which are optimized intelligent systems based on standardized data. Specifically, a physician AI assesses health status, a public health nurse AI analyzes the need for care, and a nutritionist AI suggests meals. Using the input data, each agent derives a professional diagnosis or hypothesis, which is then sent to the next discussion process. 【0646】 Step 4: 【0647】 The terminal instructs the server to search for laws and past case information based on user commands. The server uses RAG technology to acquire this information in real time. The information collected from databases and external sources is output as evidence necessary for discussions between AI agents. 【0648】 Step 5: 【0649】 On the server, multiple AI agents discuss the acquired information. Using natural language processing technology, each agent contributes their opinions, and the AIs evaluate, refute, and revise these opinions. Through this process, the optimal care needs assessment level is determined, and the final decision is output. 【0650】 Step 6: 【0651】 The server sends the final decision result to the terminal. The user reviews the result through the terminal and is given the opportunity to provide feedback and additional information as needed. The feedback received will be used to improve future processing. 【0652】 (Application Example 1) 【0653】 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". 【0654】 With the aging of society, demand for care facilities and home care is increasing. However, there is a lack of appropriate means of providing information to reduce the burden on care workers and improve the quality of services. In particular, there is a need for technology that can utilize the knowledge of multiple different experts in real time and provide concrete and appropriate countermeasures immediately on-site. 【0655】 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. 【0656】 In this invention, the server includes means for processing data using an artificial intelligence agent finely tuned with specialized knowledge; means for including an information retrieval configuration that acquires laws and regulations and past cases and provides information necessary for decision-making; and means for providing information to the user in real time via a visual device and visualizing and displaying suggestions. This enables care workers to immediately acquire appropriate countermeasures according to the condition of the person being cared for, thereby improving the efficiency and quality of care services. 【0657】 A "finely tuned artificial intelligence agent" is an artificial intelligence system that has been adjusted to deeply learn information in a specific domain and perform advanced analysis and decision-making based on that learning. 【0658】 An "information retrieval configuration for acquiring laws and past cases" refers to a system component for retrieving necessary information based on legal regulations and relevant past cases and providing it to users. 【0659】 "Means of providing information to users in real time via visual devices" refers to technologies that visually display useful information to users instantly through devices such as smart glasses and head-mounted displays. 【0660】 "Means of visualizing and displaying proposals" refers to methods of visually displaying solutions and guidelines derived by artificial intelligence in a way that is easy for users to understand. 【0661】 A "server" is a central computing system that receives, analyzes, stores, and provides data, and refers to a device that communicates with other devices via a network. 【0662】 The system for realizing this invention consists of a cloud server, a smart device, and an artificial intelligence agent. The server receives data about the care recipient entered by the user and acts as a pacemaker. Smart glasses are primarily envisioned as the terminal used by the user, and these serve as the interface for providing real-time information. 【0663】 The server analyzes the received data using AI agents written in Python. These AI agents include, for example, medical AI, nutrition AI, and nursing AI, and generate appropriate care methods based on the data. A database management system built on the cloud (e.g., MongoDB) also acquires and integrates information on laws and regulations and past care cases. 【0664】 Smart glasses visualize suggestions from a server for the user and display the information through an intuitive interface. To achieve this, each piece of information is converted into a user-friendly format using OCR and natural language processing technologies. Furthermore, the visual device utilizes short-circuit switching technology, enabling rapid information switching. 【0665】 For example, when a care recipient's condition suddenly changes, the smart glasses immediately display first aid procedures and past response examples, allowing caregivers to take swift action based on this information. Furthermore, an example of a prompt message generated using the AI ​​model is, "Please tell me the most appropriate care method for the care recipient's recent health changes. Please include similar past cases and recommendations based on relevant laws and regulations." 【0666】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0667】 Step 1: 【0668】 The server receives basic information and medical history about the care recipient entered by the user via a terminal. This input data is mainly in text format and sensor data, and is standardized and normalized for subsequent processing. This makes the data suitable for analysis by the AI ​​agent. 【0669】 Step 2: 【0670】 The server processes the received data using various AI agents that run on Python. Expert AIs, such as medical AI and nutritional AI, analyze the data within their respective fields and generate appropriate hypotheses and diagnostic results. This process utilizes data mining and pattern recognition techniques. 【0671】 Step 3: 【0672】 The server communicates with the visual device and sends analyzed information to the smart glasses. This includes caregiving suggestions and first-aid procedures. The glasses visualize the information and display it in the user's field of vision. In this step, data is output in a concise and easy-to-read format through the interface with the device. 【0673】 Step 4: 【0674】 The server retrieves laws and past cases from a database and supplements them with relevant information using an AI agent. Users can request this information as needed through the smart glasses interface. Relevant laws and past cases are retrieved in real time through information retrieval based on prompt messages. 【0675】 Step 5: 【0676】 Users provide care based on the information presented. They can take appropriate action immediately by referring to real-time information obtained through the glasses. User feedback and new data are returned to the server, enabling continuous learning and improvement of the system. 【0677】 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. 【0678】 This invention incorporates an emotion engine into a system for supporting effective decision-making in long-term care certification review committees, and a specific embodiment thereof is described below. 【0679】 First, the user inputs basic information and medical records of the person being cared for into the system via a terminal. This input is done through a user-friendly interface. At this time, the emotion engine analyzes parameters such as the user's voice tone and input speed, recognizing the user's emotional state in real time. 【0680】 The server receives data sent by the user and emotional information provided by the emotion engine, and performs data preprocessing. This process includes data standardization as well as metadata about the user's emotional state. This allows the specialized artificial intelligence agent to more accurately understand the user's needs. 【0681】 Next, the server passes the pre-processed data to finely tuned expert AIs for analysis. Each expert AI, such as a doctor, public health nurse, or nutritionist, generates hypotheses and diagnoses based on the input data and emotional information. The generated opinions reflect their respective professional perspectives and serve as a basis for careful decision-making. 【0682】 Furthermore, based on user actions, the server searches for relevant laws and past cases using a RAG (Regional Aggregation) configuration. The server provides interactive responses that take sentiment into account, presenting information to aid user understanding. 【0683】 The emotion engine on the server also takes into account factors related to the user's emotions during discussions between artificial intelligence agents. For example, if a user is feeling anxious, the AI ​​can provide a careful explanation to alleviate that anxiety. 【0684】 Ultimately, the server determines the certification level based on consensus from multiple perspectives and sends the result to the terminal. Users can review the received result and provide feedback and comments. This feedback is analyzed by an emotion engine and used to improve the interface in the future. 【0685】 This system also takes into consideration the analysis and management of emotional data, and the servers are protected by a strict security policy, ensuring thorough data protection. This makes it possible to achieve highly accurate diagnoses while reducing the psychological burden on the user. 【0686】 The following describes the processing flow. 【0687】 Step 1: 【0688】 The user uses a terminal to input necessary data such as the care recipient's basic information, medical records, and care history. Simultaneously, the emotion engine analyzes the user's voice tone and input speed to recognize the user's emotional state in real time. 【0689】 Step 2: 【0690】 The server receives data sent by the user and performs data normalization and standardization. During this process, it adds emotional information analyzed by the emotion engine, generating metadata that takes the user's emotional state into account. 【0691】 Step 3: 【0692】 The server passes pre-processed data to finely tuned artificial intelligence agents, and expert AIs begin data analysis. Doctor AI, public health nurse AI, and nutritionist AI generate opinions based on their respective expertise. In this process, decisions are formed that take into account the user's emotional information. 【0693】 Step 4: 【0694】 In response to requests from the terminal, the server uses a RAG configuration to search for laws and past cases and collect relevant information. The sentiment engine then adjusts the retrieved information before presenting it to the user, generating a response that aids user understanding. 【0695】 Step 5: 【0696】 The server initiates a process in which multiple expert AIs engage in discussions with each other. The emotion engine considers the user's emotions during the discussion, supporting the AI ​​in providing thoughtful explanations, such as those aimed at reducing anxiety. 【0697】 Step 6: 【0698】 The server integrates the results of the discussion with the user's emotional information to determine the final care needs assessment level. High-precision decision-making is achieved by reflecting the consensus of multiple expert AIs and insights from the emotional engine. 【0699】 Step 7: 【0700】 The server sends the determined certification result to the terminal. The user can review the result through the terminal and enter their feedback and additional information. User feedback is again analyzed by the emotion engine and used to improve the user interface for future use. 【0701】 Step 8: 【0702】 The server manages all data under strict security standards. We thoroughly protect acquired emotional data and personal information, maintaining a system that safeguards user privacy. 【0703】 (Example 2) 【0704】 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". 【0705】 In nursing care and medical settings, making swift and accurate decisions based on specialized knowledge is crucial. However, it is not easy to integrate the opinions of multiple experts and make consistent judgments while also considering the emotional state of the service users. Furthermore, it is necessary to ensure the secure management of information and provide accurate information to service users. Therefore, there is a need for a system that comprehensively addresses these challenges. 【0706】 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. 【0707】 In this invention, the server includes means for processing information using an intelligent agent finely tuned with specialized knowledge; means for including an information retrieval configuration that acquires laws and past cases and provides information necessary for decision-making; and means for recognizing the user's emotional state and integrating the analysis results to reflect in decision-making. This enables efficient and accurate decision-making that reflects the user's needs. 【0708】 "Specialized knowledge" refers to having a deep understanding and skills in a particular field, which are used to solve problems and make judgments in that field. 【0709】 A "finely tuned intelligent agent" refers to an artificial intelligence program that has been adjusted to be optimized for a specific task or purpose, and is designed to achieve higher accuracy and efficiency. 【0710】 An "information retrieval configuration" refers to a system for quickly searching for relevant information from large amounts of data and providing it to users. This configuration is used to support efficient decision-making. 【0711】 "Emotional state" refers to a user's psychological or emotional response or condition, and is a factor that influences their behavior and decision-making. 【0712】 "Decision-making based on discussion and integrated conclusions" refers to a decision-making process in which multiple intelligent agents exchange opinions with each other and ultimately make decisions based on a consensus reached. 【0713】 "Data management means" refers to methods and technologies for storing, preserving, and controlling access to information, and is particularly used to protect confidential information and personal information. 【0714】 In this system, users input data such as basic information and medical records of the person receiving care through a terminal. This input is done through a user-friendly interface, prioritizing ease of use. For example, a user might input information such as "70-year-old male, difficulty walking, suspected of having diabetes according to recent diagnosis." At this point, the emotion engine analyzes the user's tone of voice and input speed to recognize their emotional state in real time. 【0715】 The server receives data sent by the user and emotional information provided by the emotion engine, and preprocesses the data. Through a data standardization process, metadata about the user's emotional state is added while maintaining the integrity of the materials, enabling the intelligent agent to more accurately understand the user's needs. This prepares the server to provide more appropriate care plans. 【0716】 Next, the server passes the pre-processed data to finely tuned, specialized intelligent agents for analysis. These intelligent agents evaluate the data from perspectives based on medical knowledge, health, and nutrition, respectively, and generate hypotheses and diagnoses. The results of these specialized perspectives are then used by the care certification review committee to make appropriate decisions regarding the user. 【0717】 Furthermore, in response to user actions, the server searches for relevant laws and past cases using a RAG (Regional Aggregation) configuration and provides relevant information. For example, it can create a prompt message such as "nursing support plan based on specific diagnostic results" and input it into a generating AI model, which can then suggest appropriate diagnostic results as support measures. In this way, a situation is created where users can receive support with peace of mind. 【0718】 The system's emotion engine can design conversations by considering the user's emotional information and reflect that influence in discussions between AI agents. This makes it possible to provide more careful and empathetic explanations and a sense of security when users feel anxious or doubtful. 【0719】 Ultimately, the server determines the agreed-upon care needs assessment level based on all professional perspectives and emotional information, and sends the result to the terminal. This allows the user to review the assessment result and provide feedback as needed. This feedback is analyzed by the emotional engine and used to improve the system in the future. 【0720】 This system incorporates the latest security measures for the analysis and management of emotional data, and the servers are protected under a strict security policy. This makes it possible to reduce the psychological burden on users while enabling accurate diagnosis and effective care support. 【0721】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0722】 Step 1: 【0723】 Users input basic information and medical records of the person receiving care through their device. This input includes name, age, symptoms, and diagnosis. Specifically, the user enters information into a form on the screen and presses the submit button, sending the data to the system. The input data is temporarily stored on the device before being sent to the server. 【0724】 Step 2: 【0725】 The device sends the entered data to the server, where an emotion engine analyzes the user's voice tone and input speed in the background. During this process, the user's input actions (clicks, keyboard typing speed, etc.) are also monitored to generate data that infers their emotional state. This emotional data then influences decision-making in subsequent processes. 【0726】 Step 3: 【0727】 The server receives data sent from the terminal and performs data preprocessing. Preprocessing includes data standardization, noise reduction, and metadata creation of sentiment information. Standardization converts numerical data into a unified format and adjusts for irregularities in text data. This generates a consistent dataset. 【0728】 Step 4: 【0729】 The server passes pre-processed data to fine-tuned intelligent agents, where expert AIs perform analysis. Specifically, a medical AI assesses symptoms, a nutrition AI provides dietary recommendations, and a health AI develops care plans. The analysis results integrate opinions from multiple perspectives. For data processing, a generative AI model based on prompt text is used to generate detailed analysis results and recommendations. 【0730】 Step 5: 【0731】 The terminal retrieves analysis results provided by the server and searches for information on laws and past cases using a RAG (Retrieval-Augmented Generation) configuration. This presents the user with legal grounds and similar case studies to support the AI's judgment. The terminal organizes this information and displays it as material for the user to make a decision. 【0732】 Step 6: 【0733】 The server utilizes an emotion engine to interact with users and generate responses that reflect emotional information. For example, it provides a thorough explanation to an anxious user, reassuring them. The feedback obtained as a result of the interaction is analyzed on the server to inform future suggestions and improve the interface. 【0734】 Step 7: 【0735】 The server determines the final care needs assessment level based on multiple perspectives and emotional information, and sends the result to the terminal. Users can review this result through the terminal and input their opinions and feedback. This feedback is compiled by the server and used to improve the system. 【0736】 (Application Example 2) 【0737】 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". 【0738】 In modern care settings, staff are required to process large amounts of information and make quick and accurate decisions in order to appropriately respond to the condition and needs of those receiving care. However, traditional systems have made it difficult to accurately grasp the emotional state of residents and plan care that takes this into account. Furthermore, the psychological burden on staff tends to increase, and staff shortages are a problem. It is necessary to solve these problems and provide a better care environment. 【0739】 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. 【0740】 In this invention, the server includes processing means for recognizing and analyzing emotional states, means for processing data using an artificial intelligence agent finely tuned with specialized knowledge, and means including an information retrieval configuration that acquires laws and regulations and past cases and provides information necessary for decision-making. This makes it possible to propose appropriate care responses that take into account the emotional states of the care recipient and staff. 【0741】 "Emotional state" refers to an individual's internal emotional state, including emotions such as happiness, anxiety, and anger. 【0742】 An "artificial intelligence agent" is a program designed to achieve a specific purpose and operates autonomously using specialized knowledge and algorithms. 【0743】 "Data processing" refers to a series of tasks that involve organizing, analyzing, and converting collected information into a usable format. 【0744】 An "information retrieval configuration" refers to the functions and mechanisms for efficiently searching for and obtaining necessary data and information. 【0745】 "Interactive response" refers to a response mechanism that presents appropriate and relevant information in response to user input. 【0746】 "Data management" refers to the management processes related to the security, storage, retrieval, and deletion of information. 【0747】 "Fine-tuning" is the process of optimizing existing models or systems to meet specific needs and requirements. 【0748】 The system realizing this invention is a complex platform for analyzing emotional states and supporting decision-making in care settings. The server is equipped with dedicated software for emotion recognition and can acquire and analyze emotional data from voice and text input. The server further operates a finely tuned artificial intelligence agent that analyzes the received data based on its expertise to optimize care responses and planning. 【0749】 On the other hand, the terminal is equipped with a user interface and is designed to allow nursing home staff to easily input basic information and health records of those receiving care. The terminal also has a function to search and present laws and past cases in real time based on user operations. This allows staff to quickly and easily obtain relevant information and use it to take appropriate action. 【0750】 Through the coordinated operation of the server and terminal, users can receive interactive responses based on emotional data, enabling less stressful communication with the care recipient. The server then sends the resulting care plan and diagnosis to the terminal, providing direct feedback to the user and facilitating the rapid implementation of appropriate measures. 【0751】 For example, if a person receiving care shows signs of anxiety during communication, the device detects this and sends the information to the server. The server quickly analyzes the information and recommends specific actions to the staff to alleviate the anxiety. 【0752】 An example of a prompt message generated using an AI model is: "Please input the resident's health data and analyze their current emotional state. Then, based on the analysis results, please suggest appropriate care measures." 【0753】 This invention will enable nursing care facilities to provide more humane and efficient care to those receiving care. 【0754】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0755】 Step 1: 【0756】 The user uses a terminal to input basic information and health data of the person being cared for. This information is sent to the server in text format. The entered data is received by the server and organized in preparation for the next analysis step. 【0757】 Step 2: 【0758】 The server analyzes the user's voice data using emotion recognition software. The user's emotional state is analyzed from the voice data, and emotional information such as feelings of reassurance or anxiety is extracted. The resulting emotional data is then used for processing by the artificial intelligence agent. 【0759】 Step 3: 【0760】 The server uses a finely tuned artificial intelligence agent to analyze the input health and emotional data. This process involves data processing and calculations to assess the care recipient's condition and generate appropriate care plans and countermeasures. As a result, care-appropriate guidelines are generated and reported in the next step. 【0761】 Step 4: 【0762】 The server sends appropriate care response measures to the terminal. The terminal displays the guidelines received from the server on the user interface, providing staff with a standard for taking specific actions. The outputted response measures can be used by users when making decisions on-site. 【0763】 Step 5: 【0764】 The terminal accepts user feedback and additional input. This feedback is sent to the server as valuable data for improving the overall system's responsiveness and interface, and is used for analysis in the next cycle. 【0765】 In this way, emotional data can be utilized to enable efficient and humane responses in caregiving settings. 【0766】 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. 【0767】 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. 【0768】 In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0769】 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. 【0770】 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. 【0771】 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. 【0772】 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. 【0773】 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. 【0774】 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." 【0775】 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. 【0776】 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. 【0777】 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. 【0778】 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. 【0779】 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. 【0780】 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. 【0781】 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. 【0782】 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. 【0783】 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. 【0784】 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. 【0785】 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. 【0786】 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. 【0787】 The following is further disclosed regarding the embodiments described above. 【0788】 (Claim 1) 【0789】 A means of processing data using an artificial intelligence agent finely tuned with specialized knowledge, 【0790】 A means including an information retrieval configuration that obtains laws and regulations and past cases and provides information necessary for decision-making, 【0791】 A means by which multiple artificial intelligence agents engage in discussions with each other and make decisions based on the integrated results, 【0792】 Data management methods for managing highly confidential information and protecting personal information, 【0793】 A system that includes this. 【0794】 (Claim 2) 【0795】 The system according to claim 1, in which each artificial intelligence agent, finely tuned with specialized knowledge, generates opinions using medical information and nursing care data and engages in discussions in natural language. 【0796】 (Claim 3) 【0797】 The system according to claim 1, which searches for laws and regulations and case examples in real time and supports the decision-making of an artificial intelligence agent based on the acquired information. 【0798】 "Example 1" 【0799】 (Claim 1) 【0800】 A means by which users input information through a terminal and convert it into a unified format, 【0801】 A means of performing basic analysis by entrusting specialized knowledge to an optimized intelligent system, 【0802】 A means of obtaining information necessary for decision-making by linking relevant laws and regulations and past cases, 【0803】 A means by which multiple intelligent systems interact with each other and derive integrated results from diverse perspectives, 【0804】 A means of providing an information management configuration for storing highly confidential information and securely protecting personal information, 【0805】 A system that includes this. 【0806】 (Claim 2) 【0807】 The system according to claim 1, in which each optimized intelligent system generates opinions using health information and support data, and engages in dialogue using language technology. 【0808】 (Claim 3) 【0809】 The system according to claim 1, which continuously acquires relevant laws and regulations and case examples, and supports the intelligent system's decision-making based on the information obtained. 【0810】 "Application Example 1" 【0811】 (Claim 1) 【0812】 A means of processing data using an artificial intelligence agent finely tuned with specialized knowledge, 【0813】 A means including an information retrieval configuration that obtains laws and regulations and past cases and provides information necessary for decision-making, 【0814】 A means by which multiple artificial intelligence agents engage in discussions with each other and make decisions based on the integrated results, 【0815】 Data management methods for managing highly confidential information and protecting personal information, 【0816】 A means of providing information to users in real time via a visual device and visualizing and displaying proposals, 【0817】 A system that includes this. 【0818】 (Claim 2) 【0819】 The system according to claim 1, in which each artificial intelligence agent, finely tuned with specialized knowledge, generates opinions using medical information and nursing care data and engages in discussions in natural language. 【0820】 (Claim 3) 【0821】 The system according to claim 1, which searches for laws and regulations and case examples in real time, supports the judgment of an artificial intelligence agent based on the acquired information, and provides information to a visual device. 【0822】 "Example 2 of combining an emotion engine" 【0823】 (Claim 1) 【0824】 A means of processing information using a finely tuned intelligent agent with specialized knowledge, 【0825】 A means including an information retrieval configuration that obtains laws and regulations and past cases and provides information necessary for decision-making, 【0826】 A means of recognizing the emotional state of users, integrating the analysis results, and reflecting them in decision-making. 【0827】 A means by which multiple intelligent agents engage in discussions with each other and make decisions based on integrated conclusions, 【0828】 Data management means for managing confidential information and protecting personal information, 【0829】 A system that includes this. 【0830】 (Claim 2) 【0831】 The system according to claim 1, in which each intelligent agent, finely tuned with specialized knowledge, generates opinions using medical information and nursing care data and engages in discussions in natural language. 【0832】 (Claim 3) 【0833】 The system according to claim 1, which searches for laws and regulations and case examples in real time and supports the decision-making of an intelligent agent based on the acquired information. 【0834】 "Application example 2 when combining with an emotional engine" 【0835】 (Claim 1) 【0836】 A processing means for recognizing and analyzing emotional states, 【0837】 A means of processing data using an artificial intelligence agent finely tuned with specialized knowledge, 【0838】 A means including an information retrieval configuration that obtains laws and regulations and past cases and provides information necessary for decision-making, 【0839】 A means by which multiple artificial intelligence agents engage in discussions with each other and make decisions based on the integrated results, 【0840】 A means for generating interactive responses to users based on emotional information, 【0841】 Data management methods for managing highly confidential information and protecting personal information, 【0842】 A system that includes this. 【0843】 (Claim 2) 【0844】 The system according to claim 1, which uses artificial intelligence agents to improve opinions and countermeasures by recognizing and analyzing emotional states. 【0845】 (Claim 3) 【0846】 The system according to claim 1, which searches for laws and regulations and case examples in real time and assists in making judgments that take into account emotional information based on the acquired information. [Explanation of symbols] 【0847】 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

[Claim 1] A means of processing data using an artificial intelligence agent finely tuned with specialized knowledge, A means including an information retrieval configuration that obtains laws and regulations and past cases and provides information necessary for decision-making, A means by which multiple artificial intelligence agents engage in discussions with each other and make decisions based on the integrated results, Data management methods for managing highly confidential information and protecting personal information, A system that includes this. [Claim 2] The system according to claim 1, in which each artificial intelligence agent, finely tuned with specialized knowledge, generates opinions using medical information and nursing care data and engages in discussions in natural language. [Claim 3] The system according to claim 1, which searches for laws and regulations and case examples in real time and supports the judgment of an artificial intelligence agent based on the acquired information.

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