system

Abstract

We provide the system. [Solution] A system that provides an artificial intelligence assistant specifically for managing residential facilities, A natural language processing means for receiving natural language input from a user and analyzing said input, Information acquisition means that acquires relevant information from a rule database based on the analyzed information, A response generation means that formats the acquired information according to the user's language and generates a response, A response transmission means for sending the generated response to the user, 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, the method including 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】 [[ID=३३]] 【0004】 In residential facilities such as condominiums, lack of knowledge regarding management operations and the need for multilingual support due to internationalization pose problems. When residents change, not only is it difficult to inherit management know-how, but communication barriers due to language and cultural differences are likely to occur. Also, in the standard services provided by management companies, the problem is that they do not adequately address the individual needs of residents. There is a need for a new solution to solve such problems and operate the management of residential facilities efficiently and smoothly. 【Means for Solving the Problems】 【0005】 This invention solves the above problems by providing a system that uses an artificial intelligence assistant specifically designed for the management of residential facilities. Specifically, it includes means for analyzing natural language input from the user and obtaining necessary information from a rules database. Furthermore, it generates a response in a multilingual format that is optimal for the user based on the obtained information, and sends it to the user quickly, thereby realizing smooth communication that transcends language barriers. In addition, it compensates for the problem of insufficient knowledge in management tasks by accumulating a history of interactions with the user and improving the accuracy of responses in subsequent interactions. Moreover, it facilitates communication between different languages ​​using a language translation function, making it possible to accommodate international residents. 【0006】 "Residential facilities" refer to buildings or areas used by people to carry out their daily lives, and mainly include houses and apartment buildings. 【0007】 An "artificial intelligence assistant" is software programmed for specific tasks or purposes, and is a system that utilizes artificial intelligence technology to provide information and services that meet the user's needs. 【0008】 "Natural language processing" is a technology that enables computers to understand and process human language, and it includes processes such as text analysis, language identification, and interpretation of intent. 【0009】 A "rules database" is a collection of information that systematically stores and makes searchable the rules and guidelines related to a specific organization or facility. 【0010】 "Response generation" is the process of generating appropriate and relevant answers based on user input, and communicating them to the user in a structured and appropriate language and format. 【0011】 "Data storage" refers to the act of saving user interactions and various types of information, and recording them for future reference and analysis. 【0012】 "Translation methods" refer to technologies and processes that convert text or audio between different languages, transforming information into a form that can be understood in another language. [Brief explanation of the drawing] 【0013】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] 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]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined. 【Embodiments for Carrying Out the Invention】 【0014】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0015】 First, the terms used in the following description will be explained. 【0016】 In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0017】 In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0018】 In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0019】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0020】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0021】 [First Embodiment] 【0022】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0023】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0024】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0025】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0026】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0027】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0028】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0029】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0030】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0031】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0032】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0033】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0034】 The following configuration is adopted as an embodiment for carrying out the present invention. An artificial intelligence assistant specialized for the management of residential facilities is realized by a system that communicates between the user and the server. 【0035】 The user uses a terminal to input questions about the operation and rules of the residential facility in natural language. The terminal converts this input into an appropriate data format and sends it to the server. The server analyzes the received data using natural language processing technology to identify the language of the input text and understand its intent. For example, if a user asks about the garbage disposal rules of an apartment building, "garbage disposal" and "rules" will be analyzed. 【0036】 The server queries the rule database based on the analyzed information to retrieve the necessary data. Then, the response generation module uses the retrieved information to generate a response formatted appropriately in the user's language. For example, it might create a response such as, "Please put out your trash every Monday and Thursday morning." 【0037】 The generated response is sent from the server to the terminal and displayed to the user on the terminal. This allows the user to obtain information that is formed in real time. Furthermore, the server stores the history of the interaction in a database, which is used to improve accuracy in future interactions and to provide customized responses that are suitable for individual users. 【0038】 As a concrete example, consider a case where a user enters "What is the date of the next board meeting?". The server analyzes this question and determines that date information is needed. Next, the server consults the board meeting schedule database and retrieves the information for the next meeting date. Finally, using the retrieved information, it generates and sends a response to the user stating, "The next board meeting will be held on October 10, 2023." 【0039】 Thus, the present invention effectively and efficiently provides information that meets the diverse needs in the management of residential facilities, thereby enabling smooth communication among residents and improving the efficiency of management operations. 【0040】 The following describes the processing flow. 【0041】 Step 1: 【0042】 The user inputs questions or requests in natural language using a terminal. For example, they might input, "What are the operating hours for the shared facilities in the apartment building?" The terminal converts this input into digital data and formats it into a format that can be sent to the server. 【0043】 Step 2: 【0044】 The terminal sends user input data to the server. Following the data communication protocol, encoding and other necessary processes are performed to ensure the data is delivered without errors. 【0045】 Step 3: 【0046】 The server passes the data received from the terminal to a natural language processing module. Here, the language of the text is identified and intent analysis is performed. The focus of the user's question, "usage time for shared facilities," is identified. 【0047】 Step 4: 【0048】 The server retrieves relevant information from the rules database based on the analysis results. Specifically, it searches for data regarding the usage times of the apartment building's shared facilities and extracts the relevant information. 【0049】 Step 5: 【0050】 The server uses a response generation module to format the acquired information in a way that is easy for the user to understand. Based on the user's language settings, it generates a multilingual response. For example, it might say, "Shared facilities are available from 9 AM to 9 PM." 【0051】 Step 6: 【0052】 The server sends the generated response to the user's terminal. At this stage, the response data is sent in a format that can be interpreted by the terminal, according to the transfer protocol. 【0053】 Step 7: 【0054】 The device displays the responses it receives to the user. This visualizes the responses on the display, allowing the user to verify the answers to the questions they entered. 【0055】 Step 8: 【0056】 The server stores a series of interactions with the user in a database. This data is used to analyze customer preferences and inquiry trends, and to improve the accuracy of AI models. 【0057】 (Example 1) 【0058】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0059】 In managing residential areas, users are required to be able to ask questions and make requests in various languages, and to receive information quickly and accurately. However, conventional systems have challenges in smooth communication between languages ​​during information processing and language translation, and furthermore, they do not adequately improve response accuracy by utilizing history. 【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 information analysis means, information acquisition means, response generation means, data conversion means, history storage means, and a translation function. This enables quick and accurate responses to user inquiries, improved response accuracy through the use of history, and information exchange between multiple languages. 【0062】 A "knowledge processing device" refers to an entire system for performing information processing for the purpose of managing a residential area. 【0063】 "User" refers to a person who uses a knowledge processing device to inquire about information and management related to their living area. 【0064】 "Natural language" refers to the forms of language and writing that humans use on a daily basis, and is not a specific programming language. 【0065】 "Information analysis means" refers to a function that analyzes natural language input received from users and understands their intent. 【0066】 A "rule storage device" refers to a database that holds rules and regulations related to a residential area. 【0067】 "Information acquisition means" refers to the function of extracting necessary information from the rule storage device based on the results of analysis performed by the information analysis means. 【0068】 "Response generation means" refers to a function that organizes acquired information according to the user's language and needs and generates an appropriate response. 【0069】 "Response transmission means" refers to the functions and processes for delivering the generated response to the user. 【0070】 "Data conversion means" refers to a function that converts user input into a digital format and prepares it for processing within the system. 【0071】 "History saving means" refers to a function that saves past interactions with users and uses this information to improve the accuracy of future responses. 【0072】 A "translation function" refers to a feature that plays the role of converting languages ​​to enable smooth communication between multiple languages. 【0073】 A "generative AI model" refers to a model that utilizes artificial intelligence technology to recognize patterns through learning and generate responses. 【0074】 This invention provides a knowledge processing device specifically designed for managing residential areas, and is primarily composed of a user, a terminal, and a server. Specific embodiments are described below. 【0075】 Users input inquiries about managing their living area and related information into the terminal using natural language. For example, they might input, "Please tell me the garbage collection day." The terminal converts the received natural language input into digital data, formats it appropriately, and sends it to the server. 【0076】 The server uses a generative AI model and information analysis tools to analyze data sent by the user and understand their intent. After the analysis is complete, it retrieves relevant information from the rule storage device via an information retrieval tool. Here, information from the database is used to retrieve specific information, such as "Garbage collection days are Monday and Thursday." 【0077】 The acquired information is organized according to the user's language by a response generation mechanism on the server, generating a natural-sounding response. This process also utilizes generative AI model technology. For example, in response to a user's question, the response "The next garbage collection days are Monday and Thursday mornings" is generated. 【0078】 The generated response is sent from the server to the terminal, allowing the user to receive information in real time. The terminal is responsible for displaying the received information to the user. The server also saves a history of interactions with the user and uses this history for future communications. This allows the server to provide more accurate and personalized responses based on past interactions. 【0079】 Furthermore, if multilingual support is required, the server utilizes translation capabilities to enable communication between different languages. For example, it can generate answers in Japanese to questions asked in English. 【0080】 As described above, the present invention uses a generative AI model and natural language processing technology with prompt statements to realize an effective and efficient information provision system that meets the diverse needs in the management of residential areas. A concrete example of a prompt statement is the instruction, "Please enter your question regarding the management of residential facilities in natural language." 【0081】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0082】 Step 1: 【0083】 Users input questions and requests related to their residential area into the terminal using natural language. This input is captured as natural language text data for conversion into a digital format. For example, they might input something like, "I want to know the reservation status of the meeting rooms." 【0084】 Step 2: 【0085】 The terminal processes the input text data and converts it into a data format that can be sent to the server. This step involves converting the text's character encoding and formatting it to a protocol-compliant format. As output, the formatted string is sent to the server. 【0086】 Step 3: 【0087】 The server analyzes the formatted data received from the terminal. Using a generative AI model and natural language processing techniques, it extracts the intent and important keywords of the text to understand its content. In this case, it identifies keywords such as "meeting room rental" and "reservation status" from the text to grasp the main point of the question. 【0088】 Step 4: 【0089】 Based on the analyzed information, the server queries the rule storage device to retrieve relevant information. For example, it might refer to a database showing the "reservation status of meeting rooms" and extract availability and reservation status. Based on these results, it organizes the necessary information. 【0090】 Step 5: 【0091】 The server uses response generation tools to convert the acquired information into a language and format that is easy for the user to understand. The generation AI model produces natural-sounding sentences that fit the specific context. As output, appropriate sentences such as "The meeting room is available from 2 PM today" are created. 【0092】 Step 6: 【0093】 The server sends the generated response to the terminal. The terminal then displays the received information to the user. The user can then view the information displayed on the terminal and receive real-time guidance. 【0094】 Step 7: 【0095】 The server saves the history of interactions to a database using a history retention mechanism. This history is used to improve the accuracy of responses to similar questions in subsequent communications. Furthermore, if multilingual responses are required, a translation function is used. 【0096】 (Application Example 1) 【0097】 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." 【0098】 In modern urban life, residents seek efficient ways to obtain information about their daily lives. However, because information is so diverse, acquiring and utilizing it is not easy. Furthermore, language barriers in multilingual environments also hinder communication among residents. There is a need to address these challenges and provide support systems that enable residents to quickly and accurately obtain the information they need for their lives. 【0099】 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. 【0100】 In this invention, the server includes language processing means for receiving and analyzing natural language input from a user, information acquisition means for obtaining relevant information from a rule information repository based on the analyzed information, and urban information provision means for providing information on public facilities and services within the city. This enables residents to quickly and accurately obtain necessary information even in a multilingual environment, making urban life more comfortable. 【0101】 "Residential facilities" refer primarily to buildings and their surrounding environments used by people for their daily lives. 【0102】 "Urban management" refers to activities that operate and maintain urban infrastructure and public services to make citizens' lives comfortable and efficient. 【0103】 "Artificial intelligence assistance" refers to providing technology that enables computers to mimic human intellectual activity and automate information processing and decision-making. 【0104】 "Language processing means" refers to technologies and programs that analyze natural language input from users and understand their intent. 【0105】 "Information acquisition means" refers to the technologies and methods used to search for and acquire necessary data from information sources based on analyzed information. 【0106】 "Response generation means" refers to technologies and programs that create answers in a user-friendly format based on acquired information. 【0107】 "Response transmission means" refers to the technology and procedures for sending the generated response to the user's computer terminal. 【0108】 "Urban information provision methods" refer to systems and technologies for collecting information on public facilities and services within a city and providing it to residents. 【0109】 In the system implementing this invention, to provide information about residential facilities and urban areas, the user first inputs a question in natural language using an application on their terminal. The user's terminal receives this input as digital data and sends it to a server via the internet. The server analyzes the input received from the user using a natural language processing platform to understand the user's intent. In this process, online natural language processing services such as Google Cloud NLP are often used. 【0110】 Based on the analyzed information, the server retrieves relevant information from the rules database and also refers to the city information database, which includes information about the city's public facilities and services. Based on the retrieved data, the response generation module creates a user-friendly response and formats it in a format suitable for the user's language. 【0111】 Ultimately, the server sends this generated response to the user's terminal, allowing the user to obtain the necessary information in real time by viewing it. This enables users to quickly and accurately obtain the information they need for urban life, even in a multilingual environment. 【0112】 For example, if a user asks, "What local events are happening this week?", the server will refer to the event schedule database and generate a response such as, "There is a music festival at the city park this weekend." A possible prompt for the generating AI model could be in the form of, "Please receive a question from a citizen, analyze the information necessary to provide accurate information about events and public services using natural language processing technology, and generate an appropriate response in Japanese." 【0113】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0114】 Step 1: 【0115】 The user launches the application using their device and enters a question in natural language, such as "What are the local events this week?". The entered question is received on the device as text data. 【0116】 Step 2: 【0117】 The terminal transfers the received text data to the server via the internet. Upon receiving the input data, the server receives the data and prepares for the next processing step. HTTPS communication is used for sending and receiving data. 【0118】 Step 3: 【0119】 The server analyzes the received text data using a natural language processing platform such as Google Cloud NLP. Specifically, it extracts keywords from the input data and understands the intent of the question. In this case, the keywords extracted are "local events" and "this week." The analyzed intent data is then generated as output. 【0120】 Step 4: 【0121】 Based on the analysis results, the server queries the database where the event schedule is stored. For example, it searches the database for event information relevant to this week and extracts the relevant information. As a result, the event information extracted from the database (e.g., "There will be a music festival at the city park this weekend") is output. 【0122】 Step 5: 【0123】 The response generation module on the server generates a response tailored to the user's language based on the extracted event information. This response is then output as data formatted in a natural language format that is easy to understand. 【0124】 Step 6: 【0125】 The server sends the formatted answer data to the user's device. The user's device receives this data and displays it on the application's user interface. This allows the user to obtain answers to questions quickly and accurately. 【0126】 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. 【0127】 This invention provides more personalized responses by incorporating an emotion engine that recognizes user emotions into an artificial intelligence assistant system specifically designed for managing residential facilities. This system generates appropriate responses to user questions and requests, and further adjusts its response method according to the user's emotional state, thereby enabling smooth communication. 【0128】 Users input questions and requests into the system using natural language via a terminal. The terminal converts this information into a digital format and sends it to the server. Upon receiving the input, the server first analyzes the input text using natural language processing to understand its content and identify the user's intent. Next, based on the analysis results, it accesses a rule database to retrieve relevant information. 【0129】 The server incorporates an emotion engine that analyzes user emotions based on their input text. This process uses textual expressions, linguistic features, and past interaction history to identify the user's emotional state. The identified emotions influence the response generation process, which is used to adjust the tone and wording of the response. For example, if a user is expressing dissatisfaction, the system can generate a more polite and empathetic response. 【0130】 As a concrete example, consider a case where a user inputs, "I am dissatisfied with the recent actions of the board of directors." The server extracts the emotion of "dissatisfaction" through natural language processing. After referring to the rules database and obtaining information about the board's actions, the emotion engine takes this dissatisfaction into consideration and generates empathetic content such as, "We understand how you feel. We can also bring this up on the agenda for the next board meeting." 【0131】 Finally, the server sends the generated response to the terminal, which then displays it to the user. In this way, the user can receive a personalized, emotionally responsive response tailored to their individual situation. The history of the interaction is also stored in a database and used to improve future responses. 【0132】 This system can improve the quality of communication in the management of residential facilities and increase user satisfaction. 【0133】 The following describes the processing flow. 【0134】 Step 1: 【0135】 The user inputs questions or opinions in natural language through their device. For example, they might type, "I am dissatisfied with the board's latest decision." The device then prepares to send this text data to the server. 【0136】 Step 2: 【0137】 The terminal sends user input to the server in digital format. The data is formatted to ensure it reaches the server without errors. 【0138】 Step 3: 【0139】 The server analyzes the received data using a natural language processing engine. It extracts important keywords and intentions from the input text and identifies the focus of questions and opinions. 【0140】 Step 4: 【0141】 The server passes the input text to the sentiment engine, which analyzes the user's emotions. It detects words and expressions in the text that indicate emotions and identifies the user's emotional state (e.g., dissatisfaction, excitement, joy, etc.). 【0142】 Step 5: 【0143】 The server queries the rule database based on the analysis results. It retrieves information about the user's intent and the latest decisions, and collects the data necessary for the response. 【0144】 Step 6: 【0145】 Based on the information and emotional state collected by the server, a response generation engine is used to format the response to the user. The response is created in an emotionally sensitive tone, with specific and considerate content. For example, it might generate a response such as, "I understand your dissatisfaction. We can propose this as an agenda item at the next board meeting." 【0146】 Step 7: 【0147】 The server sends the generated response to the terminal. The data format is adjusted so that the response is easily understood by the user. 【0148】 Step 8: 【0149】 The device displays the received response on the screen. Through this response, the user can feel that the system understands their emotions and is responding appropriately. 【0150】 Step 9: 【0151】 The server stores user interactions in a database. This allows for improved response accuracy in future interactions and a deeper understanding of user preferences. 【0152】 (Example 2) 【0153】 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". 【0154】 In managing residential facilities, there is a need to provide accurate and emotionally sensitive responses to complex questions and requests from users. Furthermore, challenges exist in multilingual environments and in appropriately recognizing user emotions. 【0155】 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. 【0156】 In this invention, the server includes information processing means, information acquisition means, information generation means, information transmission means, and information analysis means. This makes it possible to personalize responses while taking user emotions into consideration and improve the quality of communication in the management of residential facilities. 【0157】 "Information processing means" refers to a method for analyzing natural language input from users and understanding their intent and content. 【0158】 "Information acquisition means" refers to the means of obtaining related information from a rule database based on the analyzed information. 【0159】 "Information generation means" refers to means for appropriately formatting acquired information and generating a response to the user. 【0160】 "Information transmission means" refers to a means of communicating the generated response to the user. 【0161】 "Information analysis means" refers to methods for analyzing the emotions based on user input and adjusting the tone and wording of responses. 【0162】 The present invention relates to an artificial intelligence assistant system specifically designed for the management of residential facilities, which accurately analyzes user input and provides responses that take emotions into consideration. This system includes information processing means, information acquisition means, information generation means, information transmission means, and information analysis means. 【0163】 First, the user inputs questions or requests in natural language via a terminal. This input is converted into text format using speech recognition software. Specific software options include open-source speech recognition engines and commercial voice input tools. The converted input is then sent to a server via the network. 【0164】 The server analyzes the input text using information processing tools. This analysis employs a natural language processing (NLP) engine, such as Google's Dialogflow or an open-source language analysis library. In this step, the user's intent is identified, and necessary information is retrieved from a rules database. 【0165】 Furthermore, the server incorporates an emotion engine as a means of information analysis. This analyzes the user's emotional state from their input, taking into account past conversation history and other factors. The analysis results are then reflected in the process of generating responses using a generative AI model. Here, the tone and wording of the responses are adjusted to generate appropriate feedback for the user. 【0166】 A concrete example of a prompt is: "Create a prompt that generates an empathetic response when a user expresses dissatisfaction with the management of their residential facility." Based on this prompt, the generation AI model generates the necessary response. 【0167】 Finally, the server sends this response to the terminal. The terminal displays the received response to the user, allowing the user to receive accurate and emotionally sensitive information. This system makes it possible to improve the quality of communication and user satisfaction in the management of residential facilities. 【0168】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0169】 Step 1: 【0170】 Users input questions and requests regarding the management of their residential facilities into the terminal using natural language. This input can be either text or voice. In the case of voice input, the terminal uses speech recognition software to convert it into text. It receives natural language data as input and obtains text data as output. 【0171】 Step 2: 【0172】 The terminal sends the input text data to the server. The transmitted data is used as information to analyze the user's requests and intentions. The input is text data transferred to the server, and the output is the transmission of data to the server. 【0173】 Step 3: 【0174】 The server uses a natural language processing (NLP) engine to analyze text data as an information processing tool. Specifically, it tokenizes the text and performs syntactic analysis to identify the user's intent. Based on the text data received as input, it extracts intent and key information to obtain the analysis results as output. 【0175】 Step 4: 【0176】 The server retrieves relevant information from the rules database based on the analyzed data. Here, it executes database queries as needed to extract appropriate information regarding the management of residential facilities. The input is the analysis result, and the output is the retrieved relevant information. 【0177】 Step 5: 【0178】 The server uses the acquired information to generate a response through a generative AI model. It utilizes an emotion engine to adjust the response to a tone that takes the user's emotional state into account. The input is the acquired information and the emotion analysis results, and the output is the adjusted response. 【0179】 Step 6: 【0180】 The server's role is to return information to the user by sending the generated response to the terminal. The input is the generated response, and the output is the sending of the response to the terminal. 【0181】 Step 7: 【0182】 The terminal displays the received response to the user. This allows the user to review the information and suggestions received from the system and decide on their next action. The input is response data from the server, and the output is a response display in a format that the user can easily understand. 【0183】 (Application Example 2) 【0184】 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". 【0185】 Communication with residents in residential facilities and urban areas goes beyond mere information exchange; it requires understanding residents' feelings and intentions, and responding to individual situations. This project aims to build a system that provides efficient and empathetic responses in dialogue with residents, thereby improving their living environment and increasing their satisfaction. 【0186】 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. 【0187】 In this invention, the server includes language processing means, information acquisition means, response generation means, response transmission means, and emotion recognition means. This enables the server to receive feedback on residential facilities and urban functions, and to understand and respond in accordance with emotions. 【0188】 "Residential facilities" refer to buildings used by people to live and work, and include spaces such as houses and public facilities. 【0189】 An "artificial intelligence assistant" is a system with intelligence that provides information in response to human instructions and questions, and assists with tasks. 【0190】 "Natural language" refers to the words and sentences that humans use on a daily basis, and is a linguistic form that is subject to machine processing. 【0191】 "Language processing means" refers to a device or process that has the technology to automatically analyze information from text or audio and understand its meaning. 【0192】 "Information acquisition means" refers to technologies and devices for collecting necessary data and information from external databases and information sources. 【0193】 "Response generation means" refers to a technology or device that constructs an appropriate response for the user based on acquired information and analysis results. 【0194】 "Response transmission means" refers to a technology or device for transmitting the generated response to the user's terminal. 【0195】 "Emotion recognition means" refers to a technology or device for analyzing and estimating an emotional state from user input. 【0196】 "Data management means" refers to technology or equipment used to accumulate the history of interactions and to improve future responses. 【0197】 "Language translation" is a technology that automatically converts spoken language and text to enable communication between different languages. 【0198】 This invention is a system for optimizing communication with residents in residential facilities and cities. The server receives user input and analyzes it using language processing means. The analyzed data is then used by information acquisition means to search and retrieve relevant information from a rule database. In this process, the Google Cloud Natural Language API is used for text analysis, and the acquired information is managed using Amazon RDS. 【0199】 The acquired information is formatted in the user's language by a response generation system to construct an appropriate response. IBM Watson® Tone Analyzer is used for this response generation, and in conjunction with emotion recognition systems, it analyzes the user's emotional state and adjusts the response tone. 【0200】 The terminal sends the generated response to the user, ensuring that the user receives information and suggestions smoothly. For example, if a user reports, "Garbage collection has been slow lately," the system recognizes the user's dissatisfaction and generates an empathetic response such as, "We value your feedback. We will promptly arrange for improvements to the garbage collection schedule." 【0201】 An example of a prompt is: "Show how a user support system for a residential facility management AI in a smart city generates a response that includes empathy and steps toward resolution in response to a message expressing dissatisfaction." 【0202】 This system allows for the effective collection of resident feedback, which can contribute to improving urban functions. 【0203】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0204】 Step 1: 【0205】 The user sends natural language input to the system via a device such as a smartphone. This input is transmitted to the server as an initial request or question. The server receives the input and prepares for the next analysis process. 【0206】 Step 2: 【0207】 The server analyzes the natural language text received using the Google Cloud Natural Language API. It breaks down the input text, understands its structure and content, and then identifies the user's intent. This process extracts semantic elements from the text, preparing it for information retrieval. 【0208】 Step 3: 【0209】 Based on the analyzed information, the server accesses Amazon RDS using information retrieval methods to search for and retrieve relevant information from the rules database. Feedback and specific data are extracted from the database, providing the necessary materials for generating a response. 【0210】 Step 4: 【0211】 The server performs sentiment analysis based on information obtained using IBM Watson Tone Analyzer. It identifies the emotional state from the user's statements and adjusts the tone of the response through sentiment recognition. At this stage, the emotional tone of the response is determined. 【0212】 Step 5: 【0213】 The server constructs an appropriate response using a response generation mechanism. The response, formatted in the user's language, is generated by taking into account the acquired information and sentiment analysis results. This response is then compiled into a specific text. 【0214】 Step 6: 【0215】 The server sends the generated response to the terminal. Immediate feedback is provided to the user via the response transmission mechanism. The generated response is displayed on the user's terminal, allowing the user to confirm the system's response. 【0216】 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. 【0217】 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. 【0218】 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. 【0219】 [Second Embodiment] 【0220】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0221】 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. 【0222】 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). 【0223】 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. 【0224】 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. 【0225】 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). 【0226】 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. 【0227】 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. 【0228】 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. 【0229】 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. 【0230】 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. 【0231】 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". 【0232】 The following configuration is adopted as an embodiment for carrying out the present invention. An artificial intelligence assistant specialized for the management of residential facilities is realized by a system that communicates between the user and the server. 【0233】 The user uses a terminal to input questions about the operation and rules of the residential facility in natural language. The terminal converts this input into an appropriate data format and sends it to the server. The server analyzes the received data using natural language processing technology to identify the language of the input text and understand its intent. For example, if a user asks about the garbage disposal rules of an apartment building, "garbage disposal" and "rules" will be analyzed. 【0234】 The server queries the rule database based on the analyzed information to retrieve the necessary data. Then, the response generation module uses the retrieved information to generate a response formatted appropriately in the user's language. For example, it might create a response such as, "Please put out your trash every Monday and Thursday morning." 【0235】 The generated response is sent from the server to the terminal and displayed to the user on the terminal. This allows the user to obtain information that is formed in real time. Furthermore, the server stores the history of the interaction in a database, which is used to improve accuracy in future interactions and to provide customized responses that are suitable for individual users. 【0236】 As a concrete example, consider a case where a user enters "What is the date of the next board meeting?". The server analyzes this question and determines that date information is needed. Next, the server consults the board meeting schedule database and retrieves the information for the next meeting date. Finally, using the retrieved information, it generates and sends a response to the user stating, "The next board meeting will be held on October 10, 2023." 【0237】 Thus, the present invention effectively and efficiently provides information that meets the diverse needs in the management of residential facilities, thereby enabling smooth communication among residents and improving the efficiency of management operations. 【0238】 The following describes the processing flow. 【0239】 Step 1: 【0240】 The user inputs questions or requests in natural language using a terminal. For example, they might input, "What are the operating hours for the shared facilities in the apartment building?" The terminal converts this input into digital data and formats it into a format that can be sent to the server. 【0241】 Step 2: 【0242】 The terminal sends user input data to the server. Following the data communication protocol, encoding and other necessary processes are performed to ensure the data is delivered without errors. 【0243】 Step 3: 【0244】 The server passes the data received from the terminal to a natural language processing module. Here, the language of the text is identified and intent analysis is performed. The focus of the user's question, "usage time for shared facilities," is identified. 【0245】 Step 4: 【0246】 The server retrieves relevant information from the rules database based on the analysis results. Specifically, it searches for data regarding the usage times of the apartment building's shared facilities and extracts the relevant information. 【0247】 Step 5: 【0248】 The server uses a response generation module to format the acquired information in a way that is easy for the user to understand. Based on the user's language settings, it generates a multilingual response. For example, it might say, "Shared facilities are available from 9 AM to 9 PM." 【0249】 Step 6: 【0250】 The server sends the generated response to the user's terminal. At this stage, the response data is sent in a format that can be interpreted by the terminal, according to the transfer protocol. 【0251】 Step 7: 【0252】 The device displays the responses it receives to the user. This visualizes the responses on the display, allowing the user to verify the answers to the questions they entered. 【0253】 Step 8: 【0254】 The server stores a series of interactions with the user in a database. This data is used to analyze customer preferences and inquiry trends, and to improve the accuracy of AI models. 【0255】 (Example 1) 【0256】 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." 【0257】 In managing residential areas, users are required to be able to ask questions and make requests in various languages, and to receive information quickly and accurately. However, conventional systems have challenges in smooth communication between languages ​​during information processing and language translation, and furthermore, they do not adequately improve response accuracy by utilizing history. 【0258】 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. 【0259】 In this invention, the server includes information analysis means, information acquisition means, response generation means, data conversion means, history storage means, and a translation function. This enables quick and accurate responses to user inquiries, improved response accuracy through the use of history, and information exchange between multiple languages. 【0260】 A "knowledge processing device" refers to an entire system for performing information processing for the purpose of managing a residential area. 【0261】 "User" refers to a person who uses a knowledge processing device to inquire about information and management related to their living area. 【0262】 "Natural language" refers to the forms of language and writing that humans use on a daily basis, and is not a specific programming language. 【0263】 "Information analysis means" refers to a function that analyzes natural language input received from users and understands their intent. 【0264】 A "rule storage device" refers to a database that holds rules and regulations related to a residential area. 【0265】 "Information acquisition means" refers to the function of extracting necessary information from the rule storage device based on the results of analysis performed by the information analysis means. 【0266】 "Response generation means" refers to a function that organizes acquired information according to the user's language and needs and generates an appropriate response. 【0267】 "Response transmission means" refers to the functions and processes for delivering the generated response to the user. 【0268】 "Data conversion means" refers to a function that converts user input into a digital format and prepares it for processing within the system. 【0269】 "History saving means" refers to a function that saves past interactions with users and uses this information to improve the accuracy of future responses. 【0270】 A "translation function" refers to a feature that plays the role of converting languages ​​to enable smooth communication between multiple languages. 【0271】 A "generative AI model" refers to a model that utilizes artificial intelligence technology to recognize patterns through learning and generate responses. 【0272】 This invention provides a knowledge processing device specifically designed for managing residential areas, and is primarily composed of a user, a terminal, and a server. Specific embodiments are described below. 【0273】 Users input inquiries about managing their living area and related information into the terminal using natural language. For example, they might input, "Please tell me the garbage collection day." The terminal converts the received natural language input into digital data, formats it appropriately, and sends it to the server. 【0274】 The server uses a generative AI model and information analysis tools to analyze data sent by the user and understand their intent. After the analysis is complete, it retrieves relevant information from the rule storage device via an information retrieval tool. Here, information from the database is used to retrieve specific information, such as "Garbage collection days are Monday and Thursday." 【0275】 The acquired information is organized according to the user's language by a response generation mechanism on the server, generating a natural-sounding response. This process also utilizes generative AI model technology. For example, in response to a user's question, the response "The next garbage collection days are Monday and Thursday mornings" is generated. 【0276】 The generated response is sent from the server to the terminal, allowing the user to receive information in real time. The terminal is responsible for displaying the received information to the user. The server also saves a history of interactions with the user and uses this history for future communications. This allows the server to provide more accurate and personalized responses based on past interactions. 【0277】 Furthermore, if multilingual support is required, the server utilizes translation capabilities to enable communication between different languages. For example, it can generate answers in Japanese to questions asked in English. 【0278】 As described above, the present invention uses a generative AI model and natural language processing technology with prompt statements to realize an effective and efficient information provision system that meets the diverse needs in the management of residential areas. A concrete example of a prompt statement is the instruction, "Please enter your question regarding the management of residential facilities in natural language." 【0279】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0280】 Step 1: 【0281】 The user inputs questions or requests related to the living area into the terminal in natural language. Since this input is to be converted into a digital format, it is obtained as natural language text data. For example, it is input as "I want to know the reservation status of the rental conference room." 【0282】 Step 2: 【0283】 The terminal processes the input text data and converts it into a data format that can be sent to the server. In this step, character encoding conversion of the text and formatting according to the protocol are performed. As output, a formatted character string is sent to the server. 【0284】 Step 3: 【0285】 The server analyzes the formatted data received from the terminal. Using a generation AI model, through natural language processing technology, it extracts the intention of the text and important keywords, and understands the content. Here, by identifying keywords such as "rental conference room" and "reservation status" from the text, the main idea of the question is grasped. 【0286】 Step 4: 【0287】 The server executes a query on the rule storage device based on the analyzed information to obtain relevant information. For example, it refers to a database showing the "reservation status of the rental conference room" and extracts the availability status and reservation status. Based on this result, the necessary information is sorted out. 【0288】 Step 5: 【0289】 The server uses a response generation means to convert the obtained information into a language and format that are easy for the user to understand. The generation AI model generates a natural sentence that conforms to the specific context. As output, an appropriate sentence such as "The rental conference room is available from 14:00 today" is created. 【0290】 Step 6: 【0291】 The server sends the generated response to the terminal. The terminal then displays the received information to the user. The user can then view the information displayed on the terminal and receive real-time guidance. 【0292】 Step 7: 【0293】 The server saves the history of interactions to a database using a history retention mechanism. This history is used to improve the accuracy of responses to similar questions in subsequent communications. Furthermore, if multilingual responses are required, a translation function is used. 【0294】 (Application Example 1) 【0295】 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." 【0296】 In modern urban life, residents seek efficient ways to obtain information about their daily lives. However, because information is so diverse, acquiring and utilizing it is not easy. Furthermore, language barriers in multilingual environments also hinder communication among residents. There is a need to address these challenges and provide support systems that enable residents to quickly and accurately obtain the information they need for their lives. 【0297】 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. 【0298】 In this invention, the server includes language processing means for receiving and analyzing natural language input from a user, information acquisition means for obtaining relevant information from a rule information repository based on the analyzed information, and urban information provision means for providing information on public facilities and services within the city. This enables residents to quickly and accurately obtain necessary information even in a multilingual environment, making urban life more comfortable. 【0299】 "Residential facilities" mainly refer to buildings and their surrounding environments used by people for their daily lives. 【0300】 "Urban management" refers to activities that involve the operation and maintenance of urban infrastructure and public services to make citizens' lives comfortable and efficient. 【0301】 "Artificial intelligence support" refers to the technology provided by computers to mimic human intellectual activities and automate information processing and decision-making. 【0302】 "Language processing means" refers to technologies and programs for analyzing natural language input from users and understanding their intentions. 【0303】 "Information acquisition means" refers to technologies and methods for searching and obtaining necessary data from information sources based on the analyzed information. 【0304】 "Response generation means" refers to technologies and programs for creating answers in an easy-to-understand form for users based on the acquired information. 【0305】 "Response transmission means" refers to technologies and procedures for transmitting the generated answers to the user's computer terminal. 【0306】 "Urban information provision means" refers to systems and technologies for collecting information on public facilities and services within a city and providing it to residents. 【0307】 In the system for implementing this invention, in order to provide information on residential facilities and within the city, the user first uses an application on the terminal to input a question in natural language. The user's terminal receives this input as digital data and transmits it to the server via the Internet. The server analyzes the input received from the user using a natural language processing platform to understand the intention. In this case, online natural language processing services such as Google Cloud NLP are often used. 【0308】 Based on the analyzed information, the server retrieves relevant information from the rules database and also refers to the city information database, which includes information about the city's public facilities and services. Based on the retrieved data, the response generation module creates a user-friendly response and formats it in a format suitable for the user's language. 【0309】 Ultimately, the server sends this generated response to the user's terminal, allowing the user to obtain the necessary information in real time by viewing it. This enables users to quickly and accurately obtain the information they need for urban life, even in a multilingual environment. 【0310】 For example, if a user asks, "What local events are happening this week?", the server will refer to the event schedule database and generate a response such as, "There is a music festival at the city park this weekend." A possible prompt for the generating AI model could be in the form of, "Please receive a question from a citizen, analyze the information necessary to provide accurate information about events and public services using natural language processing technology, and generate an appropriate response in Japanese." 【0311】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0312】 Step 1: 【0313】 The user launches the application using their device and enters a question in natural language, such as "What are the local events this week?". The entered question is received on the device as text data. 【0314】 Step 2: 【0315】 The terminal transfers the received text data to the server via the internet. Upon receiving the input data, the server receives the data and prepares for the next processing step. HTTPS communication is used for sending and receiving data. 【0316】 Step 3: 【0317】 The server analyzes the received text data using a natural language processing platform such as Google Cloud NLP. Specifically, it extracts keywords from the input data and understands the intent of the question. In this case, the keywords extracted are "local events" and "this week." The analyzed intent data is then generated as output. 【0318】 Step 4: 【0319】 Based on the analysis results, the server queries the database where the event schedule is stored. For example, it searches the database for event information relevant to this week and extracts the relevant information. As a result, the event information extracted from the database (e.g., "There will be a music festival at the city park this weekend") is output. 【0320】 Step 5: 【0321】 The response generation module on the server generates a response tailored to the user's language based on the extracted event information. This response is then output as data formatted in a natural language format that is easy to understand. 【0322】 Step 6: 【0323】 The server sends the formatted answer data to the user's device. The user's device receives this data and displays it on the application's user interface. This allows the user to obtain answers to questions quickly and accurately. 【0324】 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. 【0325】 This invention provides more personalized responses by incorporating an emotion engine that recognizes user emotions into an artificial intelligence assistant system specifically designed for managing residential facilities. This system generates appropriate responses to user questions and requests, and further adjusts its response method according to the user's emotional state, thereby enabling smooth communication. 【0326】 Users input questions and requests into the system using natural language via a terminal. The terminal converts this information into a digital format and sends it to the server. Upon receiving the input, the server first analyzes the input text using natural language processing to understand its content and identify the user's intent. Next, based on the analysis results, it accesses a rule database to retrieve relevant information. 【0327】 The server incorporates an emotion engine that analyzes user emotions based on their input text. This process uses textual expressions, linguistic features, and past interaction history to identify the user's emotional state. The identified emotions influence the response generation process, which is used to adjust the tone and wording of the response. For example, if a user is expressing dissatisfaction, the system can generate a more polite and empathetic response. 【0328】 As a concrete example, consider a case where a user inputs, "I am dissatisfied with the recent actions of the board of directors." The server extracts the emotion of "dissatisfaction" through natural language processing. After referring to the rules database and obtaining information about the board's actions, the emotion engine takes this dissatisfaction into consideration and generates empathetic content such as, "We understand how you feel. We can also bring this up on the agenda for the next board meeting." 【0329】 Finally, the server sends the generated response to the terminal, which then displays it to the user. In this way, the user can receive a personalized, emotionally responsive response tailored to their individual situation. The history of the interaction is also stored in a database and used to improve future responses. 【0330】 This system can improve the quality of communication in the management of residential facilities and increase user satisfaction. 【0331】 The following describes the processing flow. 【0332】 Step 1: 【0333】 The user inputs questions or opinions in natural language through their device. For example, they might type, "I am dissatisfied with the board's latest decision." The device then prepares to send this text data to the server. 【0334】 Step 2: 【0335】 The terminal sends user input to the server in digital format. The data is formatted to ensure it reaches the server without errors. 【0336】 Step 3: 【0337】 The server analyzes the received data using a natural language processing engine. It extracts important keywords and intentions from the input text and identifies the focus of questions and opinions. 【0338】 Step 4: 【0339】 The server passes the input text to the sentiment engine, which analyzes the user's emotions. It detects words and expressions in the text that indicate emotions and identifies the user's emotional state (e.g., dissatisfaction, excitement, joy, etc.). 【0340】 Step 5: 【0341】 The server queries the rule database based on the analysis results. It retrieves information about the user's intent and the latest decisions, and collects the data necessary for the response. 【0342】 Step 6: 【0343】 Based on the information and emotional state collected by the server, a response generation engine is used to format the response to the user. The response is created in an emotionally sensitive tone, with specific and considerate content. For example, it might generate a response such as, "I understand your dissatisfaction. We can propose this as an agenda item at the next board meeting." 【0344】 Step 7: 【0345】 The server sends the generated response to the terminal. The data format is adjusted so that the response is easily understood by the user. 【0346】 Step 8: 【0347】 The device displays the received response on the screen. Through this response, the user can feel that the system understands their emotions and is responding appropriately. 【0348】 Step 9: 【0349】 The server stores user interactions in a database. This allows for improved response accuracy in future interactions and a deeper understanding of user preferences. 【0350】 (Example 2) 【0351】 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". 【0352】 In managing residential facilities, there is a need to provide accurate and emotionally sensitive responses to complex questions and requests from users. Furthermore, challenges exist in multilingual environments and in appropriately recognizing user emotions. 【0353】 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. 【0354】 In this invention, the server includes information processing means, information acquisition means, information generation means, information transmission means, and information analysis means. This makes it possible to personalize responses while taking user emotions into consideration and improve the quality of communication in the management of residential facilities. 【0355】 "Information processing means" refers to a method for analyzing natural language input from users and understanding their intent and content. 【0356】 "Information acquisition means" refers to the means of obtaining related information from a rule database based on the analyzed information. 【0357】 "Information generation means" refers to means for appropriately formatting acquired information and generating a response to the user. 【0358】 "Information transmission means" refers to a means of communicating the generated response to the user. 【0359】 "Information analysis means" refers to methods for analyzing the emotions based on user input and adjusting the tone and wording of responses. 【0360】 The present invention relates to an artificial intelligence assistant system specifically designed for the management of residential facilities, which accurately analyzes user input and provides responses that take emotions into consideration. This system includes information processing means, information acquisition means, information generation means, information transmission means, and information analysis means. 【0361】 First, the user inputs questions or requests in natural language via a terminal. This input is converted into text format using speech recognition software. Specific software options include open-source speech recognition engines and commercial voice input tools. The converted input is then sent to a server via the network. 【0362】 The server analyzes the input text using information processing tools. This analysis employs a natural language processing (NLP) engine, such as Google's Dialogflow or an open-source language analysis library. In this step, the user's intent is identified, and necessary information is retrieved from a rules database. 【0363】 Furthermore, the server incorporates an emotion engine as a means of information analysis. This analyzes the user's emotional state from their input, taking into account past conversation history and other factors. The analysis results are then reflected in the process of generating responses using a generative AI model. Here, the tone and wording of the responses are adjusted to generate appropriate feedback for the user. 【0364】 A concrete example of a prompt is: "Create a prompt that generates an empathetic response when a user expresses dissatisfaction with the management of their residential facility." Based on this prompt, the generation AI model generates the necessary response. 【0365】 Finally, the server sends this response to the terminal. The terminal displays the received response to the user, allowing the user to receive accurate and emotionally sensitive information. This system makes it possible to improve the quality of communication and user satisfaction in the management of residential facilities. 【0366】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0367】 Step 1: 【0368】 Users input questions and requests regarding the management of their residential facilities into the terminal using natural language. This input can be either text or voice. In the case of voice input, the terminal uses speech recognition software to convert it into text. It receives natural language data as input and obtains text data as output. 【0369】 Step 2: 【0370】 The terminal sends the input text data to the server. The transmitted data is used as information to analyze the user's requests and intentions. The input is text data transferred to the server, and the output is the transmission of data to the server. 【0371】 Step 3: 【0372】 The server uses a natural language processing (NLP) engine to analyze text data as an information processing tool. Specifically, it tokenizes the text and performs syntactic analysis to identify the user's intent. Based on the text data received as input, it extracts intent and key information to obtain the analysis results as output. 【0373】 Step 4: 【0374】 The server retrieves relevant information from the rules database based on the analyzed data. Here, it executes database queries as needed to extract appropriate information regarding the management of residential facilities. The input is the analysis result, and the output is the retrieved relevant information. 【0375】 Step 5: 【0376】 The server uses the acquired information to generate a response through a generative AI model. It utilizes an emotion engine to adjust the response to a tone that takes the user's emotional state into account. The input is the acquired information and the emotion analysis results, and the output is the adjusted response. 【0377】 Step 6: 【0378】 The server's role is to return information to the user by sending the generated response to the terminal. The input is the generated response, and the output is the sending of the response to the terminal. 【0379】 Step 7: 【0380】 The terminal displays the received response to the user. This allows the user to review the information and suggestions received from the system and decide on their next action. The input is response data from the server, and the output is a response display in a format that the user can easily understand. 【0381】 (Application Example 2) 【0382】 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." 【0383】 Communication with residents in residential facilities and urban areas goes beyond mere information exchange; it requires understanding residents' feelings and intentions, and responding to individual situations. This project aims to build a system that provides efficient and empathetic responses in dialogue with residents, thereby improving their living environment and increasing their satisfaction. 【0384】 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. 【0385】 In this invention, the server includes language processing means, information acquisition means, response generation means, response transmission means, and emotion recognition means. This enables the server to receive feedback on residential facilities and urban functions, and to understand and respond in accordance with emotions. 【0386】 "Residential facilities" refer to buildings used by people to live and work, and include spaces such as houses and public facilities. 【0387】 An "artificial intelligence assistant" is a system with intelligence that provides information in response to human instructions and questions, and assists with tasks. 【0388】 "Natural language" refers to the words and sentences that humans use on a daily basis, and is a linguistic form that is subject to machine processing. 【0389】 "Language processing means" refers to a device or process that has the technology to automatically analyze information from text or audio and understand its meaning. 【0390】 "Information acquisition means" refers to technologies and devices for collecting necessary data and information from external databases and information sources. 【0391】 "Response generation means" refers to a technology or device that constructs an appropriate response for the user based on acquired information and analysis results. 【0392】 "Response transmission means" refers to a technology or device for transmitting the generated response to the user's terminal. 【0393】 "Emotion recognition means" refers to a technology or device for analyzing and estimating an emotional state from user input. 【0394】 "Data management means" refers to technology or equipment used to accumulate the history of interactions and to improve future responses. 【0395】 "Language translation" is a technology that automatically converts spoken language and text to enable communication between different languages. 【0396】 This invention is a system for optimizing communication with residents in residential facilities and cities. The server receives user input and analyzes it using language processing means. The analyzed data is then used by information acquisition means to search and retrieve relevant information from a rule database. In this process, the Google Cloud Natural Language API is used for text analysis, and the acquired information is managed using Amazon RDS. 【0397】 The acquired information is formatted in the user's language by a response generation system to construct an appropriate response. IBM Watson Tone Analyzer is used for this response generation, and in conjunction with emotion recognition systems, it analyzes the user's emotional state and adjusts the response tone. 【0398】 The terminal sends the generated response to the user, ensuring that the user receives information and suggestions smoothly. For example, if a user reports, "Garbage collection has been slow lately," the system recognizes the user's dissatisfaction and generates an empathetic response such as, "We value your feedback. We will promptly arrange for improvements to the garbage collection schedule." 【0399】 An example of a prompt is: "Show how a user support system for a residential facility management AI in a smart city generates a response that includes empathy and steps toward resolution in response to a message expressing dissatisfaction." 【0400】 This system allows for the effective collection of resident feedback, which can contribute to improving urban functions. 【0401】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0402】 Step 1: 【0403】 The user sends natural language input to the system via a device such as a smartphone. This input is transmitted to the server as an initial request or question. The server receives the input and prepares for the next analysis process. 【0404】 Step 2: 【0405】 The server analyzes the natural language text received using the Google Cloud Natural Language API. It breaks down the input text, understands its structure and content, and then identifies the user's intent. This process extracts semantic elements from the text, preparing it for information retrieval. 【0406】 Step 3: 【0407】 Based on the analyzed information, the server accesses Amazon RDS using information retrieval methods to search for and retrieve relevant information from the rules database. Feedback and specific data are extracted from the database, providing the necessary materials for generating a response. 【0408】 Step 4: 【0409】 The server performs sentiment analysis based on information obtained using IBM Watson Tone Analyzer. It identifies the emotional state from the user's statements and adjusts the tone of the response through sentiment recognition. At this stage, the emotional tone of the response is determined. 【0410】 Step 5: 【0411】 The server constructs an appropriate response using a response generation mechanism. The response, formatted in the user's language, is generated by taking into account the acquired information and sentiment analysis results. This response is then compiled into a specific text. 【0412】 Step 6: 【0413】 The server sends the generated response to the terminal. Immediate feedback is provided to the user via the response transmission mechanism. The generated response is displayed on the user's terminal, allowing the user to confirm the system's response. 【0414】 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. 【0415】 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. 【0416】 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. 【0417】 [Third Embodiment] 【0418】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0419】 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. 【0420】 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). 【0421】 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. 【0422】 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. 【0423】 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). 【0424】 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. 【0425】 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. 【0426】 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. 【0427】 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. 【0428】 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. 【0429】 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". 【0430】 The following configuration is adopted as an embodiment for carrying out the present invention. An artificial intelligence assistant specialized for the management of residential facilities is realized by a system that communicates between the user and the server. 【0431】 The user uses a terminal to input questions about the operation and rules of the residential facility in natural language. The terminal converts this input into an appropriate data format and sends it to the server. The server analyzes the received data using natural language processing technology to identify the language of the input text and understand its intent. For example, if a user asks about the garbage disposal rules of an apartment building, "garbage disposal" and "rules" will be analyzed. 【0432】 The server queries the rule database based on the analyzed information to retrieve the necessary data. Then, the response generation module uses the retrieved information to generate a response formatted appropriately in the user's language. For example, it might create a response such as, "Please put out your trash every Monday and Thursday morning." 【0433】 The generated response is sent from the server to the terminal and displayed to the user on the terminal. This allows the user to obtain information that is formed in real time. Furthermore, the server stores the history of the interaction in a database, which is used to improve accuracy in future interactions and to provide customized responses that are suitable for individual users. 【0434】 As a concrete example, consider a case where a user enters "What is the date of the next board meeting?". The server analyzes this question and determines that date information is needed. Next, the server consults the board meeting schedule database and retrieves the information for the next meeting date. Finally, using the retrieved information, it generates and sends a response to the user stating, "The next board meeting will be held on October 10, 2023." 【0435】 Thus, the present invention effectively and efficiently provides information that meets the diverse needs in the management of residential facilities, thereby enabling smooth communication among residents and improving the efficiency of management operations. 【0436】 The following describes the processing flow. 【0437】 Step 1: 【0438】 The user inputs questions or requests in natural language using a terminal. For example, they might input, "What are the operating hours for the shared facilities in the apartment building?" The terminal converts this input into digital data and formats it into a format that can be sent to the server. 【0439】 Step 2: 【0440】 The terminal sends user input data to the server. Following the data communication protocol, encoding and other necessary processes are performed to ensure the data is delivered without errors. 【0441】 Step 3: 【0442】 The server passes the data received from the terminal to a natural language processing module. Here, the language of the text is identified and intent analysis is performed. The focus of the user's question, "usage time for shared facilities," is identified. 【0443】 Step 4: 【0444】 The server retrieves relevant information from the rules database based on the analysis results. Specifically, it searches for data regarding the usage times of the apartment building's shared facilities and extracts the relevant information. 【0445】 Step 5: 【0446】 The server uses a response generation module to format the acquired information in a way that is easy for the user to understand. Based on the user's language settings, it generates a multilingual response. For example, it might say, "Shared facilities are available from 9 AM to 9 PM." 【0447】 Step 6: 【0448】 The server sends the generated response to the user's terminal. At this stage, the response data is sent in a format that can be interpreted by the terminal, according to the transfer protocol. 【0449】 Step 7: 【0450】 The device displays the responses it receives to the user. This visualizes the responses on the display, allowing the user to verify the answers to the questions they entered. 【0451】 Step 8: 【0452】 The server stores a series of interactions with the user in a database. This data is used to analyze customer preferences and inquiry trends, and to improve the accuracy of AI models. 【0453】 (Example 1) 【0454】 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." 【0455】 In managing residential areas, users are required to be able to ask questions and make requests in various languages, and to receive information quickly and accurately. However, conventional systems have challenges in smooth communication between languages ​​during information processing and language translation, and furthermore, they do not adequately improve response accuracy by utilizing history. 【0456】 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. 【0457】 In this invention, the server includes information analysis means, information acquisition means, response generation means, data conversion means, history storage means, and a translation function. This enables quick and accurate responses to user inquiries, improved response accuracy through the use of history, and information exchange between multiple languages. 【0458】 A "knowledge processing device" refers to an entire system for performing information processing for the purpose of managing a residential area. 【0459】 "User" refers to a person who uses a knowledge processing device to inquire about information and management related to their living area. 【0460】 "Natural language" refers to the forms of language and writing that humans use on a daily basis, and is not a specific programming language. 【0461】 "Information analysis means" refers to a function that analyzes natural language input received from users and understands their intent. 【0462】 A "rule storage device" refers to a database that holds rules and regulations related to a residential area. 【0463】 "Information acquisition means" refers to the function of extracting necessary information from the rule storage device based on the results of analysis performed by the information analysis means. 【0464】 "Response generation means" refers to a function that organizes acquired information according to the user's language and needs and generates an appropriate response. 【0465】 "Response transmission means" refers to the functions and processes for delivering the generated response to the user. 【0466】 "Data conversion means" refers to a function that converts user input into a digital format and prepares it for processing within the system. 【0467】 "History saving means" refers to a function that saves past interactions with users and uses this information to improve the accuracy of future responses. 【0468】 A "translation function" refers to a feature that plays the role of converting languages ​​to enable smooth communication between multiple languages. 【0469】 A "generative AI model" refers to a model that utilizes artificial intelligence technology to recognize patterns through learning and generate responses. 【0470】 This invention provides a knowledge processing device specifically designed for managing residential areas, and is primarily composed of a user, a terminal, and a server. Specific embodiments are described below. 【0471】 Users input inquiries about managing their living area and related information into the terminal using natural language. For example, they might input, "Please tell me the garbage collection day." The terminal converts the received natural language input into digital data, formats it appropriately, and sends it to the server. 【0472】 The server uses a generative AI model and information analysis tools to analyze data sent by the user and understand their intent. After the analysis is complete, it retrieves relevant information from the rule storage device via an information retrieval tool. Here, information from the database is used to retrieve specific information, such as "Garbage collection days are Monday and Thursday." 【0473】 The acquired information is organized according to the user's language by a response generation mechanism on the server, generating a natural-sounding response. This process also utilizes generative AI model technology. For example, in response to a user's question, the response "The next garbage collection days are Monday and Thursday mornings" is generated. 【0474】 The generated response is sent from the server to the terminal, allowing the user to receive information in real time. The terminal is responsible for displaying the received information to the user. The server also saves a history of interactions with the user and uses this history for future communications. This allows the server to provide more accurate and personalized responses based on past interactions. 【0475】 Furthermore, if multilingual support is required, the server utilizes translation capabilities to enable communication between different languages. For example, it can generate answers in Japanese to questions asked in English. 【0476】 As described above, the present invention uses a generative AI model and natural language processing technology with prompt statements to realize an effective and efficient information provision system that meets the diverse needs in the management of residential areas. A concrete example of a prompt statement is the instruction, "Please enter your question regarding the management of residential facilities in natural language." 【0477】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0478】 Step 1: 【0479】 Users input questions and requests related to their residential area into the terminal using natural language. This input is captured as natural language text data for conversion into a digital format. For example, they might input something like, "I want to know the reservation status of the meeting rooms." 【0480】 Step 2: 【0481】 The terminal processes the input text data and converts it into a data format that can be sent to the server. This step involves converting the text's character encoding and formatting it to a protocol-compliant format. As output, the formatted string is sent to the server. 【0482】 Step 3: 【0483】 The server analyzes the formatted data received from the terminal. Using a generative AI model and natural language processing techniques, it extracts the intent and important keywords of the text to understand its content. In this case, it identifies keywords such as "meeting room rental" and "reservation status" from the text to grasp the main point of the question. 【0484】 Step 4: 【0485】 Based on the analyzed information, the server queries the rule storage device to retrieve relevant information. For example, it might refer to a database showing the "reservation status of meeting rooms" and extract availability and reservation status. Based on these results, it organizes the necessary information. 【0486】 Step 5: 【0487】 The server uses response generation tools to convert the acquired information into a language and format that is easy for the user to understand. The generation AI model produces natural-sounding sentences that fit the specific context. As output, appropriate sentences such as "The meeting room is available from 2 PM today" are created. 【0488】 Step 6: 【0489】 The server sends the generated response to the terminal. The terminal then displays the received information to the user. The user can then view the information displayed on the terminal and receive real-time guidance. 【0490】 Step 7: 【0491】 The server saves the history of interactions to a database using a history retention mechanism. This history is used to improve the accuracy of responses to similar questions in subsequent communications. Furthermore, if multilingual responses are required, a translation function is used. 【0492】 (Application Example 1) 【0493】 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." 【0494】 In modern urban life, residents seek efficient ways to obtain information about their daily lives. However, because information is so diverse, acquiring and utilizing it is not easy. Furthermore, language barriers in multilingual environments also hinder communication among residents. There is a need to address these challenges and provide support systems that enable residents to quickly and accurately obtain the information they need for their lives. 【0495】 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. 【0496】 In this invention, the server includes language processing means for receiving and analyzing natural language input from a user, information acquisition means for obtaining relevant information from a rule information repository based on the analyzed information, and urban information provision means for providing information on public facilities and services within the city. This enables residents to quickly and accurately obtain necessary information even in a multilingual environment, making urban life more comfortable. 【0497】 "Residential facilities" refer primarily to buildings and their surrounding environments used by people for their daily lives. 【0498】 "Urban management" refers to activities that operate and maintain urban infrastructure and public services to make citizens' lives comfortable and efficient. 【0499】 "Artificial intelligence assistance" refers to providing technology that enables computers to mimic human intellectual activity and automate information processing and decision-making. 【0500】 "Language processing means" refers to technologies and programs that analyze natural language input from users and understand their intent. 【0501】 "Information acquisition means" refers to the technologies and methods used to search for and acquire necessary data from information sources based on analyzed information. 【0502】 "Response generation means" refers to technologies and programs that create answers in a user-friendly format based on acquired information. 【0503】 "Response transmission means" refers to the technology and procedures for sending the generated response to the user's computer terminal. 【0504】 "Urban information provision methods" refer to systems and technologies for collecting information on public facilities and services within a city and providing it to residents. 【0505】 In the system implementing this invention, to provide information about residential facilities and urban areas, the user first inputs a question in natural language using an application on their terminal. The user's terminal receives this input as digital data and sends it to a server via the internet. The server analyzes the input received from the user using a natural language processing platform to understand the user's intent. In this process, online natural language processing services such as Google Cloud NLP are often used. 【0506】 Based on the analyzed information, the server retrieves relevant information from the rules database and also refers to the city information database, which includes information about the city's public facilities and services. Based on the retrieved data, the response generation module creates a user-friendly response and formats it in a format suitable for the user's language. 【0507】 Ultimately, the server sends this generated response to the user's terminal, allowing the user to obtain the necessary information in real time by viewing it. This enables users to quickly and accurately obtain the information they need for urban life, even in a multilingual environment. 【0508】 For example, if a user asks, "What local events are happening this week?", the server will refer to the event schedule database and generate a response such as, "There is a music festival at the city park this weekend." A possible prompt for the generating AI model could be in the form of, "Please receive a question from a citizen, analyze the information necessary to provide accurate information about events and public services using natural language processing technology, and generate an appropriate response in Japanese." 【0509】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0510】 Step 1: 【0511】 The user launches the application using their device and enters a question in natural language, such as "What are the local events this week?". The entered question is received on the device as text data. 【0512】 Step 2: 【0513】 The terminal transfers the received text data to the server via the internet. Upon receiving the input data, the server receives the data and prepares for the next processing step. HTTPS communication is used for sending and receiving data. 【0514】 Step 3: 【0515】 The server analyzes the received text data using a natural language processing platform such as Google Cloud NLP. Specifically, it extracts keywords from the input data and understands the intent of the question. In this case, the keywords extracted are "local events" and "this week." The analyzed intent data is then generated as output. 【0516】 Step 4: 【0517】 Based on the analysis results, the server queries the database where the event schedule is stored. For example, it searches the database for event information relevant to this week and extracts the relevant information. As a result, the event information extracted from the database (e.g., "There will be a music festival at the city park this weekend") is output. 【0518】 Step 5: 【0519】 The response generation module on the server generates a response tailored to the user's language based on the extracted event information. This response is then output as data formatted in a natural language format that is easy to understand. 【0520】 Step 6: 【0521】 The server sends the formatted answer data to the user's device. The user's device receives this data and displays it on the application's user interface. This allows the user to obtain answers to questions quickly and accurately. 【0522】 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. 【0523】 This invention provides more personalized responses by incorporating an emotion engine that recognizes user emotions into an artificial intelligence assistant system specifically designed for managing residential facilities. This system generates appropriate responses to user questions and requests, and further adjusts its response method according to the user's emotional state, thereby enabling smooth communication. 【0524】 Users input questions and requests into the system using natural language via a terminal. The terminal converts this information into a digital format and sends it to the server. Upon receiving the input, the server first analyzes the input text using natural language processing to understand its content and identify the user's intent. Next, based on the analysis results, it accesses a rule database to retrieve relevant information. 【0525】 The server incorporates an emotion engine that analyzes user emotions based on their input text. This process uses textual expressions, linguistic features, and past interaction history to identify the user's emotional state. The identified emotions influence the response generation process, which is used to adjust the tone and wording of the response. For example, if a user is expressing dissatisfaction, the system can generate a more polite and empathetic response. 【0526】 As a concrete example, consider a case where a user inputs, "I am dissatisfied with the recent actions of the board of directors." The server extracts the emotion of "dissatisfaction" through natural language processing. After referring to the rules database and obtaining information about the board's actions, the emotion engine takes this dissatisfaction into consideration and generates empathetic content such as, "We understand how you feel. We can also bring this up on the agenda for the next board meeting." 【0527】 Finally, the server sends the generated response to the terminal, which then displays it to the user. In this way, the user can receive a personalized, emotionally responsive response tailored to their individual situation. The history of the interaction is also stored in a database and used to improve future responses. 【0528】 This system can improve the quality of communication in the management of residential facilities and increase user satisfaction. 【0529】 The following describes the processing flow. 【0530】 Step 1: 【0531】 The user inputs questions or opinions in natural language through their device. For example, they might type, "I am dissatisfied with the board's latest decision." The device then prepares to send this text data to the server. 【0532】 Step 2: 【0533】 The terminal sends user input to the server in digital format. The data is formatted to ensure it reaches the server without errors. 【0534】 Step 3: 【0535】 The server analyzes the received data using a natural language processing engine. It extracts important keywords and intentions from the input text and identifies the focus of questions and opinions. 【0536】 Step 4: 【0537】 The server passes the input text to the sentiment engine, which analyzes the user's emotions. It detects words and expressions in the text that indicate emotions and identifies the user's emotional state (e.g., dissatisfaction, excitement, joy, etc.). 【0538】 Step 5: 【0539】 The server queries the rule database based on the analysis results. It retrieves information about the user's intent and the latest decisions, and collects the data necessary for the response. 【0540】 Step 6: 【0541】 Based on the information and emotional state collected by the server, a response generation engine is used to format the response to the user. The response is created in an emotionally sensitive tone, with specific and considerate content. For example, it might generate a response such as, "I understand your dissatisfaction. We can propose this as an agenda item at the next board meeting." 【0542】 Step 7: 【0543】 The server sends the generated response to the terminal. The data format is adjusted so that the response is easily understood by the user. 【0544】 Step 8: 【0545】 The device displays the received response on the screen. Through this response, the user can feel that the system understands their emotions and is responding appropriately. 【0546】 Step 9: 【0547】 The server stores user interactions in a database. This allows for improved response accuracy in future interactions and a deeper understanding of user preferences. 【0548】 (Example 2) 【0549】 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." 【0550】 In managing residential facilities, there is a need to provide accurate and emotionally sensitive responses to complex questions and requests from users. Furthermore, challenges exist in multilingual environments and in appropriately recognizing user emotions. 【0551】 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. 【0552】 In this invention, the server includes information processing means, information acquisition means, information generation means, information transmission means, and information analysis means. This makes it possible to personalize responses while taking user emotions into consideration and improve the quality of communication in the management of residential facilities. 【0553】 "Information processing means" refers to a method for analyzing natural language input from users and understanding their intent and content. 【0554】 "Information acquisition means" refers to the means of obtaining related information from a rule database based on the analyzed information. 【0555】 "Information generation means" refers to means for appropriately formatting acquired information and generating a response to the user. 【0556】 "Information transmission means" refers to a means of communicating the generated response to the user. 【0557】 "Information analysis means" refers to methods for analyzing the emotions based on user input and adjusting the tone and wording of responses. 【0558】 The present invention relates to an artificial intelligence assistant system specifically designed for the management of residential facilities, which accurately analyzes user input and provides responses that take emotions into consideration. This system includes information processing means, information acquisition means, information generation means, information transmission means, and information analysis means. 【0559】 First, the user inputs questions or requests in natural language via a terminal. This input is converted into text format using speech recognition software. Specific software options include open-source speech recognition engines and commercial voice input tools. The converted input is then sent to a server via the network. 【0560】 The server analyzes the input text using information processing tools. This analysis employs a natural language processing (NLP) engine, such as Google's Dialogflow or an open-source language analysis library. In this step, the user's intent is identified, and necessary information is retrieved from a rules database. 【0561】 Furthermore, the server incorporates an emotion engine as a means of information analysis. This analyzes the user's emotional state from their input, taking into account past conversation history and other factors. The analysis results are then reflected in the process of generating responses using a generative AI model. Here, the tone and wording of the responses are adjusted to generate appropriate feedback for the user. 【0562】 A concrete example of a prompt is: "Create a prompt that generates an empathetic response when a user expresses dissatisfaction with the management of their residential facility." Based on this prompt, the generation AI model generates the necessary response. 【0563】 Finally, the server sends this response to the terminal. The terminal displays the received response to the user, allowing the user to receive accurate and emotionally sensitive information. This system makes it possible to improve the quality of communication and user satisfaction in the management of residential facilities. 【0564】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0565】 Step 1: 【0566】 Users input questions and requests regarding the management of their residential facilities into the terminal using natural language. This input can be either text or voice. In the case of voice input, the terminal uses speech recognition software to convert it into text. It receives natural language data as input and obtains text data as output. 【0567】 Step 2: 【0568】 The terminal sends the input text data to the server. The transmitted data is used as information to analyze the user's requests and intentions. The input is text data transferred to the server, and the output is the transmission of data to the server. 【0569】 Step 3: 【0570】 The server uses a natural language processing (NLP) engine to analyze text data as an information processing tool. Specifically, it tokenizes the text and performs syntactic analysis to identify the user's intent. Based on the text data received as input, it extracts intent and key information to obtain the analysis results as output. 【0571】 Step 4: 【0572】 The server retrieves relevant information from the rules database based on the analyzed data. Here, it executes database queries as needed to extract appropriate information regarding the management of residential facilities. The input is the analysis result, and the output is the retrieved relevant information. 【0573】 Step 5: 【0574】 The server uses the acquired information to generate a response through a generative AI model. It utilizes an emotion engine to adjust the response to a tone that takes the user's emotional state into account. The input is the acquired information and the emotion analysis results, and the output is the adjusted response. 【0575】 Step 6: 【0576】 The server's role is to return information to the user by sending the generated response to the terminal. The input is the generated response, and the output is the sending of the response to the terminal. 【0577】 Step 7: 【0578】 The terminal displays the received response to the user. This allows the user to review the information and suggestions received from the system and decide on their next action. The input is response data from the server, and the output is a response display in a format that the user can easily understand. 【0579】 (Application Example 2) 【0580】 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." 【0581】 Communication with residents in residential facilities and urban areas goes beyond mere information exchange; it requires understanding residents' feelings and intentions, and responding to individual situations. This project aims to build a system that provides efficient and empathetic responses in dialogue with residents, thereby improving their living environment and increasing their satisfaction. 【0582】 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. 【0583】 In this invention, the server includes language processing means, information acquisition means, response generation means, response transmission means, and emotion recognition means. This enables the server to receive feedback on residential facilities and urban functions, and to understand and respond in accordance with emotions. 【0584】 "Residential facilities" refer to buildings used by people to live and work, and include spaces such as houses and public facilities. 【0585】 An "artificial intelligence assistant" is a system with intelligence that provides information in response to human instructions and questions, and assists with tasks. 【0586】 "Natural language" refers to the words and sentences that humans use on a daily basis, and is a linguistic form that is subject to machine processing. 【0587】 "Language processing means" refers to a device or process that has the technology to automatically analyze information from text or audio and understand its meaning. 【0588】 "Information acquisition means" refers to technologies and devices for collecting necessary data and information from external databases and information sources. 【0589】 "Response generation means" refers to a technology or device that constructs an appropriate response for the user based on acquired information and analysis results. 【0590】 "Response transmission means" refers to a technology or device for transmitting the generated response to the user's terminal. 【0591】 "Emotion recognition means" refers to a technology or device for analyzing and estimating an emotional state from user input. 【0592】 "Data management means" refers to technology or equipment used to accumulate the history of interactions and to improve future responses. 【0593】 "Language translation" is a technology that automatically converts spoken language and text to enable communication between different languages. 【0594】 This invention is a system for optimizing communication with residents in residential facilities and cities. The server receives user input and analyzes it using language processing means. The analyzed data is then used by information acquisition means to search and retrieve relevant information from a rule database. In this process, the Google Cloud Natural Language API is used for text analysis, and the acquired information is managed using Amazon RDS. 【0595】 The acquired information is formatted in the user's language by a response generation system to construct an appropriate response. IBM Watson Tone Analyzer is used for this response generation, and in conjunction with emotion recognition systems, it analyzes the user's emotional state and adjusts the response tone. 【0596】 The terminal sends the generated response to the user, ensuring that the user receives information and suggestions smoothly. For example, if a user reports, "Garbage collection has been slow lately," the system recognizes the user's dissatisfaction and generates an empathetic response such as, "We value your feedback. We will promptly arrange for improvements to the garbage collection schedule." 【0597】 An example of a prompt is: "Show how a user support system for a residential facility management AI in a smart city generates a response that includes empathy and steps toward resolution in response to a message expressing dissatisfaction." 【0598】 This system allows for the effective collection of resident feedback, which can contribute to improving urban functions. 【0599】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0600】 Step 1: 【0601】 The user sends natural language input to the system via a device such as a smartphone. This input is transmitted to the server as an initial request or question. The server receives the input and prepares for the next analysis process. 【0602】 Step 2: 【0603】 The server analyzes the natural language text received using the Google Cloud Natural Language API. It breaks down the input text, understands its structure and content, and then identifies the user's intent. This process extracts semantic elements from the text, preparing it for information retrieval. 【0604】 Step 3: 【0605】 Based on the analyzed information, the server accesses Amazon RDS using information retrieval methods to search for and retrieve relevant information from the rules database. Feedback and specific data are extracted from the database, providing the necessary materials for generating a response. 【0606】 Step 4: 【0607】 The server performs sentiment analysis based on information obtained using IBM Watson Tone Analyzer. It identifies the emotional state from the user's statements and adjusts the tone of the response through sentiment recognition. At this stage, the emotional tone of the response is determined. 【0608】 Step 5: 【0609】 The server constructs an appropriate response using a response generation mechanism. The response, formatted in the user's language, is generated by taking into account the acquired information and sentiment analysis results. This response is then compiled into a specific text. 【0610】 Step 6: 【0611】 The server sends the generated response to the terminal. Immediate feedback is provided to the user via the response transmission mechanism. The generated response is displayed on the user's terminal, allowing the user to confirm the system's response. 【0612】 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. 【0613】 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. 【0614】 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. 【0615】 [Fourth Embodiment] 【0616】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0617】 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. 【0618】 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). 【0619】 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. 【0620】 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. 【0621】 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). 【0622】 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. 【0623】 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. 【0624】 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. 【0625】 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. 【0626】 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. 【0627】 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. 【0628】 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". 【0629】 The following configuration is adopted as an embodiment for carrying out the present invention. An artificial intelligence assistant specialized for the management of residential facilities is realized by a system that communicates between the user and the server. 【0630】 The user uses a terminal to input questions about the operation and rules of the residential facility in natural language. The terminal converts this input into an appropriate data format and sends it to the server. The server analyzes the received data using natural language processing technology to identify the language of the input text and understand its intent. For example, if a user asks about the garbage disposal rules of an apartment building, "garbage disposal" and "rules" will be analyzed. 【0631】 The server queries the rule database based on the analyzed information to retrieve the necessary data. Then, the response generation module uses the retrieved information to generate a response formatted appropriately in the user's language. For example, it might create a response such as, "Please put out your trash every Monday and Thursday morning." 【0632】 The generated response is sent from the server to the terminal and displayed to the user on the terminal. This allows the user to obtain information that is formed in real time. Furthermore, the server stores the history of the interaction in a database, which is used to improve accuracy in future interactions and to provide customized responses that are suitable for individual users. 【0633】 As a concrete example, consider a case where a user enters "What is the date of the next board meeting?". The server analyzes this question and determines that date information is needed. Next, the server consults the board meeting schedule database and retrieves the information for the next meeting date. Finally, using the retrieved information, it generates and sends a response to the user stating, "The next board meeting will be held on October 10, 2023." 【0634】 Thus, the present invention effectively and efficiently provides information that meets the diverse needs in the management of residential facilities, thereby enabling smooth communication among residents and improving the efficiency of management operations. 【0635】 The following describes the processing flow. 【0636】 Step 1: 【0637】 The user inputs questions or requests in natural language using a terminal. For example, they might input, "What are the operating hours for the shared facilities in the apartment building?" The terminal converts this input into digital data and formats it into a format that can be sent to the server. 【0638】 Step 2: 【0639】 The terminal sends user input data to the server. Following the data communication protocol, encoding and other necessary processes are performed to ensure the data is delivered without errors. 【0640】 Step 3: 【0641】 The server passes the data received from the terminal to a natural language processing module. Here, the language of the text is identified and intent analysis is performed. The focus of the user's question, "usage time for shared facilities," is identified. 【0642】 Step 4: 【0643】 The server retrieves relevant information from the rules database based on the analysis results. Specifically, it searches for data regarding the usage times of the apartment building's shared facilities and extracts the relevant information. 【0644】 Step 5: 【0645】 The server uses a response generation module to format the acquired information in a way that is easy for the user to understand. Based on the user's language settings, it generates a multilingual response. For example, it might say, "Shared facilities are available from 9 AM to 9 PM." 【0646】 Step 6: 【0647】 The server sends the generated response to the user's terminal. At this stage, the response data is sent in a format that can be interpreted by the terminal, according to the transfer protocol. 【0648】 Step 7: 【0649】 The device displays the responses it receives to the user. This visualizes the responses on the display, allowing the user to verify the answers to the questions they entered. 【0650】 Step 8: 【0651】 The server stores a series of interactions with the user in a database. This data is used to analyze customer preferences and inquiry trends, and to improve the accuracy of AI models. 【0652】 (Example 1) 【0653】 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". 【0654】 In managing residential areas, users are required to be able to ask questions and make requests in various languages, and to receive information quickly and accurately. However, conventional systems have challenges in smooth communication between languages ​​during information processing and language translation, and furthermore, they do not adequately improve response accuracy by utilizing history. 【0655】 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. 【0656】 In this invention, the server includes information analysis means, information acquisition means, response generation means, data conversion means, history storage means, and a translation function. This enables quick and accurate responses to user inquiries, improved response accuracy through the use of history, and information exchange between multiple languages. 【0657】 A "knowledge processing device" refers to an entire system for performing information processing for the purpose of managing a residential area. 【0658】 "User" refers to a person who uses a knowledge processing device to inquire about information and management related to their living area. 【0659】 "Natural language" refers to the forms of language and writing that humans use on a daily basis, and is not a specific programming language. 【0660】 "Information analysis means" refers to a function that analyzes natural language input received from users and understands their intent. 【0661】 A "rule storage device" refers to a database that holds rules and regulations related to a residential area. 【0662】 "Information acquisition means" refers to the function of extracting necessary information from the rule storage device based on the results of analysis performed by the information analysis means. 【0663】 "Response generation means" refers to a function that organizes acquired information according to the user's language and needs and generates an appropriate response. 【0664】 "Response transmission means" refers to the functions and processes for delivering the generated response to the user. 【0665】 "Data conversion means" refers to a function that converts user input into a digital format and prepares it for processing within the system. 【0666】 "History saving means" refers to a function that saves past interactions with users and uses this information to improve the accuracy of future responses. 【0667】 A "translation function" refers to a feature that plays the role of converting languages ​​to enable smooth communication between multiple languages. 【0668】 A "generative AI model" refers to a model that utilizes artificial intelligence technology to recognize patterns through learning and generate responses. 【0669】 This invention provides a knowledge processing device specifically designed for managing residential areas, and is primarily composed of a user, a terminal, and a server. Specific embodiments are described below. 【0670】 Users input inquiries about managing their living area and related information into the terminal using natural language. For example, they might input, "Please tell me the garbage collection day." The terminal converts the received natural language input into digital data, formats it appropriately, and sends it to the server. 【0671】 The server uses a generative AI model and information analysis tools to analyze data sent by the user and understand their intent. After the analysis is complete, it retrieves relevant information from the rule storage device via an information retrieval tool. Here, information from the database is used to retrieve specific information, such as "Garbage collection days are Monday and Thursday." 【0672】 The acquired information is organized according to the user's language by a response generation mechanism on the server, generating a natural-sounding response. This process also utilizes generative AI model technology. For example, in response to a user's question, the response "The next garbage collection days are Monday and Thursday mornings" is generated. 【0673】 The generated response is sent from the server to the terminal, allowing the user to receive information in real time. The terminal is responsible for displaying the received information to the user. The server also saves a history of interactions with the user and uses this history for future communications. This allows the server to provide more accurate and personalized responses based on past interactions. 【0674】 Furthermore, if multilingual support is required, the server utilizes translation capabilities to enable communication between different languages. For example, it can generate answers in Japanese to questions asked in English. 【0675】 As described above, the present invention uses a generative AI model and natural language processing technology with prompt statements to realize an effective and efficient information provision system that meets the diverse needs in the management of residential areas. A concrete example of a prompt statement is the instruction, "Please enter your question regarding the management of residential facilities in natural language." 【0676】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0677】 Step 1: 【0678】 Users input questions and requests related to their residential area into the terminal using natural language. This input is captured as natural language text data for conversion into a digital format. For example, they might input something like, "I want to know the reservation status of the meeting rooms." 【0679】 Step 2: 【0680】 The terminal processes the input text data and converts it into a data format that can be sent to the server. This step involves converting the text's character encoding and formatting it to a protocol-compliant format. As output, the formatted string is sent to the server. 【0681】 Step 3: 【0682】 The server analyzes the formatted data received from the terminal. Using a generative AI model and natural language processing techniques, it extracts the intent and important keywords of the text to understand its content. In this case, it identifies keywords such as "meeting room rental" and "reservation status" from the text to grasp the main point of the question. 【0683】 Step 4: 【0684】 Based on the analyzed information, the server queries the rule storage device to retrieve relevant information. For example, it might refer to a database showing the "reservation status of meeting rooms" and extract availability and reservation status. Based on these results, it organizes the necessary information. 【0685】 Step 5: 【0686】 The server uses response generation tools to convert the acquired information into a language and format that is easy for the user to understand. The generation AI model produces natural-sounding sentences that fit the specific context. As output, appropriate sentences such as "The meeting room is available from 2 PM today" are created. 【0687】 Step 6: 【0688】 The server sends the generated response to the terminal. The terminal then displays the received information to the user. The user can then view the information displayed on the terminal and receive real-time guidance. 【0689】 Step 7: 【0690】 The server saves the history of interactions to a database using a history retention mechanism. This history is used to improve the accuracy of responses to similar questions in subsequent communications. Furthermore, if multilingual responses are required, a translation function is used. 【0691】 (Application Example 1) 【0692】 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". 【0693】 In modern urban life, residents seek efficient ways to obtain information about their daily lives. However, because information is so diverse, acquiring and utilizing it is not easy. Furthermore, language barriers in multilingual environments also hinder communication among residents. There is a need to address these challenges and provide support systems that enable residents to quickly and accurately obtain the information they need for their lives. 【0694】 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. 【0695】 In this invention, the server includes language processing means for receiving and analyzing natural language input from a user, information acquisition means for obtaining relevant information from a rule information repository based on the analyzed information, and urban information provision means for providing information on public facilities and services within the city. This enables residents to quickly and accurately obtain necessary information even in a multilingual environment, making urban life more comfortable. 【0696】 "Residential facilities" refer primarily to buildings and their surrounding environments used by people for their daily lives. 【0697】 "Urban management" refers to activities that operate and maintain urban infrastructure and public services to make citizens' lives comfortable and efficient. 【0698】 "Artificial intelligence assistance" refers to providing technology that enables computers to mimic human intellectual activity and automate information processing and decision-making. 【0699】 "Language processing means" refers to technologies and programs that analyze natural language input from users and understand their intent. 【0700】 "Information acquisition means" refers to the technologies and methods used to search for and acquire necessary data from information sources based on analyzed information. 【0701】 "Response generation means" refers to technologies and programs that create answers in a user-friendly format based on acquired information. 【0702】 "Response transmission means" refers to the technology and procedures for sending the generated response to the user's computer terminal. 【0703】 "Urban information provision methods" refer to systems and technologies for collecting information on public facilities and services within a city and providing it to residents. 【0704】 In the system implementing this invention, to provide information about residential facilities and urban areas, the user first inputs a question in natural language using an application on their terminal. The user's terminal receives this input as digital data and sends it to a server via the internet. The server analyzes the input received from the user using a natural language processing platform to understand the user's intent. In this process, online natural language processing services such as Google Cloud NLP are often used. 【0705】 Based on the analyzed information, the server retrieves relevant information from the rules database and also refers to the city information database, which includes information about the city's public facilities and services. Based on the retrieved data, the response generation module creates a user-friendly response and formats it in a format suitable for the user's language. 【0706】 Ultimately, the server sends this generated response to the user's terminal, allowing the user to obtain the necessary information in real time by viewing it. This enables users to quickly and accurately obtain the information they need for urban life, even in a multilingual environment. 【0707】 For example, if a user asks, "What local events are happening this week?", the server will refer to the event schedule database and generate a response such as, "There is a music festival at the city park this weekend." A possible prompt for the generating AI model could be in the form of, "Please receive a question from a citizen, analyze the information necessary to provide accurate information about events and public services using natural language processing technology, and generate an appropriate response in Japanese." 【0708】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0709】 Step 1: 【0710】 The user launches the application using their device and enters a question in natural language, such as "What are the local events this week?". The entered question is received on the device as text data. 【0711】 Step 2: 【0712】 The terminal transfers the received text data to the server via the internet. Upon receiving the input data, the server receives the data and prepares for the next processing step. HTTPS communication is used for sending and receiving data. 【0713】 Step 3: 【0714】 The server analyzes the received text data using a natural language processing platform such as Google Cloud NLP. Specifically, it extracts keywords from the input data and understands the intent of the question. In this case, the keywords extracted are "local events" and "this week." The analyzed intent data is then generated as output. 【0715】 Step 4: 【0716】 Based on the analysis results, the server queries the database where the event schedule is stored. For example, it searches the database for event information relevant to this week and extracts the relevant information. As a result, the event information extracted from the database (e.g., "There will be a music festival at the city park this weekend") is output. 【0717】 Step 5: 【0718】 The response generation module on the server generates a response tailored to the user's language based on the extracted event information. This response is then output as data formatted in a natural language format that is easy to understand. 【0719】 Step 6: 【0720】 The server sends the formatted answer data to the user's device. The user's device receives this data and displays it on the application's user interface. This allows the user to obtain answers to questions quickly and accurately. 【0721】 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. 【0722】 This invention provides more personalized responses by incorporating an emotion engine that recognizes user emotions into an artificial intelligence assistant system specifically designed for managing residential facilities. This system generates appropriate responses to user questions and requests, and further adjusts its response method according to the user's emotional state, thereby enabling smooth communication. 【0723】 Users input questions and requests into the system using natural language via a terminal. The terminal converts this information into a digital format and sends it to the server. Upon receiving the input, the server first analyzes the input text using natural language processing to understand its content and identify the user's intent. Next, based on the analysis results, it accesses a rule database to retrieve relevant information. 【0724】 The server incorporates an emotion engine that analyzes user emotions based on their input text. This process uses textual expressions, linguistic features, and past interaction history to identify the user's emotional state. The identified emotions influence the response generation process, which is used to adjust the tone and wording of the response. For example, if a user is expressing dissatisfaction, the system can generate a more polite and empathetic response. 【0725】 As a concrete example, consider a case where a user inputs, "I am dissatisfied with the recent actions of the board of directors." The server extracts the emotion of "dissatisfaction" through natural language processing. After referring to the rules database and obtaining information about the board's actions, the emotion engine takes this dissatisfaction into consideration and generates empathetic content such as, "We understand how you feel. We can also bring this up on the agenda for the next board meeting." 【0726】 Finally, the server sends the generated response to the terminal, which then displays it to the user. In this way, the user can receive a personalized, emotionally responsive response tailored to their individual situation. The history of the interaction is also stored in a database and used to improve future responses. 【0727】 This system can improve the quality of communication in the management of residential facilities and increase user satisfaction. 【0728】 The following describes the processing flow. 【0729】 Step 1: 【0730】 The user inputs questions or opinions in natural language through their device. For example, they might type, "I am dissatisfied with the board's latest decision." The device then prepares to send this text data to the server. 【0731】 Step 2: 【0732】 The terminal sends user input to the server in digital format. The data is formatted to ensure it reaches the server without errors. 【0733】 Step 3: 【0734】 The server analyzes the received data using a natural language processing engine. It extracts important keywords and intentions from the input text and identifies the focus of questions and opinions. 【0735】 Step 4: 【0736】 The server passes the input text to the sentiment engine, which analyzes the user's emotions. It detects words and expressions in the text that indicate emotions and identifies the user's emotional state (e.g., dissatisfaction, excitement, joy, etc.). 【0737】 Step 5: 【0738】 The server queries the rule database based on the analysis results. It retrieves information about the user's intent and the latest decisions, and collects the data necessary for the response. 【0739】 Step 6: 【0740】 Based on the information and emotional state collected by the server, a response generation engine is used to format the response to the user. The response is created in an emotionally sensitive tone, with specific and considerate content. For example, it might generate a response such as, "I understand your dissatisfaction. We can propose this as an agenda item at the next board meeting." 【0741】 Step 7: 【0742】 The server sends the generated response to the terminal. The data format is adjusted so that the response is easily understood by the user. 【0743】 Step 8: 【0744】 The device displays the received response on the screen. Through this response, the user can feel that the system understands their emotions and is responding appropriately. 【0745】 Step 9: 【0746】 The server stores user interactions in a database. This allows for improved response accuracy in future interactions and a deeper understanding of user preferences. 【0747】 (Example 2) 【0748】 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". 【0749】 In managing residential facilities, there is a need to provide accurate and emotionally sensitive responses to complex questions and requests from users. Furthermore, challenges exist in multilingual environments and in appropriately recognizing user emotions. 【0750】 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. 【0751】 In this invention, the server includes information processing means, information acquisition means, information generation means, information transmission means, and information analysis means. This makes it possible to personalize responses while taking user emotions into consideration and improve the quality of communication in the management of residential facilities. 【0752】 "Information processing means" refers to a method for analyzing natural language input from users and understanding their intent and content. 【0753】 "Information acquisition means" refers to the means of obtaining related information from a rule database based on the analyzed information. 【0754】 "Information generation means" refers to means for appropriately formatting acquired information and generating a response to the user. 【0755】 "Information transmission means" refers to a means of communicating the generated response to the user. 【0756】 "Information analysis means" refers to methods for analyzing the emotions based on user input and adjusting the tone and wording of responses. 【0757】 The present invention relates to an artificial intelligence assistant system specifically designed for the management of residential facilities, which accurately analyzes user input and provides responses that take emotions into consideration. This system includes information processing means, information acquisition means, information generation means, information transmission means, and information analysis means. 【0758】 First, the user inputs questions or requests in natural language via a terminal. This input is converted into text format using speech recognition software. Specific software options include open-source speech recognition engines and commercial voice input tools. The converted input is then sent to a server via the network. 【0759】 The server analyzes the input text using information processing tools. This analysis employs a natural language processing (NLP) engine, such as Google's Dialogflow or an open-source language analysis library. In this step, the user's intent is identified, and necessary information is retrieved from a rules database. 【0760】 Furthermore, the server incorporates an emotion engine as a means of information analysis. This analyzes the user's emotional state from their input, taking into account past conversation history and other factors. The analysis results are then reflected in the process of generating responses using a generative AI model. Here, the tone and wording of the responses are adjusted to generate appropriate feedback for the user. 【0761】 A concrete example of a prompt is: "Create a prompt that generates an empathetic response when a user expresses dissatisfaction with the management of their residential facility." Based on this prompt, the generation AI model generates the necessary response. 【0762】 Finally, the server sends this response to the terminal. The terminal displays the received response to the user, allowing the user to receive accurate and emotionally sensitive information. This system makes it possible to improve the quality of communication and user satisfaction in the management of residential facilities. 【0763】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0764】 Step 1: 【0765】 Users input questions and requests regarding the management of their residential facilities into the terminal using natural language. This input can be either text or voice. In the case of voice input, the terminal uses speech recognition software to convert it into text. It receives natural language data as input and obtains text data as output. 【0766】 Step 2: 【0767】 The terminal sends the input text data to the server. The transmitted data is used as information to analyze the user's requests and intentions. The input is text data transferred to the server, and the output is the transmission of data to the server. 【0768】 Step 3: 【0769】 The server uses a natural language processing (NLP) engine to analyze text data as an information processing tool. Specifically, it tokenizes the text and performs syntactic analysis to identify the user's intent. Based on the text data received as input, it extracts intent and key information to obtain the analysis results as output. 【0770】 Step 4: 【0771】 The server retrieves relevant information from the rules database based on the analyzed data. Here, it executes database queries as needed to extract appropriate information regarding the management of residential facilities. The input is the analysis result, and the output is the retrieved relevant information. 【0772】 Step 5: 【0773】 The server uses the acquired information to generate a response through a generative AI model. It utilizes an emotion engine to adjust the response to a tone that takes the user's emotional state into account. The input is the acquired information and the emotion analysis results, and the output is the adjusted response. 【0774】 Step 6: 【0775】 The server's role is to return information to the user by sending the generated response to the terminal. The input is the generated response, and the output is the sending of the response to the terminal. 【0776】 Step 7: 【0777】 The terminal displays the received response to the user. This allows the user to review the information and suggestions received from the system and decide on their next action. The input is response data from the server, and the output is a response display in a format that the user can easily understand. 【0778】 (Application Example 2) 【0779】 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". 【0780】 Communication with residents in residential facilities and urban areas goes beyond mere information exchange; it requires understanding residents' feelings and intentions, and responding to individual situations. This project aims to build a system that provides efficient and empathetic responses in dialogue with residents, thereby improving their living environment and increasing their satisfaction. 【0781】 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. 【0782】 In this invention, the server includes language processing means, information acquisition means, response generation means, response transmission means, and emotion recognition means. This enables the server to receive feedback on residential facilities and urban functions, and to understand and respond in accordance with emotions. 【0783】 "Residential facilities" refer to buildings used by people to live and work, and include spaces such as houses and public facilities. 【0784】 An "artificial intelligence assistant" is a system with intelligence that provides information in response to human instructions and questions, and assists with tasks. 【0785】 "Natural language" refers to the words and sentences that humans use on a daily basis, and is a linguistic form that is subject to machine processing. 【0786】 "Language processing means" refers to a device or process that has the technology to automatically analyze information from text or audio and understand its meaning. 【0787】 "Information acquisition means" refers to technologies and devices for collecting necessary data and information from external databases and information sources. 【0788】 "Response generation means" refers to a technology or device that constructs an appropriate response for the user based on acquired information and analysis results. 【0789】 "Response transmission means" refers to a technology or device for transmitting the generated response to the user's terminal. 【0790】 "Emotion recognition means" refers to a technology or device for analyzing and estimating an emotional state from user input. 【0791】 "Data management means" refers to technology or equipment used to accumulate the history of interactions and to improve future responses. 【0792】 "Language translation" is a technology that automatically converts spoken language and text to enable communication between different languages. 【0793】 This invention is a system for optimizing communication with residents in residential facilities and cities. The server receives user input and analyzes it using language processing means. The analyzed data is then used by information acquisition means to search and retrieve relevant information from a rule database. In this process, the Google Cloud Natural Language API is used for text analysis, and the acquired information is managed using Amazon RDS. 【0794】 The acquired information is formatted in the user's language by a response generation system to construct an appropriate response. IBM Watson Tone Analyzer is used for this response generation, and in conjunction with emotion recognition systems, it analyzes the user's emotional state and adjusts the response tone. 【0795】 The terminal sends the generated response to the user, ensuring that the user receives information and suggestions smoothly. For example, if a user reports, "Garbage collection has been slow lately," the system recognizes the user's dissatisfaction and generates an empathetic response such as, "We value your feedback. We will promptly arrange for improvements to the garbage collection schedule." 【0796】 An example of a prompt is: "Show how a user support system for a residential facility management AI in a smart city generates a response that includes empathy and steps toward resolution in response to a message expressing dissatisfaction." 【0797】 This system allows for the effective collection of resident feedback, which can contribute to improving urban functions. 【0798】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0799】 Step 1: 【0800】 The user sends natural language input to the system via a device such as a smartphone. This input is transmitted to the server as an initial request or question. The server receives the input and prepares for the next analysis process. 【0801】 Step 2: 【0802】 The server analyzes the natural language text received using the Google Cloud Natural Language API. It breaks down the input text, understands its structure and content, and then identifies the user's intent. This process extracts semantic elements from the text, preparing it for information retrieval. 【0803】 Step 3: 【0804】 Based on the analyzed information, the server accesses Amazon RDS using information retrieval methods to search for and retrieve relevant information from the rules database. Feedback and specific data are extracted from the database, providing the necessary materials for generating a response. 【0805】 Step 4: 【0806】 The server performs sentiment analysis based on information obtained using IBM Watson Tone Analyzer. It identifies the emotional state from the user's statements and adjusts the tone of the response through sentiment recognition. At this stage, the emotional tone of the response is determined. 【0807】 Step 5: 【0808】 The server constructs an appropriate response using a response generation mechanism. The response, formatted in the user's language, is generated by taking into account the acquired information and sentiment analysis results. This response is then compiled into a specific text. 【0809】 Step 6: 【0810】 The server sends the generated response to the terminal. Immediate feedback is provided to the user via the response transmission mechanism. The generated response is displayed on the user's terminal, allowing the user to confirm the system's response. 【0811】 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. 【0812】 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. 【0813】 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. 【0814】 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. 【0815】 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. 【0816】 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. 【0817】 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. 【0818】 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. 【0819】 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." 【0820】 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. 【0821】 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. 【0822】 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. 【0823】 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. 【0824】 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. 【0825】 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. 【0826】 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. 【0827】 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. 【0828】 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. 【0829】 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. 【0830】 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. 【0831】 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. 【0832】 The following is further disclosed regarding the embodiments described above. 【0833】 (Claim 1) 【0834】 A system that provides an artificial intelligence assistant specifically for managing residential facilities, 【0835】 A natural language processing means for receiving natural language input from a user and analyzing said input, 【0836】 Information acquisition means that acquires relevant information from a rule database based on the analyzed information, 【0837】 A response generation means that formats the acquired information according to the user's language and generates a response, 【0838】 A response transmission means for sending the generated response to the user, 【0839】 A system that includes this. 【0840】 (Claim 2) 【0841】 The system according to claim 1, further comprising a data storage means for accumulating a history of interactions with users and improving the accuracy of responses in subsequent interactions. 【0842】 (Claim 3) 【0843】 The system according to claim 1, further comprising a translation means for performing language translation to support communication between users in multiple languages. 【0844】 "Example 1" 【0845】 (Claim 1) 【0846】 A system that provides a knowledge processing device specifically for managing residential areas, 【0847】 Information analysis means for receiving natural language input from a user and analyzing said input, 【0848】 Information acquisition means that acquires related information from a rule storage device based on the analyzed information, 【0849】 A response generation means that formats the acquired information according to the user's language and generates a response, 【0850】 A response transmission means for sending the generated response to the user, 【0851】 A data conversion means that converts user input into a digital format, 【0852】 A means for saving the history of information exchange to improve the accuracy of responses in the future, 【0853】 A system that includes this. 【0854】 (Claim 2) 【0855】 The system according to claim 1, further comprising a translation function that performs language translation to support information exchange between users in multiple languages. 【0856】 (Claim 3) 【0857】 The system according to claim 1, characterized in that it generates a response using a generative AI model. 【0858】 "Application Example 1" 【0859】 (Claim 1) 【0860】 This system provides AI support specifically for residential facilities and urban management. 【0861】 A language processing means for receiving natural language input from a user and analyzing said input, 【0862】 Information acquisition means that acquires related information from a rule information repository based on the analyzed information, 【0863】 A response generation means that formats the acquired information according to the user's language and generates a response, 【0864】 A response transmission means for transmitting the generated response to a computer terminal, 【0865】 A means of providing urban information for providing information on public facilities and services within a city, 【0866】 A system that includes this. 【0867】 (Claim 2) 【0868】 The system according to claim 1, further comprising a data storage means for accumulating a history of interactions with users and improving the accuracy of responses in subsequent interactions. 【0869】 (Claim 3) 【0870】 The system according to claim 1, further comprising a translation means for performing language conversion to support communication between users in multiple languages. 【0871】 "Example 2 of combining an emotion engine" 【0872】 (Claim 1) 【0873】 Information processing means for receiving natural language input from a user and analyzing said input, 【0874】 Information acquisition means that acquires relevant information from a rule database based on the analyzed information, 【0875】 Information generation means that formats the acquired information according to the user's language and generates a response, 【0876】 Information transmission means for sending the generated response to the user, 【0877】 An information analysis means that analyzes emotions based on user input and adjusts the tone of response, 【0878】 A system that includes this. 【0879】 (Claim 2) 【0880】 The system according to claim 1, further comprising means for accumulating a history of interactions with users and for storing information to improve the accuracy of responses in the future. 【0881】 (Claim 3) 【0882】 The system according to claim 1, further comprising translation means for performing information translation to support communication between users in multiple languages. 【0883】 "Application example 2 when combining with an emotional engine" 【0884】 (Claim 1) 【0885】 A system that provides an artificial intelligence assistant specifically for managing residential facilities, 【0886】 A language processing means for receiving natural language input from a user and analyzing said input, 【0887】 Information acquisition means that acquires relevant information from a rule database based on the analyzed information, 【0888】 A response generation means that formats the acquired information according to the user's language and generates a response, 【0889】 A response transmission means for sending the generated response to the user, 【0890】 An emotion recognition means that analyzes the user's emotional state and adjusts the tone and content of the response according to that state, 【0891】 A system that includes this. 【0892】 (Claim 2) 【0893】 The system according to claim 1, further comprising data management means for accumulating a history of interactions with users and improving the accuracy of responses in the future. 【0894】 (Claim 3) 【0895】 The system according to claim 1, further comprising a translation means for performing language translation to support multilingual communication between users, and capable of performing sentiment analysis in conversations with residents in a city and receiving feedback on urban functions. [Explanation of symbols] 【0896】 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 system that provides an artificial intelligence assistant specifically for managing residential facilities, A natural language processing means for receiving natural language input from a user and analyzing said input, Information acquisition means that acquires relevant information from a rule database based on the analyzed information, A response generation means that formats the acquired information according to the user's language and generates a response, A response transmission means for sending the generated response to the user, A system that includes this. [Claim 2] The system according to claim 1, further comprising a data storage means for accumulating a history of interactions with users and improving the accuracy of responses in subsequent interactions. [Claim 3] The system according to claim 1, further comprising a translation means for performing language translation to support communication between users in multiple languages.

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