system

Abstract

The system according to this embodiment aims to automate and streamline information management, communication, event planning, and accounting operations for neighborhood associations. [Solution] The system according to the embodiment comprises an information management department, a communication department, an event planning department, and an accounting department. The information management department manages information of the neighborhood association. The communication department automates communication based on the information managed by the information management department. The event planning department automates event planning based on the information automated by the communication department. The accounting department automates accounting operations based on the information automated by the event planning department.

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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, there are problems that information management, communication, event planning, accounting operations, etc. of a neighborhood association are carried out manually, with low efficiency and insufficient cooperation among residents.

[0005] The system according to the embodiment aims to automate and improve the efficiency of information management, communication, event planning, and accounting operations of a neighborhood association.

Means for Solving the Problems

[0006] The system according to this embodiment comprises an Information Management Department, a Communication Department, an Event Planning Department, and an Accounting Department. The Information Management Department manages information of the neighborhood association. The Communication Department automates communication based on the information managed by the Information Management Department. The Event Planning Department automates event planning based on the information automated by the Communication Department. The Accounting Department automates accounting operations based on the information automated by the Event Planning Department. [Effects of the Invention]

[0007] The system according to this embodiment can automate and streamline information management, communication, event planning, and accounting operations for neighborhood associations. [Brief explanation of the drawing]

[0008] [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 a data processing device and a 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. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

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

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

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

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

[0017] As shown in FIG. 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.

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

[0019] The smart device 14 comprises a computer 36, a receiving 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 receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice 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 unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (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.

[0022] 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.

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

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

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

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

[0028] (Example of form 1) The AI ​​agent system according to an embodiment of the present invention is a system that automates and streamlines information management, communication, event planning, and accounting operations for neighborhood associations. This AI agent system supports the operation of neighborhood associations and strengthens cooperation among residents. The AI ​​agent system centrally manages various types of information of neighborhood associations and provides necessary information quickly. For example, the AI ​​agent system manages meeting minutes and inquiries from residents of neighborhood associations and provides them to residents as needed. This information management ensures the smooth operation of neighborhood associations. Next, the AI ​​agent system uses natural language processing to automatically send emails and bulletin board posts. For example, the AI ​​agent system automatically sends announcements for neighborhood association meetings and event notices. The AI ​​agent system also collects opinions and feedback from residents and reflects them in the operation of neighborhood associations. This facilitates smooth communication among residents. Furthermore, the AI ​​agent system uses machine learning to manage and analyze accounting data. For example, the AI ​​agent system automatically manages the neighborhood association's budget and analyzes expenditures, and creates accounting reports. The AI ​​agent system also automates event scheduling, supporting efficient event management. This will streamline the operation of the neighborhood association and reduce the burden on residents. The AI ​​agent system includes an opinion collection unit that collects residents' opinions and feedback. For example, the AI ​​agent system automates how to conduct surveys and collect feedback. The AI ​​agent system includes a schedule management unit that automates schedule management. For example, the AI ​​agent system automates how to use the calendar and set reminders. The AI ​​agent system includes an information management unit that manages meeting minutes of the neighborhood association and inquiries from residents. For example, the AI ​​agent system automates the format and saving method of meeting minutes. The AI ​​agent system includes a communication unit that uses natural language processing to automatically send emails and bulletin board posts. For example, the AI ​​agent system uses morphological and grammatical analysis to automatically generate email content. The AI ​​agent system includes an event planning unit that automates event schedule management.For example, the AI ​​agent system automatically generates schedules and invites participants. The AI ​​agent system also includes an accounting department that uses machine learning to manage and analyze accounting data. For example, the AI ​​agent system automatically calculates expenses and generates reports. This allows the AI ​​agent system to streamline the operation of neighborhood associations and strengthen cooperation among residents.

[0029] The AI ​​agent system according to this embodiment comprises an Information Management Department, a Communication Department, an Event Planning Department, and an Accounting Department. The Information Management Department manages information of the neighborhood association. For example, the Information Management Department manages minutes of neighborhood association meetings and inquiries from residents. For example, the Information Management Department centrally manages information using a database and provides necessary information quickly. For example, the Information Management Department automatically generates meeting minute formats and automates the saving method. For example, the Information Management Department classifies inquiries and automates the response method. The Communication Department automates communication based on the information managed by the Information Management Department. For example, the Communication Department automatically sends emails and bulletin board posts using natural language processing. For example, the Communication Department automatically generates email content using morphological analysis and grammatical analysis. For example, the Communication Department automatically responds to inquiries from residents using a chatbot. For example, the Communication Department collects opinions and feedback from residents and reflects them in the operation of the neighborhood association. The Event Planning Department automates event planning based on the information automated by the Communication Department. The Event Planning Department automates, for example, event scheduling. The Event Planning Department automatically generates schedules and invites participants. The Event Planning Department automatically generates event content and notifies participants. The Event Planning Department monitors the progress of events in real time and makes adjustments as needed. The Accounting Department automates accounting operations based on the information automated by the Event Planning Department. The Accounting Department manages and analyzes accounting data using machine learning. The Accounting Department automatically calculates expenses and generates reports. The Accounting Department automatically manages budgets and analyzes expenditures and creates accounting reports. The Accounting Department monitors accounting data in real time and issues alerts if anomalies are detected. As a result, the AI ​​agent system according to this embodiment automates and streamlines the information management, communication, event planning, and accounting operations of the community association, thereby ensuring the smooth operation of the community association.

[0030] The Information Management Department manages information for the neighborhood association. Specifically, it manages meeting minutes and inquiries from residents. The Information Management Department uses a database to centrally manage information and quickly provide necessary information. For example, it automatically generates meeting minute formats and automates the saving process. This ensures that meeting contents are accurately recorded and can be easily referenced later. It also categorizes inquiries and automates response methods, enabling quick and appropriate responses to residents' inquiries. The Information Management Department can also use AI to automatically summarize meeting minutes and extract key points. This allows for a quick understanding of meeting contents and enables efficient operation. Furthermore, it uses natural language processing technology to analyze the intent and content of inquiries and classify them into appropriate categories. This enables optimal responses tailored to the content of inquiries. Through these functions, the Information Management Department plays a role in streamlining information management for the neighborhood association and facilitating smooth communication with residents.

[0031] The Communications Department automates communication based on information managed by the Information Management Department. Specifically, it uses natural language processing to automatically send emails and bulletin board posts. For example, it uses morphological and grammatical analysis to automatically generate email content. This allows for the rapid and accurate delivery of information necessary for the operation of the neighborhood association to residents. It also uses a chatbot to automatically respond to inquiries from residents. The chatbot analyzes the content of residents' inquiries and provides appropriate answers. This speeds up responses to residents' inquiries and ensures the smooth operation of the neighborhood association. Furthermore, the Communications Department plays a role in collecting opinions and feedback from residents and reflecting them in the operation of the neighborhood association. For example, it automatically generates and distributes questionnaires to residents to collect their opinions. The collected opinions are analyzed using AI and used to improve the operation of the neighborhood association. This enables operations that reflect residents' opinions, making the activities of the neighborhood association more fulfilling. Through these functions, the Communications Department facilitates communication between the neighborhood association and residents and supports the operation of the neighborhood association.

[0032] The Event Planning Department automates event planning based on information automated by the Communications Department. Specifically, it automates event schedule management, such as automatically generating schedules and inviting participants. This streamlines event planning and ensures quick participant invitations. It also automatically generates event content and notifies participants, ensuring accurate communication and smooth participation. Furthermore, it monitors event progress in real time and makes adjustments as needed. For example, it monitors event progress to ensure it is proceeding according to schedule. If problems arise, it responds quickly to ensure the smooth running of the event. Through these functions, the Event Planning Department streamlines community association event planning and provides an environment that is easy for residents to participate in. This revitalizes community association activities and promotes interaction among residents. The Event Planning Department plays a vital role in supporting the activities of the community association.

[0033] The Accounting Department automates accounting operations based on information automated by the Event Planning Department. Specifically, it uses machine learning to manage and analyze accounting data. For example, it automatically calculates expenses and generates reports. This streamlines accounting operations and provides accurate accounting data. It also automates budget management and expenditure analysis to create accounting reports. This allows for an accurate understanding of the association's financial situation and enables appropriate budget management. Furthermore, it monitors accounting data in real time and issues alerts if anomalies are detected. For example, if fraudulent expenditures or unusual transactions are detected, an alert is immediately issued to prompt appropriate action. Through these functions, the Accounting Department streamlines the association's accounting operations and supports accurate financial management. This ensures the smooth operation of the association and gains the trust of residents. The Accounting Department plays a crucial role in supporting the financial management of the association.

[0034] The Opinion Collection Department collects residents' opinions and feedback. For example, the Opinion Collection Department automates the methods for conducting surveys and collecting feedback. For example, the Opinion Collection Department automatically generates and distributes online surveys to residents. For example, the Opinion Collection Department automatically classifies and analyzes feedback from residents. For example, the Opinion Collection Department collects residents' opinions in real time and incorporates them into the operation of the neighborhood association. This allows the collection of residents' opinions and feedback to be reflected in the operation of the neighborhood association.

[0035] The Schedule Management Department automates schedule management. For example, it automates the use of calendars and the setting of reminders. For example, it automatically generates event schedules and notifies participants. For example, it automatically sets reminders and notifies participants before events. For example, it makes real-time changes and adjustments to schedules. By automating schedule management in this way, it supports efficient event operation.

[0036] The Information Management Department manages meeting minutes and inquiries from residents. For example, the Information Management Department automatically generates meeting minute formats and automates the saving process. For example, the Information Management Department classifies inquiries and automates the response process. For example, the Information Management Department stores resident inquiries in a database and provides necessary information quickly. This allows for the rapid provision of necessary information by managing meeting minutes and inquiries from residents.

[0037] The Communications Department uses natural language processing to automatically send emails and bulletin board posts. For example, the Communications Department automatically generates email content using morphological and grammatical analysis. For example, the Communications Department uses a chatbot to automatically respond to inquiries from residents. For example, the Communications Department collects opinions and feedback from residents and incorporates them into the operation of the community association. In this way, rapid information sharing is achieved through the use of natural language processing.

[0038] The event planning department automates event scheduling. For example, it automatically generates schedules and invites participants. It also automatically generates event content and notifies participants. Furthermore, it monitors event progress in real time and makes adjustments as needed. This automation of event scheduling enables efficient event management.

[0039] The accounting department uses machine learning to manage and analyze accounting data. For example, the accounting department can automatically calculate expenses and generate reports. For example, the accounting department can automatically manage budgets and analyze expenditures to create accounting reports. For example, the accounting department can monitor accounting data in real time and issue alerts if anomalies are detected. In this way, the accuracy of accounting data management and analysis is improved by using machine learning.

[0040] The Information Management Department analyzes residents' past inquiry history and selects the most appropriate method of providing information. For example, the Information Management Department prioritizes providing relevant information based on the topics residents have frequently inquired about in the past. For example, the Information Management Department selects the most effective method of providing information (email, bulletin board, etc.) from residents' inquiry history. For example, the Information Management Department analyzes residents' inquiry history and selects the most appropriate method of providing information for specific time periods. In this way, the most appropriate method of providing information can be selected by analyzing residents' past inquiry history.

[0041] The Information Management Department filters information based on residents' areas of interest and provides highly relevant information. For example, the Information Management Department prioritizes providing information related to events that residents have expressed interest in. For example, the Information Management Department filters relevant news and notices based on residents' areas of interest. For example, the Information Management Department provides information on relevant community association activities based on residents' areas of interest. In this way, by providing information based on residents' areas of interest, highly relevant information can be provided.

[0042] The Information Management Department prioritizes providing highly relevant information by considering residents' geographical location. For example, it prioritizes providing information on nearby events based on residents' current location. For example, it prioritizes providing local news and notifications based on residents' geographical location. For example, it provides information on the nearest community facilities, taking residents' geographical location into consideration. This allows for the provision of highly relevant information by considering residents' geographical location.

[0043] The Information Management Department analyzes residents' social media activity and provides relevant information. For example, it provides information related to topics residents have shown interest in on social media. For example, it provides relevant event information based on residents' social media activity. For example, it analyzes residents' social media activity and provides news and notifications of interest. In this way, by analyzing residents' social media activity, it can provide relevant information.

[0044] The communications department analyzes residents' past opinions and feedback to select the most effective communication method. For example, the communications department selects the most effective communication method based on feedback residents have provided in the past. For example, the communications department analyzes residents' opinion history to select the most effective communication method (email, bulletin board, etc.). For example, the communications department selects the most effective communication method for a specific time period based on residents' opinion history. In this way, the communications department can select the most effective communication method by analyzing residents' past opinions and feedback.

[0045] The communications department customizes messages based on residents' areas of interest. For example, the communications department customizes messages related to events that residents have expressed interest in. For example, the communications department customizes relevant news and notifications based on residents' areas of interest. For example, the communications department customizes information on relevant community association activities based on residents' areas of interest. By customizing messages based on residents' areas of interest, the communications department can provide highly relevant messages.

[0046] The communications department prioritizes sending highly relevant messages by considering residents' geographical location. For example, it prioritizes sending information about nearby events based on residents' current location. For example, it prioritizes sending local news and notifications based on residents' geographical location. For example, it prioritizes sending information about the nearest community center, taking residents' geographical location into consideration. This allows for the provision of highly relevant messages by considering residents' geographical location.

[0047] The communications department analyzes residents' social media activity and sends relevant messages. For example, it sends messages related to topics that residents have shown interest in on social media. For example, it sends relevant event information based on residents' social media activity. For example, it analyzes residents' social media activity and sends news and notifications that are of interest to them. In this way, by analyzing residents' social media activity, it is possible to provide relevant messages.

[0048] The event planning department analyzes residents' past participation history when planning events and selects the most suitable event content. For example, the event planning department selects the most suitable event content based on the history of events residents have previously attended. For example, the event planning department analyzes residents' participation history and selects the most popular event content. For example, the event planning department selects the most suitable event content for a specific time slot based on residents' participation history. In this way, the optimal event content can be selected by analyzing residents' past participation history.

[0049] The Event Planning Department customizes events based on residents' areas of interest when planning them. For example, the Event Planning Department customizes events related to topics that residents have expressed interest in. For example, the Event Planning Department customizes the content of relevant events based on residents' areas of interest. For example, the Event Planning Department customizes information on relevant community association activities based on residents' areas of interest. By customizing events based on residents' areas of interest, the department can provide highly relevant events.

[0050] The Event Planning Department prioritizes events that are highly relevant to residents, taking their geographical location into consideration when planning events. For example, the Event Planning Department prioritizes events in the vicinity based on residents' current location. For example, the Event Planning Department prioritizes local events based on residents' geographical location. For example, the Event Planning Department plans events at the nearest community center, taking residents' geographical location into consideration. By considering residents' geographical location, the department can provide events that are highly relevant to them.

[0051] The Event Planning Department analyzes residents' social media activity when planning events and plans relevant events. For example, the Event Planning Department plans events related to topics that residents have shown interest in on social media. For example, the Event Planning Department plans relevant event content based on residents' social media activity. For example, the Event Planning Department analyzes residents' social media activity and plans events that will attract their interest. In this way, by analyzing residents' social media activity, it is possible to provide relevant events.

[0052] The accounting department analyzes past accounting data and selects the optimal accounting management method during accounting management. For example, the accounting department selects the optimal budget allocation based on past accounting data. For example, the accounting department analyzes past accounting data and selects the most effective expenditure management method. For example, the accounting department selects the optimal accounting management method for a specific period based on past accounting data. This allows for the selection of the optimal accounting management method by analyzing past accounting data.

[0053] The accounting department filters accounting data based on residents' areas of interest during accounting management, providing highly relevant data. For example, the accounting department prioritizes providing accounting data related to expenditure items that residents have expressed interest in. For example, the accounting department filters relevant budget information based on residents' areas of interest. For example, the accounting department provides relevant expenditure analysis data based on residents' areas of interest. In this way, by providing accounting data based on residents' areas of interest, highly relevant data can be provided.

[0054] The accounting department prioritizes providing highly relevant accounting data when managing accounts, taking into account residents' geographical location information. For example, the accounting department prioritizes providing regional accounting data based on residents' current location. For example, the accounting department prioritizes providing regional budget information based on residents' geographical location information. For example, the accounting department provides accounting data for the nearest community association facility, taking residents' geographical location information into consideration. This allows for the provision of highly relevant accounting data by considering residents' geographical location information.

[0055] The accounting department analyzes residents' social media activity during accounting management and provides relevant accounting data. For example, the accounting department provides accounting data related to expenditure items that residents have shown interest in on social media. For example, the accounting department provides relevant budget information based on residents' social media activity. For example, the accounting department analyzes residents' social media activity and provides interesting expenditure analysis data. This allows the accounting department to provide relevant accounting data by analyzing residents' social media activity.

[0056] The opinion collection department analyzes residents' past opinion history and selects the most suitable opinion collection method. For example, the opinion collection department selects the most suitable opinion collection method based on the opinion history previously provided by residents. For example, the opinion collection department analyzes residents' opinion history and selects the most effective opinion collection method (survey, interview, etc.). For example, the opinion collection department selects the most suitable opinion collection method for a specific time period based on residents' opinion history. In this way, the most suitable opinion collection method can be selected by analyzing residents' past opinion history.

[0057] The opinion collection department prioritizes collecting highly relevant opinions by considering residents' geographical location information. For example, the opinion collection department prioritizes collecting local opinions based on residents' current location. For example, the opinion collection department prioritizes collecting opinions on local issues based on residents' geographical location information. For example, the opinion collection department collects opinions on the nearest community association facilities by considering residents' geographical location information. In this way, by considering residents' geographical location information, it is possible to collect highly relevant opinions.

[0058] The Schedule Management Department analyzes residents' past schedule history to select the optimal schedule management method. For example, the Schedule Management Department selects the optimal schedule management method based on the schedule history of events that residents have participated in in the past. For example, the Schedule Management Department analyzes residents' schedule history to select the most effective schedule management method. For example, the Schedule Management Department selects the optimal schedule management method for a specific time slot based on residents' schedule history. In this way, the optimal schedule management method can be selected by analyzing residents' past schedule history.

[0059] The Schedule Management Department prioritizes managing schedules that are highly relevant to residents, taking their geographical location into consideration. For example, the Schedule Management Department prioritizes managing local schedules based on residents' current location. For example, the Schedule Management Department prioritizes managing local event schedules based on residents' geographical location. For example, the Schedule Management Department manages schedules for the nearest community association facilities, taking residents' geographical location into consideration. This allows for the provision of highly relevant schedules by considering residents' geographical location.

[0060] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0061] The Information Management Department can also monitor residents' health status and provide health-related information. For example, it can collect residents' health data and provide health advice. If residents undergo health checkups, it can make health management suggestions based on the results. Furthermore, it can provide appropriate exercise and dietary advice according to residents' health status. This enables the department to support residents' health management and provide health-related information.

[0062] The schedule management department can also prioritize and manage schedules that are highly relevant to residents, taking into account their geographical location. For example, it can prioritize local schedules based on residents' current location, prioritize local event schedules based on residents' geographical location, and manage schedules for the nearest community facilities, taking residents' geographical location into consideration. This allows for the provision of highly relevant schedules by considering residents' geographical location.

[0063] The Information Management Department can also analyze residents' social media activity and provide relevant information. For example, it can provide information related to topics residents have shown interest in on social media. Based on residents' social media activity, it can provide relevant event information. It can analyze residents' social media activity and provide news and notifications that are of interest to them. In this way, by analyzing residents' social media activity, it is possible to provide relevant information.

[0064] The event planning department can also analyze residents' past participation history to select the most suitable event content. For example, they can select the most suitable event content based on residents' past event participation history. They can analyze residents' participation history to select the most popular event content. They can select the most suitable event content for a specific time slot based on residents' participation history. In this way, the most suitable event content can be selected by analyzing residents' past participation history.

[0065] The opinion collection department can also prioritize collecting highly relevant opinions by considering residents' geographical location information. For example, it can prioritize collecting local opinions based on residents' current location. It can prioritize collecting opinions on local issues based on residents' geographical location information. It can collect opinions on the nearest community association facilities by considering residents' geographical location information. In this way, by considering residents' geographical location information, it is possible to collect highly relevant opinions.

[0066] The accounting department can also analyze residents' social media activity during accounting management and provide relevant accounting data. For example, it can provide accounting data related to expenditure items that residents have shown interest in on social media. It can provide relevant budget information based on residents' social media activity. It can analyze residents' social media activity and provide interesting expenditure analysis data. In this way, relevant accounting data can be provided by analyzing residents' social media activity.

[0067] The following briefly describes the processing flow for example form 1.

[0068] Step 1: The Information Management Department manages the information of the neighborhood association. For example, it manages meeting minutes and inquiries from residents, and centralizes information using a database. It provides necessary information quickly, automatically generates meeting minute formats, and automates the storage process. It also categorizes inquiries and automates the response process. Step 2: The Communications Department automates communication based on information managed by the Information Management Department. For example, it uses natural language processing to automatically send emails and bulletin board posts, and uses morphological and grammatical analysis to automatically generate email content. Furthermore, it uses a chatbot to automatically respond to inquiries from residents and collect opinions and feedback from residents to reflect in the operation of the neighborhood association. Step 3: The Event Planning Department automates event planning based on information automated by the Communications Department. For example, it automates event scheduling, including automatic schedule generation and participant invitations. Furthermore, it automatically generates event content and notifies participants. It monitors the progress of the event in real time and makes adjustments as needed. Step 4: The Accounting Department automates accounting operations based on information automated by the Event Planning Department. For example, it uses machine learning to manage and analyze accounting data, automatically calculates expenses, and generates reports. Furthermore, it automates budget management and expenditure analysis to create accounting reports. It monitors accounting data in real time and issues alerts if anomalies are detected.

[0069] (Example of form 2) The AI ​​agent system according to an embodiment of the present invention is a system that automates and streamlines information management, communication, event planning, and accounting operations for neighborhood associations. This AI agent system supports the operation of neighborhood associations and strengthens cooperation among residents. The AI ​​agent system centrally manages various types of information of neighborhood associations and provides necessary information quickly. For example, the AI ​​agent system manages meeting minutes and inquiries from residents of neighborhood associations and provides them to residents as needed. This information management ensures the smooth operation of neighborhood associations. Next, the AI ​​agent system uses natural language processing to automatically send emails and bulletin board posts. For example, the AI ​​agent system automatically sends announcements for neighborhood association meetings and event notices. The AI ​​agent system also collects opinions and feedback from residents and reflects them in the operation of neighborhood associations. This facilitates smooth communication among residents. Furthermore, the AI ​​agent system uses machine learning to manage and analyze accounting data. For example, the AI ​​agent system automatically manages the neighborhood association's budget and analyzes expenditures, and creates accounting reports. The AI ​​agent system also automates event scheduling, supporting efficient event management. This will streamline the operation of the neighborhood association and reduce the burden on residents. The AI ​​agent system includes an opinion collection unit that collects residents' opinions and feedback. For example, the AI ​​agent system automates how to conduct surveys and collect feedback. The AI ​​agent system includes a schedule management unit that automates schedule management. For example, the AI ​​agent system automates how to use the calendar and set reminders. The AI ​​agent system includes an information management unit that manages meeting minutes of the neighborhood association and inquiries from residents. For example, the AI ​​agent system automates the format and saving method of meeting minutes. The AI ​​agent system includes a communication unit that uses natural language processing to automatically send emails and bulletin board posts. For example, the AI ​​agent system uses morphological and grammatical analysis to automatically generate email content. The AI ​​agent system includes an event planning unit that automates event schedule management.For example, the AI ​​agent system automatically generates schedules and invites participants. The AI ​​agent system also includes an accounting department that uses machine learning to manage and analyze accounting data. For example, the AI ​​agent system automatically calculates expenses and generates reports. This allows the AI ​​agent system to streamline the operation of neighborhood associations and strengthen cooperation among residents.

[0070] The AI ​​agent system according to this embodiment comprises an Information Management Department, a Communication Department, an Event Planning Department, and an Accounting Department. The Information Management Department manages information of the neighborhood association. For example, the Information Management Department manages minutes of neighborhood association meetings and inquiries from residents. For example, the Information Management Department centrally manages information using a database and provides necessary information quickly. For example, the Information Management Department automatically generates meeting minute formats and automates the saving method. For example, the Information Management Department classifies inquiries and automates the response method. The Communication Department automates communication based on the information managed by the Information Management Department. For example, the Communication Department automatically sends emails and bulletin board posts using natural language processing. For example, the Communication Department automatically generates email content using morphological analysis and grammatical analysis. For example, the Communication Department automatically responds to inquiries from residents using a chatbot. For example, the Communication Department collects opinions and feedback from residents and reflects them in the operation of the neighborhood association. The Event Planning Department automates event planning based on the information automated by the Communication Department. The Event Planning Department automates, for example, event scheduling. The Event Planning Department automatically generates schedules and invites participants. The Event Planning Department automatically generates event content and notifies participants. The Event Planning Department monitors the progress of events in real time and makes adjustments as needed. The Accounting Department automates accounting operations based on the information automated by the Event Planning Department. The Accounting Department manages and analyzes accounting data using machine learning. The Accounting Department automatically calculates expenses and generates reports. The Accounting Department automatically manages budgets and analyzes expenditures and creates accounting reports. The Accounting Department monitors accounting data in real time and issues alerts if anomalies are detected. As a result, the AI ​​agent system according to this embodiment automates and streamlines the information management, communication, event planning, and accounting operations of the community association, thereby ensuring the smooth operation of the community association.

[0071] The Information Management Department manages information for the neighborhood association. Specifically, it manages meeting minutes and inquiries from residents. The Information Management Department uses a database to centrally manage information and quickly provide necessary information. For example, it automatically generates meeting minute formats and automates the saving process. This ensures that meeting contents are accurately recorded and can be easily referenced later. It also categorizes inquiries and automates response methods, enabling quick and appropriate responses to residents' inquiries. The Information Management Department can also use AI to automatically summarize meeting minutes and extract key points. This allows for a quick understanding of meeting contents and enables efficient operation. Furthermore, it uses natural language processing technology to analyze the intent and content of inquiries and classify them into appropriate categories. This enables optimal responses tailored to the content of inquiries. Through these functions, the Information Management Department plays a role in streamlining information management for the neighborhood association and facilitating smooth communication with residents.

[0072] The Communications Department automates communication based on information managed by the Information Management Department. Specifically, it uses natural language processing to automatically send emails and bulletin board posts. For example, it uses morphological and grammatical analysis to automatically generate email content. This allows for the rapid and accurate delivery of information necessary for the operation of the neighborhood association to residents. It also uses a chatbot to automatically respond to inquiries from residents. The chatbot analyzes the content of residents' inquiries and provides appropriate answers. This speeds up responses to residents' inquiries and ensures the smooth operation of the neighborhood association. Furthermore, the Communications Department plays a role in collecting opinions and feedback from residents and reflecting them in the operation of the neighborhood association. For example, it automatically generates and distributes questionnaires to residents to collect their opinions. The collected opinions are analyzed using AI and used to improve the operation of the neighborhood association. This enables operations that reflect residents' opinions, making the activities of the neighborhood association more fulfilling. Through these functions, the Communications Department facilitates communication between the neighborhood association and residents and supports the operation of the neighborhood association.

[0073] The Event Planning Department automates event planning based on information automated by the Communications Department. Specifically, it automates event schedule management, such as automatically generating schedules and inviting participants. This streamlines event planning and ensures quick participant invitations. It also automatically generates event content and notifies participants, ensuring accurate communication and smooth participation. Furthermore, it monitors event progress in real time and makes adjustments as needed. For example, it monitors event progress to ensure it is proceeding according to schedule. If problems arise, it responds quickly to ensure the smooth running of the event. Through these functions, the Event Planning Department streamlines community association event planning and provides an environment that is easy for residents to participate in. This revitalizes community association activities and promotes interaction among residents. The Event Planning Department plays a vital role in supporting the activities of the community association.

[0074] The Accounting Department automates accounting operations based on information automated by the Event Planning Department. Specifically, it uses machine learning to manage and analyze accounting data. For example, it automatically calculates expenses and generates reports. This streamlines accounting operations and provides accurate accounting data. It also automates budget management and expenditure analysis to create accounting reports. This allows for an accurate understanding of the association's financial situation and enables appropriate budget management. Furthermore, it monitors accounting data in real time and issues alerts if anomalies are detected. For example, if fraudulent expenditures or unusual transactions are detected, an alert is immediately issued to prompt appropriate action. Through these functions, the Accounting Department streamlines the association's accounting operations and supports accurate financial management. This ensures the smooth operation of the association and gains the trust of residents. The Accounting Department plays a crucial role in supporting the financial management of the association.

[0075] The Opinion Collection Department collects residents' opinions and feedback. For example, the Opinion Collection Department automates the methods for conducting surveys and collecting feedback. For example, the Opinion Collection Department automatically generates and distributes online surveys to residents. For example, the Opinion Collection Department automatically classifies and analyzes feedback from residents. For example, the Opinion Collection Department collects residents' opinions in real time and incorporates them into the operation of the neighborhood association. This allows the collection of residents' opinions and feedback to be reflected in the operation of the neighborhood association.

[0076] The Schedule Management Department automates schedule management. For example, it automates the use of calendars and the setting of reminders. For example, it automatically generates event schedules and notifies participants. For example, it automatically sets reminders and notifies participants before events. For example, it makes real-time changes and adjustments to schedules. By automating schedule management in this way, it supports efficient event operation.

[0077] The Information Management Department manages meeting minutes and inquiries from residents. For example, the Information Management Department automatically generates meeting minute formats and automates the saving process. For example, the Information Management Department classifies inquiries and automates the response process. For example, the Information Management Department stores resident inquiries in a database and provides necessary information quickly. This allows for the rapid provision of necessary information by managing meeting minutes and inquiries from residents.

[0078] The Communications Department uses natural language processing to automatically send emails and bulletin board posts. For example, the Communications Department automatically generates email content using morphological and grammatical analysis. For example, the Communications Department uses a chatbot to automatically respond to inquiries from residents. For example, the Communications Department collects opinions and feedback from residents and incorporates them into the operation of the community association. In this way, rapid information sharing is achieved through the use of natural language processing.

[0079] The event planning department automates event scheduling. For example, it automatically generates schedules and invites participants. It also automatically generates event content and notifies participants. Furthermore, it monitors event progress in real time and makes adjustments as needed. This automation of event scheduling enables efficient event management.

[0080] The accounting department uses machine learning to manage and analyze accounting data. For example, the accounting department can automatically calculate expenses and generate reports. For example, the accounting department can automatically manage budgets and analyze expenditures to create accounting reports. For example, the accounting department can monitor accounting data in real time and issue alerts if anomalies are detected. In this way, the accuracy of accounting data management and analysis is improved by using machine learning.

[0081] The Information Management Department estimates residents' emotions and prioritizes information based on these estimated emotions. For example, if a resident is feeling anxious, the Information Management Department prioritizes providing reassuring information. For example, if a resident is excited, the Information Management Department prioritizes providing interesting information. For example, if a resident is tired, the Information Management Department prioritizes providing concise and important information. By prioritizing information based on residents' emotions, more appropriate information can be provided. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0082] The Information Management Department analyzes residents' past inquiry history and selects the most appropriate method of providing information. For example, the Information Management Department prioritizes providing relevant information based on the topics residents have frequently inquired about in the past. For example, the Information Management Department selects the most effective method of providing information (email, bulletin board, etc.) from residents' inquiry history. For example, the Information Management Department analyzes residents' inquiry history and selects the most appropriate method of providing information for specific time periods. In this way, the most appropriate method of providing information can be selected by analyzing residents' past inquiry history.

[0083] The Information Management Department filters information based on residents' areas of interest and provides highly relevant information. For example, the Information Management Department prioritizes providing information related to events that residents have expressed interest in. For example, the Information Management Department filters relevant news and notices based on residents' areas of interest. For example, the Information Management Department provides information on relevant community association activities based on residents' areas of interest. In this way, by providing information based on residents' areas of interest, highly relevant information can be provided.

[0084] The Information Management Department estimates residents' emotions and adjusts how information is displayed based on these estimations. For example, if a resident is feeling anxious, the Information Management Department displays information using reassuring colors and designs. If a resident is excited, the Information Management Department displays information using visually stimulating designs. If a resident is tired, the Information Management Department displays information using simple and highly visible designs. By adjusting how information is displayed based on residents' emotions, more appropriate information can be displayed. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0085] The Information Management Department prioritizes providing highly relevant information by considering residents' geographical location. For example, it prioritizes providing information on nearby events based on residents' current location. For example, it prioritizes providing local news and notifications based on residents' geographical location. For example, it provides information on the nearest community facilities, taking residents' geographical location into consideration. This allows for the provision of highly relevant information by considering residents' geographical location.

[0086] The Information Management Department analyzes residents' social media activity and provides relevant information. For example, it provides information related to topics residents have shown interest in on social media. For example, it provides relevant event information based on residents' social media activity. For example, it analyzes residents' social media activity and provides news and notifications of interest. In this way, by analyzing residents' social media activity, it can provide relevant information.

[0087] The communications department estimates residents' emotions and adjusts the communication style based on the estimated emotions. For example, if a resident is feeling anxious, the communications department will communicate in a way that provides reassurance. If a resident is excited, the communications department will communicate in a way that is visually stimulating. If a resident is tired, the communications department will communicate in a way that is simple and easy to understand. By adjusting the communication style based on residents' emotions, more appropriate communication becomes possible. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0088] The communications department analyzes residents' past opinions and feedback to select the most effective communication method. For example, the communications department selects the most effective communication method based on feedback residents have provided in the past. For example, the communications department analyzes residents' opinion history to select the most effective communication method (email, bulletin board, etc.). For example, the communications department selects the most effective communication method for a specific time period based on residents' opinion history. In this way, the communications department can select the most effective communication method by analyzing residents' past opinions and feedback.

[0089] The communications department customizes messages based on residents' areas of interest. For example, the communications department customizes messages related to events that residents have expressed interest in. For example, the communications department customizes relevant news and notifications based on residents' areas of interest. For example, the communications department customizes information on relevant community association activities based on residents' areas of interest. By customizing messages based on residents' areas of interest, the communications department can provide highly relevant messages.

[0090] The communication department estimates residents' emotions and adjusts the frequency of communication based on the estimated emotions. For example, if a resident is feeling anxious, the communication department will communicate frequently to provide reassurance. If a resident is excited, the communication department will communicate at an appropriate frequency to maintain their interest. If a resident is tired, the communication department will communicate at the minimum necessary frequency. By adjusting the frequency of communication based on residents' emotions, more appropriate communication becomes possible. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0091] The communications department prioritizes sending highly relevant messages by considering residents' geographical location. For example, it prioritizes sending information about nearby events based on residents' current location. For example, it prioritizes sending local news and notifications based on residents' geographical location. For example, it prioritizes sending information about the nearest community center, taking residents' geographical location into consideration. This allows for the provision of highly relevant messages by considering residents' geographical location.

[0092] The communications department analyzes residents' social media activity and sends relevant messages. For example, it sends messages related to topics that residents have shown interest in on social media. For example, it sends relevant event information based on residents' social media activity. For example, it analyzes residents' social media activity and sends news and notifications that are of interest to them. In this way, by analyzing residents' social media activity, it is possible to provide relevant messages.

[0093] The event planning department estimates the emotions of residents and adjusts the event content based on those estimates. For example, if residents are feeling anxious, the event planning department will adjust the event content to provide a sense of security. For example, if residents are excited, the event planning department will adjust the event content to be visually stimulating. For example, if residents are tired, the event planning department will adjust the event content to be relaxing. In this way, by adjusting the event content based on residents' emotions, more appropriate events can be planned. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0094] The event planning department analyzes residents' past participation history when planning events and selects the most suitable event content. For example, the event planning department selects the most suitable event content based on the history of events residents have previously attended. For example, the event planning department analyzes residents' participation history and selects the most popular event content. For example, the event planning department selects the most suitable event content for a specific time slot based on residents' participation history. In this way, the optimal event content can be selected by analyzing residents' past participation history.

[0095] The Event Planning Department customizes events based on residents' areas of interest when planning them. For example, the Event Planning Department customizes events related to topics that residents have expressed interest in. For example, the Event Planning Department customizes the content of relevant events based on residents' areas of interest. For example, the Event Planning Department customizes information on relevant community association activities based on residents' areas of interest. By customizing events based on residents' areas of interest, the department can provide highly relevant events.

[0096] The event planning department estimates residents' emotions and adjusts the event schedule based on these estimates. For example, if residents are feeling anxious, the event planning department will adjust the schedule to provide a sense of security. If residents are excited, the event planning department will adjust the schedule to be visually stimulating. If residents are tired, the event planning department will adjust the schedule to be relaxing. By adjusting the event schedule based on residents' emotions, a more appropriate schedule can be set. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0097] The Event Planning Department prioritizes events that are highly relevant to residents, taking their geographical location into consideration when planning events. For example, the Event Planning Department prioritizes events in the vicinity based on residents' current location. For example, the Event Planning Department prioritizes local events based on residents' geographical location. For example, the Event Planning Department plans events at the nearest community center, taking residents' geographical location into consideration. By considering residents' geographical location, the department can provide events that are highly relevant to them.

[0098] The Event Planning Department analyzes residents' social media activity when planning events and plans relevant events. For example, the Event Planning Department plans events related to topics that residents have shown interest in on social media. For example, the Event Planning Department plans relevant event content based on residents' social media activity. For example, the Event Planning Department analyzes residents' social media activity and plans events that will attract their interest. In this way, by analyzing residents' social media activity, it is possible to provide relevant events.

[0099] The accounting department estimates residents' emotions and adjusts the presentation of accounting reports based on these estimates. For example, if residents are feeling anxious, the accounting department will present the reports in a reassuring manner. If residents are excited, the accounting department will present the reports in a visually stimulating manner. If residents are tired, the accounting department will present the reports in a simple and easily understandable manner. By adjusting the presentation of accounting reports based on residents' emotions, more appropriate accounting reports can be provided. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0100] The accounting department analyzes past accounting data and selects the optimal accounting management method during accounting management. For example, the accounting department selects the optimal budget allocation based on past accounting data. For example, the accounting department analyzes past accounting data and selects the most effective expenditure management method. For example, the accounting department selects the optimal accounting management method for a specific period based on past accounting data. This allows for the selection of the optimal accounting management method by analyzing past accounting data.

[0101] The accounting department filters accounting data based on residents' areas of interest during accounting management, providing highly relevant data. For example, the accounting department prioritizes providing accounting data related to expenditure items that residents have expressed interest in. For example, the accounting department filters relevant budget information based on residents' areas of interest. For example, the accounting department provides relevant expenditure analysis data based on residents' areas of interest. In this way, by providing accounting data based on residents' areas of interest, highly relevant data can be provided.

[0102] The accounting department estimates residents' emotions and adjusts the frequency of accounting reports based on these estimates. For example, if residents are feeling anxious, the accounting department will provide frequent accounting reports to reassure them. If residents are excited, the accounting department will provide accounting reports at a moderate frequency to maintain their interest. If residents are tired, the accounting department will provide accounting reports at the minimum necessary frequency. By adjusting the frequency of accounting reports based on residents' emotions, more appropriate accounting reports can be provided. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0103] The accounting department prioritizes providing highly relevant accounting data when managing accounts, taking into account residents' geographical location information. For example, the accounting department prioritizes providing regional accounting data based on residents' current location. For example, the accounting department prioritizes providing regional budget information based on residents' geographical location information. For example, the accounting department provides accounting data for the nearest community association facility, taking residents' geographical location information into consideration. This allows for the provision of highly relevant accounting data by considering residents' geographical location information.

[0104] The accounting department analyzes residents' social media activity during accounting management and provides relevant accounting data. For example, the accounting department provides accounting data related to expenditure items that residents have shown interest in on social media. For example, the accounting department provides relevant budget information based on residents' social media activity. For example, the accounting department analyzes residents' social media activity and provides interesting expenditure analysis data. This allows the accounting department to provide relevant accounting data by analyzing residents' social media activity.

[0105] The opinion gathering department estimates the emotions of residents and adjusts the opinion gathering method based on the estimated emotions. For example, if residents are feeling anxious, the opinion gathering department will gather opinions in a way that provides reassurance. For example, if residents are excited, the opinion gathering department will gather opinions in a way that is visually stimulating. For example, if residents are tired, the opinion gathering department will gather opinions in a way that is simple and easy to see. By adjusting the opinion gathering method based on the emotions of residents, more appropriate opinion gathering becomes possible. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is not limited to, but may include, text generation AI (e.g., LLM) or multimodal generation AI.

[0106] The opinion collection department analyzes residents' past opinion history and selects the most suitable opinion collection method. For example, the opinion collection department selects the most suitable opinion collection method based on the opinion history previously provided by residents. For example, the opinion collection department analyzes residents' opinion history and selects the most effective opinion collection method (survey, interview, etc.). For example, the opinion collection department selects the most suitable opinion collection method for a specific time period based on residents' opinion history. In this way, the most suitable opinion collection method can be selected by analyzing residents' past opinion history.

[0107] The opinion gathering unit estimates residents' emotions and adjusts the frequency of opinion gathering based on the estimated emotions. For example, if residents are feeling anxious, the opinion gathering unit will gather opinions frequently to provide reassurance. If residents are excited, the opinion gathering unit will gather opinions at a moderate frequency to maintain their interest. If residents are tired, the opinion gathering unit will gather opinions at the minimum necessary frequency. By adjusting the frequency of opinion gathering based on residents' emotions, more appropriate opinion gathering becomes possible. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0108] The opinion collection department prioritizes collecting highly relevant opinions by considering residents' geographical location information. For example, the opinion collection department prioritizes collecting local opinions based on residents' current location. For example, the opinion collection department prioritizes collecting opinions on local issues based on residents' geographical location information. For example, the opinion collection department collects opinions on the nearest community association facilities by considering residents' geographical location information. In this way, by considering residents' geographical location information, it is possible to collect highly relevant opinions.

[0109] The schedule management unit estimates residents' emotions and adjusts the schedule management method based on the estimated emotions. For example, if a resident is feeling anxious, the schedule management unit will manage the schedule in a way that provides reassurance. For example, if a resident is excited, the schedule management unit will manage the schedule in a way that is visually stimulating. For example, if a resident is tired, the schedule management unit will manage the schedule in a way that is simple and easy to see. By adjusting the schedule management method based on residents' emotions, more appropriate schedule management becomes possible. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0110] The Schedule Management Department analyzes residents' past schedule history to select the optimal schedule management method. For example, the Schedule Management Department selects the optimal schedule management method based on the schedule history of events that residents have participated in in the past. For example, the Schedule Management Department analyzes residents' schedule history to select the most effective schedule management method. For example, the Schedule Management Department selects the optimal schedule management method for a specific time slot based on residents' schedule history. In this way, the optimal schedule management method can be selected by analyzing residents' past schedule history.

[0111] The scheduling department estimates residents' emotions and adjusts the frequency of event scheduling based on these estimates. For example, if residents are feeling anxious, the scheduling department will frequently manage events to provide reassurance. If residents are excited, the scheduling department will maintain their interest with a moderate frequency of events. If residents are tired, the scheduling department will manage events with the minimum necessary frequency. By adjusting the frequency of event scheduling based on residents' emotions, more appropriate scheduling becomes possible. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may include, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0112] The Schedule Management Department prioritizes managing schedules that are highly relevant to residents, taking their geographical location into consideration. For example, the Schedule Management Department prioritizes managing local schedules based on residents' current location. For example, the Schedule Management Department prioritizes managing local event schedules based on residents' geographical location. For example, the Schedule Management Department manages schedules for the nearest community association facilities, taking residents' geographical location into consideration. This allows for the provision of highly relevant schedules by considering residents' geographical location.

[0113] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0114] The Information Management Department can also monitor residents' health status and provide health-related information. For example, it can collect residents' health data and provide health advice. If residents undergo health checkups, it can make health management suggestions based on the results. Furthermore, it can provide appropriate exercise and dietary advice according to residents' health status. This enables the department to support residents' health management and provide health-related information.

[0115] The opinion gathering department can also estimate residents' emotions and adjust the opinion gathering methods based on those estimates. For example, if residents are feeling anxious, they can gather opinions in a way that provides reassurance. If residents are excited, they can gather opinions in a visually stimulating way. If residents are tired, they can gather opinions in a simple and easily visible way. By adjusting the opinion gathering methods based on residents' emotions, more appropriate opinion gathering becomes possible.

[0116] The schedule management department can also prioritize and manage schedules that are highly relevant to residents, taking into account their geographical location. For example, it can prioritize local schedules based on residents' current location, prioritize local event schedules based on residents' geographical location, and manage schedules for the nearest community facilities, taking residents' geographical location into consideration. This allows for the provision of highly relevant schedules by considering residents' geographical location.

[0117] The Information Management Department can also analyze residents' social media activity and provide relevant information. For example, it can provide information related to topics residents have shown interest in on social media. Based on residents' social media activity, it can provide relevant event information. It can analyze residents' social media activity and provide news and notifications that are of interest to them. In this way, by analyzing residents' social media activity, it is possible to provide relevant information.

[0118] The communications department can also estimate residents' emotions and adjust the communication style based on those estimates. For example, if a resident is feeling anxious, they can communicate in a way that provides reassurance. If a resident is excited, they can communicate in a way that is visually stimulating. If a resident is tired, they can communicate in a way that is simple and easy to understand. By adjusting the communication style based on residents' emotions, more appropriate communication becomes possible.

[0119] The event planning department can also analyze residents' past participation history to select the most suitable event content. For example, they can select the most suitable event content based on residents' past event participation history. They can analyze residents' participation history to select the most popular event content. They can select the most suitable event content for a specific time slot based on residents' participation history. In this way, the most suitable event content can be selected by analyzing residents' past participation history.

[0120] The accounting department can also estimate residents' emotions and adjust the presentation of accounting reports based on those estimates. For example, if residents are feeling anxious, the accounting report will be presented in a reassuring manner. If residents are excited, the accounting report will be presented in a visually stimulating manner. If residents are tired, the accounting report will be presented in a simple and easily understandable manner. By adjusting the presentation of accounting reports based on residents' emotions, more appropriate accounting reports can be provided.

[0121] The opinion collection department can also prioritize collecting highly relevant opinions by considering residents' geographical location information. For example, it can prioritize collecting local opinions based on residents' current location. It can prioritize collecting opinions on local issues based on residents' geographical location information. It can collect opinions on the nearest community association facilities by considering residents' geographical location information. In this way, by considering residents' geographical location information, it is possible to collect highly relevant opinions.

[0122] The scheduling department can also estimate residents' emotions and adjust scheduling methods based on those estimates. For example, if residents are feeling anxious, scheduling will be done in a way that provides reassurance. If residents are excited, scheduling will be done in a visually stimulating way. If residents are tired, scheduling will be done in a simple and easily visible way. By adjusting scheduling methods based on residents' emotions, more appropriate scheduling becomes possible.

[0123] The accounting department can also analyze residents' social media activity during accounting management and provide relevant accounting data. For example, it can provide accounting data related to expenditure items that residents have shown interest in on social media. It can provide relevant budget information based on residents' social media activity. It can analyze residents' social media activity and provide interesting expenditure analysis data. In this way, relevant accounting data can be provided by analyzing residents' social media activity.

[0124] The following briefly describes the processing flow for example form 2.

[0125] Step 1: The Information Management Department manages the information of the neighborhood association. For example, it manages meeting minutes and inquiries from residents, and centralizes information using a database. It provides necessary information quickly, automatically generates meeting minute formats, and automates the storage process. It also categorizes inquiries and automates the response process. Step 2: The Communications Department automates communication based on information managed by the Information Management Department. For example, it uses natural language processing to automatically send emails and bulletin board posts, and uses morphological and grammatical analysis to automatically generate email content. Furthermore, it uses a chatbot to automatically respond to inquiries from residents and collect opinions and feedback from residents to reflect in the operation of the neighborhood association. Step 3: The Event Planning Department automates event planning based on information automated by the Communications Department. For example, it automates event scheduling, including automatic schedule generation and participant invitations. Furthermore, it automatically generates event content and notifies participants. It monitors the progress of the event in real time and makes adjustments as needed. Step 4: The Accounting Department automates accounting operations based on information automated by the Event Planning Department. For example, it uses machine learning to manage and analyze accounting data, automatically calculates expenses, and generates reports. Furthermore, it automates budget management and expenditure analysis to create accounting reports. It monitors accounting data in real time and issues alerts if anomalies are detected.

[0126] 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.

[0127] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. 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 (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0128] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0129] Each of the above-mentioned elements, including the Information Management Department, Communication Department, Event Planning Department, Accounting Department, Opinion Gathering Department, and Schedule Management Department, is implemented by, for example, at least one of the smart device 14 and the data processing device 12. For example, the Information Management Department is implemented by the control unit 46A of the smart device 14 and manages minutes of neighborhood association meetings and inquiries from residents. The Communication Department is implemented by, for example, the specific processing unit 290 of the data processing device 12 and uses natural language processing to automatically send emails and bulletin board posts. The Event Planning Department is implemented by, for example, the control unit 46A of the smart device 14 and automates event schedule management. The Accounting Department is implemented by, for example, the specific processing unit 290 of the data processing device 12 and uses machine learning to manage and analyze accounting data. The Opinion Gathering Department is implemented by, for example, the control unit 46A of the smart device 14 and collects opinions and feedback from residents. The Schedule Management Department is implemented by, for example, the specific processing unit 290 of the data processing device 12 and automates schedule management. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0130] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0131] 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.

[0132] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0133] 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.

[0134] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0135] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0136] 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.

[0137] 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 by the processor 28. The storage 32 stores the specific processing program 56.

[0138] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0139] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0140] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0141] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0142] 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.

[0143] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0144] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0145] Each of the above-mentioned elements, including the Information Management Department, Communication Department, Event Planning Department, Accounting Department, Opinion Gathering Department, and Schedule Management Department, is implemented by at least one of the smart glasses 214 and the data processing device 12. For example, the Information Management Department is implemented by the control unit 46A of the smart glasses 214 and manages minutes of neighborhood association meetings and inquiries from residents. The Communication Department is implemented by the specific processing unit 290 of the data processing device 12 and uses natural language processing to automatically send emails and bulletin board posts. The Event Planning Department is implemented by the control unit 46A of the smart glasses 214 and automates event schedule management. The Accounting Department is implemented by the specific processing unit 290 of the data processing device 12 and uses machine learning to manage and analyze accounting data. The Opinion Gathering Department is implemented by the control unit 46A of the smart glasses 214 and collects opinions and feedback from residents. The Schedule Management Department is implemented by the specific processing unit 290 of the data processing device 12 and automates schedule management. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0146] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0147] 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.

[0148] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0149] 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.

[0150] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0151] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0152] 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.

[0153] 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.

[0154] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0155] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0156] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0157] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0158] 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.

[0159] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0160] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0161] Each of the above-mentioned elements, including the Information Management Department, Communication Department, Event Planning Department, Accounting Department, Opinion Gathering Department, and Schedule Management Department, is implemented by, for example, at least one of the headset terminal 314 and the data processing device 12. For example, the Information Management Department is implemented by the control unit 46A of the headset terminal 314 and manages minutes of neighborhood association meetings and inquiries from residents. The Communication Department is implemented by, for example, the specific processing unit 290 of the data processing device 12 and uses natural language processing to automatically send emails and bulletin board posts. The Event Planning Department is implemented by, for example, the control unit 46A of the headset terminal 314 and automates event schedule management. The Accounting Department is implemented by, for example, the specific processing unit 290 of the data processing device 12 and uses machine learning to manage and analyze accounting data. The Opinion Gathering Department is implemented by, for example, the control unit 46A of the headset terminal 314 and collects opinions and feedback from residents. The Schedule Management Department is implemented by, for example, the specific processing unit 290 of the data processing device 12 and automates schedule management. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0162] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0163] 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.

[0164] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0165] 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.

[0166] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0167] 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 image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0168] 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.

[0169] 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. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0170] 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.

[0171] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0172] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0173] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0174] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0175] 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.

[0176] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0177] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0178] Each of the above-mentioned elements, including the Information Management Department, Communication Department, Event Planning Department, Accounting Department, Opinion Gathering Department, and Schedule Management Department, is implemented by, for example, at least one of the robot 414 and the data processing device 12. For example, the Information Management Department is implemented by the control unit 46A of the robot 414 and manages minutes of neighborhood association meetings and inquiries from residents. The Communication Department is implemented by, for example, the specific processing unit 290 of the data processing device 12 and uses natural language processing to automatically send emails and bulletin board posts. The Event Planning Department is implemented by, for example, the control unit 46A of the robot 414 and automates event schedule management. The Accounting Department is implemented by, for example, the specific processing unit 290 of the data processing device 12 and uses machine learning to manage and analyze accounting data. The Opinion Gathering Department is implemented by, for example, the control unit 46A of the robot 414 and collects opinions and feedback from residents. The Schedule Management Department is implemented by, for example, the specific processing unit 290 of the data processing device 12 and automates schedule management. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0179] 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.

[0180] Figure 9 shows the 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.

[0181] 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.

[0182] 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.

[0183] 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, and motorcycles, 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 based, for example, 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.

[0184] 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."

[0185] 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.

[0186] 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 method for the specific process may be used, which includes computer 22 and multiple other computers.

[0187] 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.

[0188] 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.

[0189] 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.

[0190] 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.

[0191] 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.

[0192] 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.

[0193] 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.

[0194] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0195] 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 other things 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.

[0196] 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.

[0197] (Note 1) The Information Management Department manages information for the neighborhood association, Based on the information managed by the aforementioned Information Management Department, the Communication Department automates communication, Based on the information automated by the aforementioned communications department, the event planning department automates event planning, The system includes an accounting department that automates accounting operations based on information automated by the aforementioned event planning department. A system characterized by the following features. (Note 2) It has a department for collecting opinions and feedback from residents. The system described in Appendix 1, characterized by the features described herein. (Note 3) It is equipped with a schedule management unit that automates schedule management. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned information management department, Manages meeting minutes and inquiries from residents of the neighborhood association. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned communications department, Automate sending emails and message board messages using natural language processing. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned event planning department, Automate event scheduling. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned accounting department, Using machine learning to manage and analyze accounting data The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned information management department, The system estimates the sentiments of residents and prioritizes information based on those estimated sentiments. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned information management department, We analyze residents' past inquiry history and select the most appropriate method for providing information. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned information management department, Filter information based on residents' areas of interest and provide highly relevant information. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned information management department, The system estimates residents' sentiments and adjusts how information is displayed based on those estimated sentiments. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned information management department, Prioritize providing highly relevant information, taking into account the geographical location of residents. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned information management department, Analyze residents' social media activity and provide relevant information. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned communications department, The system estimates the feelings of residents and adjusts the communication style based on those estimated feelings. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned communications department, Analyze residents' past opinions and feedback to select the most suitable communication method. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned communications department, Customize messages based on residents' areas of interest. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned communications department, The system estimates residents' emotions and adjusts the frequency of communication based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned communications department, Prioritize sending highly relevant messages by considering residents' geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned communications department, Analyze residents' social media activity and send relevant messages. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned event planning department, We estimate the residents' feelings and adjust the event content based on those estimated feelings. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned event planning department, When planning an event, we analyze residents' past participation history to select the most suitable event content. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned event planning department, When planning an event, customize it based on the areas of interest of the residents. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned event planning department, The system estimates residents' sentiments and adjusts event schedules based on those estimated sentiments. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned event planning department, When planning events, prioritize events that are highly relevant to residents, taking their geographical location into consideration. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned event planning department, When planning events, we analyze residents' social media activity and plan relevant events. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned accounting department, We estimate the sentiments of the residents and adjust the way accounting reports are presented based on those estimated sentiments. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned accounting department, During accounting management, past accounting data is analyzed to select the optimal accounting management method. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned accounting department, During accounting management, the system filters accounting data based on residents' areas of interest to provide highly relevant data. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned accounting department, We estimate residents' sentiments and adjust the frequency of accounting reports based on those estimated sentiments. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned accounting department, During accounting management, the system prioritizes providing highly relevant accounting data by considering residents' geographical location information. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned accounting department, During accounting management, we analyze residents' social media activity and provide relevant accounting data. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned opinion collection department, We estimate the sentiments of the residents and adjust the methods of collecting opinions based on those estimated sentiments. The system described in Appendix 2, characterized by the features described herein. (Note 33) The aforementioned opinion collection department, When collecting opinions, we analyze residents' past opinion history and select the most suitable method for collecting opinions. The system described in Appendix 2, characterized by the features described herein. (Note 34) The aforementioned opinion collection department, We estimate the sentiments of the residents and adjust the frequency of opinion gathering based on those estimated sentiments. The system described in Appendix 2, characterized by the features described herein. (Note 35) The aforementioned opinion collection department, When collecting opinions, we will prioritize collecting opinions that are highly relevant, taking into account the geographical location of residents. The system described in Appendix 2, characterized by the features described herein. (Note 36) The aforementioned schedule management unit, Estimate residents' sentiments and adjust schedule management methods based on those estimated sentiments. The system described in Appendix 3, characterized by the features described herein. (Note 37) The aforementioned schedule management unit, When managing schedules, analyze residents' past schedule history and select the most suitable schedule management method. The system described in Appendix 3, characterized by the features described herein. (Note 38) The aforementioned schedule management unit, The system estimates residents' sentiments and adjusts the frequency of event scheduling based on those estimated sentiments. The system described in Appendix 3, characterized by the features described herein. (Note 39) The aforementioned schedule management unit, When managing schedules, prioritize highly relevant schedules by considering residents' geographical location information. The system described in Appendix 3, characterized by the features described herein. [Explanation of symbols]

[0198] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The Information Management Department manages information for the neighborhood association, Based on the information managed by the aforementioned Information Management Department, the Communication Department automates communication, Based on the information automated by the aforementioned communications department, the event planning department automates event planning, The system includes an accounting department that automates accounting operations based on information automated by the aforementioned event planning department. A system characterized by the following features.

2. It has a department for collecting opinions and feedback from residents. The system according to feature 1.

3. It is equipped with a schedule management unit that automates schedule management. The system according to feature 1.

4. The aforementioned information management department, Manages meeting minutes and inquiries from residents of the neighborhood association. The system according to feature 1.

5. The aforementioned communications department, Automate sending emails and message board messages using natural language processing. The system according to feature 1.

6. The aforementioned event planning department, Automate event scheduling. The system according to feature 1.

7. The aforementioned accounting department, Using machine learning to manage and analyze accounting data The system according to feature 1.

8. The aforementioned information management department, The system estimates the sentiments of residents and prioritizes information based on those estimated sentiments. The system according to feature 1.

9. The aforementioned information management department, We analyze residents' past inquiry history and select the most appropriate method for providing information. The system according to feature 1.

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