System

Abstract

A system is provided.SOLUTION: A system for supporting an operation of a Neighborhood Association, comprising: means for collecting operation information provided from the Neighborhood Association using a generation and AI engine and accumulating the operation information in a database; means for generating an optimal operation proposal based on the operation information accumulated in the database; and means for notifying members of the Neighborhood Association of the generated operation proposal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The management of neighborhood associations and community groups plays an important role for local residents, but there are problems with efficient management due to the large aging population, declining IT literacy, and a lack of management know-how. Furthermore, there is a lack of information sharing and communication during management, and it is difficult to manage data and make appropriate proposals quickly. As a result, local events and cultural activities are delayed, hindering the revitalization of the local community. The objective of this invention is to solve these problems and provide a support system for efficient management of neighborhood associations. [Means for solving the problem]

[0005] The present invention relates to a system that uses a generative AI engine to support the management of neighborhood associations. Specifically, the system includes a means for using the generative AI engine to collect management information provided by the neighborhood association and store it in a database, a means for generating optimal management proposals based on the management information stored in the database, and a means for notifying neighborhood association members of the generated management proposals. The system also includes a means for supporting information sharing and communication among neighborhood association members using an electronic circular and communication tools, and a means for supporting neighborhood association event planning, accounting management, and activity feedback collection, thereby achieving efficient and effective neighborhood association management.

[0006] A "generative AI engine" is a system equipped with artificial intelligence technology that automatically generates appropriate suggestions and solutions based on data.

[0007] A "neighborhood association" is an organization in which residents of a certain area come together to solve local problems and hold events and activities.

[0008] A "database" is an information management system that efficiently stores and manages various information and data, and allows easy access when needed.

[0009] "Operational information" refers to all information related to the operation of the neighborhood association, such as neighborhood association activities and events, meeting records, and accounting information.

[0010] "Management proposals" are proposals that show specific action plans and improvement measures for the management of the neighborhood association, and are automatically generated by a generation AI engine.

[0011] An "electronic circular" is an information sharing tool that is circulated electronically, and is used to widely disseminate information to residents in the same way as a paper circular.

[0012] "Communication tools" are electronic means for supporting information exchange and communication between residents, and include chat and bulletin board functions.

[0013] "Event planning" is a series of processes for planning and implementing local events and activities held by neighborhood associations.

[0014] "Accounting management" refers to the task of understanding the financial situation of the neighborhood association, planning the budget, and settling expenses.

[0015] "Feedback collection" is the process of collecting evaluations and improvements from residents regarding activities and events that have been carried out, and reflecting this in future activities. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] This invention relates to a system for efficiently supporting the management of neighborhood associations. This system uses a generative AI engine to collect and store management information about neighborhood associations, and then generates and notifies optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing electronic circulars and communication tools. Furthermore, it also has functions to support specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection.

[0038] Explanation of program processing

[0039] 1. Supporting users' business operations

[0040] Users can input information about the operation of their neighborhood association into the system through their terminals. For example, when a user inputs planning information for a "summer festival," they enter details of the event (type, budget, number of participants, date and time, etc.). This information is sent from the terminal to the server.

[0041] 2. Role of the terminal

[0042] The terminal receives information input by the user and sends it to the server. It also displays suggestions and information returned from the server to the user. Specifically, it sends data entered by the user to the server in real time and reflects the generated suggestions on the display screen. The terminal supports information sharing and communication between users via electronic circulars and communication tools.

[0043] 3. Server Roles

[0044] The server receives the operational information sent from the device and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. The generated proposals are sent from the server to the device and notified to the user. The server also receives feedback information and updates the database and knowledge base.

[0045] Specific examples

[0046] For example, when members of a neighborhood association plan a "summer festival," the process goes as follows: First, the user logs in to their device and enters information about the "summer festival." At this time, details such as the budget, number of participants, and date and time are also entered. The entered data is sent from the device to a server, which stores it in a database.

[0047] Next, the server uses a generative AI engine to generate optimal proposals based on the collected data. For example, specific action plans such as "Install a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within a budget" are proposed. These proposals are sent from the server to the device and notified to the user.

[0048] The user reviews the proposal and decides whether to adopt it. If they do, they proceed with specific preparations based on the proposal. After the event is over, the user enters feedback on whether it was successful or not and what needs to be improved, and sends it to the server from their device.

[0049] Finally, the server stores the feedback information in a database and updates the knowledge base to reflect it in future proposals.In this way, the system of the present invention is expected to efficiently support the management of neighborhood associations and contribute to the revitalization of local communities.

[0050] The processing flow will be explained below.

[0051] Step 1:

[0052] A user logs in to a terminal and accesses the dashboard. The terminal prompts the user to enter their ID and password, and sends the entered information to the server. The server performs authentication, and if authentication is successful, returns the user's dashboard information to the terminal. The terminal displays the received dashboard information to the user.

[0053] Step 2:

[0054] The user selects "Summer Festival Plan" from the event planning menu and enters event information. The items to be entered include the event type (summer festival), budget (50,000 yen), number of participants (100 people), and date and time (August 1, 2023). The device sends this input data to the server.

[0055] Step 3:

[0056] The server accumulates the event information received from the terminal in a database. Specifically, it organizes information about summer festival planning and saves it in the database in an appropriate format.

[0057] Step 4:

[0058] The server runs a generative AI engine based on the information stored in the database to generate optimal management proposals. The generative AI engine references past data and existing knowledge bases to generate specific proposals such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[0059] Step 5:

[0060] The server sends the generated management proposal to the terminal, which displays the proposal to the user. The user checks the proposal and makes corrections or approvals as necessary.

[0061] Step 6:

[0062] If the user accepts the proposal, he or she clicks the "Accept" button. The terminal sends the instruction to the server, which records in the database that the proposal has been accepted. This starts the specific preparations for the event.

[0063] Step 7:

[0064] After the event, the user enters whether the event was successful or not and what needs to be improved in the feedback form. The device then sends this feedback information to the server.

[0065] Step 8:

[0066] The server stores the feedback information in a database and updates the knowledge base. The updated knowledge base is reflected in future proposal generation, enabling more accurate operational support.

[0067] As described above, the system of the present invention streamlines the series of steps involved in running a neighborhood association and provides more effective support for running the association.

[0068] Example 1

[0069] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0070] In traditional neighborhood association management, the collection of management information, analysis, proposal generation, information sharing, communication, and feedback management are often all done separately, making efficient management difficult. In particular, since the accumulation of management information and the reflection of feedback are done manually, management tasks take time and effort, and appropriate proposals may not be provided promptly. Furthermore, many neighborhood associations lack tools for effective event planning, accounting management, and information sharing and communication between members, which reduces the efficiency of management.

[0071] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0072] In this invention, the server includes means for collecting input management information using a generation AI engine and storing it in a database, means for generating optimal management proposals based on the management information stored in the database, means for notifying users of the generated management proposals, means for users to check the proposal contents and input feedback, means for saving the feedback information in the database and knowledge base, and means for improving future proposals based on updates to the knowledge base. This enables efficient collection, analysis, and proposal generation of neighborhood association management information, facilitates information sharing and communication between users, quickly reflects feedback, and continuously improves proposals by updating the knowledge base.

[0073] A "neighborhood association" is an organization in which local residents independently manage and carry out local welfare and activities.

[0074] A "generative AI engine" is a system that uses artificial intelligence technology to analyze input data and generate optimal suggestions and answers.

[0075] "Operational information" is information necessary for running the neighborhood association, including details of events, accounting information, and feedback from participants.

[0076] A "database" is a data collection system that systematically stores collected data and allows it to be retrieved as needed.

[0077] "Management proposals" are proposals for specific actions and plans to improve and support neighborhood association management, generated by the AI ​​engine based on management information.

[0078] "User" refers to an individual or group who is a member of the neighborhood association and uses the system to input operational information, review proposals, provide feedback, etc.

[0079] "Notification means" refers to a function or process for notifying users of the generated management proposal.

[0080] "Feedback" is information that records evaluations and opinions on proposals and actions, and is used to help improve proposals and actions in the future.

[0081] A "knowledge base" is a collection of knowledge accumulated based on past experience and feedback, which is used to make future proposals and decisions.

[0082] An "electronic circular" is a tool for sharing information in a digital format, and is an electronic alternative to traditional paper circulars.

[0083] "Communication tools" are software and applications that support information exchange and communication between users.

[0084] This invention relates to a system for efficiently supporting the management of neighborhood associations. This system has the function of collecting and accumulating management information about neighborhood associations using a generative AI engine, and then generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing electronic circulars and communication tools. Furthermore, it also has the function of supporting specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection.

[0085] An embodiment of the system includes the following hardware and software.

[0086] Hardware and Software

[0087] 1. Server: Collects, stores, and generates data. Analyzes it using an AI engine, generates operational proposals, and processes feedback.

[0088] 2. Terminal: Provides functions for user information input, data transmission and reception with the server, display of management proposals and information, electronic circulars, and communication tools.

[0089] 3. Generative AI engine: Analyzes operational information and generates optimal operational proposals.

[0090] Specific examples of processing

[0091] Enter user information

[0092] The user logs in to the device and enters event information and other operational information. For example, for a "Summer Festival" event, the user enters the following details:

[0093] Type: Summer Festival

[0094] Budget: 500,000 yen

[0095] Number of participants: 300 people

[0096] Date and Time: August 5th, 5pm to 9pm

[0097] Data transmission and storage

[0098] The terminal transmits the input data in real time to the server, which then stores the received data in a database.

[0099] Generate operational proposals

[0100] The server inputs the data stored in the database into the generative AI engine, which generates optimal management proposals based on the input data. For example, it may generate proposals such as "Install a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within a budget."

[0101] Proposal Notification

[0102] The generated management proposal is sent from the server to the terminal and notified to the user, who then reviews the proposal and decides whether to adopt it.

[0103] Gathering feedback

[0104] After the event, the user inputs feedback on whether it was successful or not and what needs to be improved, and sends it from the terminal to the server, which then stores the feedback information in the database and knowledge base.

[0105] Prompt Sentence Examples

[0106] Here is an example of inputting the following prompt sentence into a generative AI model:

[0107] User input: "I'd like to plan a summer festival event for the neighborhood association. The budget is 500,000 yen, and I expect 300 participants. The event will take place on August 5th from 5:00 PM to 9:00 PM. Please provide your proposal."

[0108] Based on these prompts, the generative AI engine generates specific management proposals, which are then sent to the user via the server. In this way, the operation of the neighborhood association is efficiently supported, contributing to the revitalization of the local community.

[0109] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0110] Step 1: Enter your information

[0111] The user logs in to the terminal. The user enters the ID and password and clicks the login button. This provides the terminal with user authentication information as input.

[0112] The terminal sends authentication information to the server, which then performs authentication and returns the result to the terminal. If authentication is successful, the user can proceed to the event information input screen.

[0113] Step 2: Enter your event information

[0114] The user inputs event information. For example, for a "summer festival," the user enters the following detailed information into the form: type (summer festival), budget (500,000 yen), number of participants (300 people), and date and time (August 5th, 5:00 PM to 9:00 PM). When the user enters the information and clicks the submit button, this information is given to the terminal as input.

[0115] The terminal collects the input information, formats the data, and sends it to the server in real time. This transmitted data becomes the input to the server.

[0116] Step 3: Save your data

[0117] The server analyzes the data received from the device and stores it in a database. The server takes the received data as input and stores it in a database using SQL queries, which stores the event information.

[0118] Step 4: Generate an operational proposal

[0119] The server inputs data stored in the database into the generative AI engine. The server issues SQL queries to obtain the necessary data and provides this data to the generative AI engine. The generative AI engine analyzes the input data and generates optimal management proposals. For example, it outputs proposals such as "Set up a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within the budget."

[0120] Step 5: Proposal Notification

[0121] The generated management proposal is sent from the server to the terminal. The server sends the generated proposal to the terminal in the form of an HTTP response. The terminal receives this proposal, processes it as input, and reflects it on the display screen. The user can then confirm the proposal.

[0122] Step 6: Provide feedback

[0123] After the event, the user enters feedback on whether the event was successful or not, and on areas for improvement. The user fills in the information in the feedback form and clicks the submit button. This information is provided to the terminal as input.

[0124] Step 7: Submit your feedback

[0125] The terminal transmits feedback information to the server. The terminal collects input feedback information and transmits it to the server. This transmitted feedback information becomes input to the server.

[0126] Step 8: Save your feedback and update your knowledge base

[0127] The server receives the feedback information sent from the device and stores it in a database and knowledge base. The server takes the received feedback information as input and stores it in a database using SQL queries. It also updates the knowledge base, so that the feedback is reflected in future suggestions.

[0128] This structure efficiently supports the administrative work of the neighborhood association and revitalizes local activities.

[0129] (Application example 1)

[0130] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0131] In current factory operations, production planning and work efficiency are dependent on manual work and experience, resulting in problems such as inefficiencies and malfunctions. There is also a lack of real-time information sharing between equipment and robots, making it time-consuming to coordinate work. Furthermore, collecting feedback and incorporating it into the next plan is time-consuming, often delaying improvements. To solve these issues, a system is needed that collects and analyzes factory operation information and automatically generates and notifies optimal work plans.

[0132] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0133] In this invention, the server includes means for collecting operation information using a generation AI engine and storing it in a database, means for generating an optimal work plan based on the operation information stored in the database, and means for displaying the generated work plan on the robot terminal, thereby improving the efficiency of factory operations and enabling work optimization and real-time information sharing.

[0134] A "generative AI engine" is a computer system that uses machine learning and deep learning technologies to generate optimal suggestions and predictions from given data.

[0135] "Operational information" refers to data necessary for the operation of an organization such as a factory or local government, and includes information such as production plans, work schedules, staff allocation, budgets, and the operating status of each piece of equipment.

[0136] "Database" means an electronic data storage system for systematically storing and managing collected operational information.

[0137] An "optimal work plan" is a plan that proposes work schedules and allocations that maximize efficiency and effectiveness based on collected operational information.

[0138] A "robot terminal" is a terminal device attached to a robot or equipment in a factory, and is a device that has the function of displaying a generated work plan.

[0139] "Feedback information" is data on evaluations and areas for improvement collected after work or an event is carried out, and is important information that can be reflected in future plans.

[0140] A "knowledge base" is a knowledge database that stores past operational information and feedback information and uses it to generate future proposals and make decisions.

[0141] An "electronic circular board" is a system for sharing and circulating information electronically, rather than through the circulation of physical documents.

[0142] "Communication tools" are software and services that support information sharing and communication among members, including chat, video calls, email, etc.

[0143] This invention relates to a system for streamlining factory operations. Specifically, it is a system that uses a generative AI engine to collect and accumulate operational information, and then generates and notifies optimal work plans. Furthermore, it achieves continuous improvement by collecting feedback and reflecting it in the next plan.

[0144] The system's programs are primarily implemented in Python. The Python web framework Flask is used to build the API server that collects data and generates suggestions. The generative AI engine uses advanced natural language processing models such as OpenAI's GPT-3.

[0145] The hardware used will consist of terminals installed on the robots used in factories and a central management server. The terminals are expected to be mainly durable industrial tablets or interface devices built into the robots themselves.

[0146] First, the user (factory manager) inputs information about factory operations into the system via a terminal. Operational information includes the operating status of each piece of equipment, production plans, work plans, staff allocation, budgets, etc. This information is sent to the server in real time and stored in a database.

[0147] Next, the server uses a generative AI engine to generate an optimal work plan based on the accumulated data. The generated work plan includes specific steps, deployment, and personnel planning. The proposed results are then sent back from the server to the device and notified to the user.

[0148] For example, if a factory manager is seeking suggestions for how to run a new production line more efficiently, he might enter the following information into the system:

[0149] Number of machines in operation: 10

[0150] Number of staff: 5

[0151] Target production volume: 500 units / day

[0152] Budget: 500,000 yen

[0153] Here are some examples of prompts based on the input:

[0154] Propose the best work plan based on the factory's operational information, including:

[0155] Number of machines in operation: 10

[0156] Number of staff: 5

[0157] Target production volume: 500 units / day

[0158] Budget: 500,000 yen

[0159] Use this information to suggest an efficient work plan.

[0160] The system uses these prompts to generate a work plan using a generative AI engine. The resulting proposals include specific suggestions such as "distributing staff between machine maintenance and production line supervision," "procuring necessary materials within budget," and "prioritizing work such as frames." The generated proposals are displayed on the robot's terminal screen, allowing the user to proceed with the work based on them.

[0161] After the event is completed, users can input their feedback information into their devices and send it to the server, which then stores the collected feedback in a database and knowledge base and uses it to improve future operational proposals, thereby continuously improving operational efficiency.

[0162] In this way, the present invention not only achieves more efficient factory operations, but also enables continuous improvement through real-time information sharing and feedback collection.

[0163] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0164] Step 1:

[0165] Users input information about factory operations into the terminal. Specific information includes the number of machines in operation, the number of staff, target production volume, and budget. This information is saved on the terminal in data format such as JSON. The input data is sent to the server in real time.

[0166] input:

[0167] Number of machines in operation

[0168] Number of staff

[0169] Target production volume

[0170] budget

[0171] output:

[0172] JSON data sent to the server

[0173] Step 2:

[0174] The terminal sends the operational information entered by the user to the server. The server stores the received data in a database. Specifically, an INSERT query is issued to store each piece of operational information in the appropriate table in the database.

[0175] input:

[0176] Operational information entered by the user

[0177] output:

[0178] Operational information stored in the database

[0179] Step 3:

[0180] The server generates a prompt for the AI ​​engine based on the operational information stored in the database. The prompt text includes the operational information entered by the user and is generated in a format that encourages the proposal of an optimal work plan. This prompt text is sent to the AI ​​engine as an API request.

[0181] input:

[0182] Operational information stored in a database

[0183] output:

[0184] Prompt sent to the generative AI engine

[0185] Step 4:

[0186] The server receives the proposed work plan from the generative AI engine. The generative AI engine generates an optimal work plan based on the prompt and returns the result to the server. The server then analyzes it and stores it in a database.

[0187] input:

[0188] Work plan proposals from a generative AI engine

[0189] output:

[0190] Work plans stored in the database

[0191] Step 5:

[0192] The server sends the generated work plan to the terminal, which displays the received work plan on its screen and notifies the user. The user confirms the proposed content and begins work.

[0193] input:

[0194] Generated Work Plan

[0195] output:

[0196] Work plan displayed on the device

[0197] Step 6:

[0198] After completing a task, the user inputs feedback information into the terminal. The feedback information includes successes, problems, and areas for improvement. This feedback information is then sent back to the server.

[0199] input:

[0200] Feedback Information

[0201] output:

[0202] Feedback information sent to the server

[0203] Step 7:

[0204] The server stores the received feedback information in the database and knowledge base. Specifically, it stores the feedback information in the appropriate table of the database using an INSERT query and updates the knowledge base.

[0205] input:

[0206] Feedback Information

[0207] output:

[0208] Feedback information stored in databases and knowledge bases

[0209] These steps will streamline factory operations, enable real-time information sharing, and enable continuous improvement.

[0210] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0211] The present invention relates to a system that efficiently supports the management of neighborhood associations by combining a generative AI engine and an emotion engine. This system has the function of collecting and accumulating management information about the neighborhood association and generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing an electronic circular and communication tools. Furthermore, in addition to functions that support specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection, the system also has a means for recognizing user emotions using an emotion engine and making management proposals and communication support based on those emotions.

[0212] Explanation of program processing

[0213] 1. Supporting users' business operations

[0214] Users input information about the operation of their neighborhood association into the system via their terminal. For example, when a user inputs planning information for a "summer festival," they input details of the event (type, budget, number of participants, date and time, etc.). This information is sent from the terminal to the server.

[0215] 2. Role of the terminal

[0216] The terminal receives information input by the user and sends it to the server. It also displays suggestions and information returned from the server to the user. Specifically, it sends data entered by the user to the server in real time and reflects the generated suggestions on the display screen. The terminal supports information sharing and communication between users via electronic circulars and communication tools.

[0217] 3. Server Roles

[0218] The server receives the operational information sent from the device and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. The generated proposals are sent from the server to the device and notified to the user. The server also receives feedback information and updates the database and knowledge base.

[0219] 4. The Role of the Emotional Engine

[0220] The emotion engine recognizes the user's emotional state and reflects it in operational proposals and communication support. Specifically, it analyzes emotions based on user input, dialogue history, and facial expression analysis, and generates operational proposals that are adapted to the user's emotional state, such as making suggestions that reduce stress when the user's stress level is high.

[0221] Specific examples

[0222] For example, when members of a neighborhood association plan a "summer festival," the process goes as follows: First, the user logs in to their device and enters information about the "summer festival." At this time, details such as the budget, number of participants, and date and time are also entered. The entered data is sent from the device to a server, which stores it in a database.

[0223] Next, the server uses a generative AI engine to generate optimal suggestions based on the collected data. For example, specific action plans such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and drinks within a budget" are proposed. At the same time, an emotion engine is also running to analyze the user's emotional state. For example, if the user is feeling stressed, suggestions may include elements such as "division of tasks to reduce the burden." The generated suggestions are sent from the server to the device and notified to the user.

[0224] The user reviews the proposal and decides whether to adopt it. If they do, they proceed with specific preparations based on the proposal. After the event is over, the user enters feedback on whether it was successful or not and what needs to be improved, and sends it to the server from their device.

[0225] Finally, the server saves the feedback information in a database and updates the knowledge base. The updated knowledge base will be reflected in the next proposal generation, enabling more accurate operational support. In addition, since the feedback information also includes the user's emotional state, the emotion engine also contributes to updating the knowledge base in cooperation with the server. This will enable customized proposals to be made to individual users in the future.

[0226] In this way, the system of the present invention, which combines a generative AI engine and an emotion engine, streamlines the management operations of neighborhood associations and, by taking into consideration the emotions of members, provides more effective and satisfying management support.

[0227] The processing flow will be explained below.

[0228] Step 1:

[0229] A user logs in to a terminal and accesses the dashboard. The terminal prompts the user to enter their ID and password, and sends the entered information to the server. The server authenticates the user, and if authentication is successful, returns the user's dashboard information to the terminal. The terminal displays the received dashboard information to the user.

[0230] Step 2:

[0231] The user selects "Summer Festival Plan" from the event planning menu and enters event information. The items to be entered include the event type (summer festival), budget (50,000 yen), number of participants (100 people), and date and time (August 1, 2023). The device sends this input data to the server.

[0232] Step 3:

[0233] The server accumulates the event information received from the terminal in a database. Specifically, it organizes information about summer festival planning and saves it in the database in an appropriate format.

[0234] Step 4:

[0235] The server runs a generative AI engine based on the information stored in the database to generate optimal management proposals. The generative AI engine references past data and existing knowledge bases to generate specific proposals such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[0236] Step 5:

[0237] The emotion engine analyzes the user's emotional state based on input data, the user's dialogue history, facial expression analysis, etc. For example, if the user is feeling stressed, it will output a result that the stress level is high. The emotion engine then sends this emotional data to the server.

[0238] Step 6:

[0239] The server reflects the data from the emotion engine in the generated operational proposals and adjusts them based on the user's emotional state. For example, the proposals may include elements such as "division of roles to reduce workload" and "relaxing activities." The adjusted proposals are then sent to the device and notified to the user.

[0240] Step 7:

[0241] The user checks the proposal displayed on the terminal. If the proposal is satisfactory, they click the "Accept" button to accept the proposal. The terminal sends this instruction to the server, which records the adoption of the proposal in the database. This starts the specific preparations for the event.

[0242] Step 8:

[0243] After the event, the user fills in a feedback form to indicate whether the event was successful, what needs to be improved, and how they felt during the event. The device then sends this feedback information to the server.

[0244] Step 9:

[0245] The server saves the feedback information in a database and updates the knowledge base. The updated knowledge base is reflected in the next proposal generation, enabling more accurate operational support. In addition, since the feedback information also includes the user's emotional state, the emotion engine also works together to contribute to updating the knowledge base.

[0246] As described above, the system of the present invention not only improves the efficiency of neighborhood association management operations, but also makes the management of neighborhood associations more effective and satisfying by making individual suggestions that take into consideration the feelings of members.

[0247] Example 2

[0248] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0249] In the management of local governments, it is necessary to efficiently carry out a series of processes, from planning to execution and feedback collection, and to facilitate information sharing and communication among members. It is also important to make optimal management proposals while taking into consideration the emotional state of each member. Conventional systems have had difficulty meeting these requirements and have had problems such as a heavy workload.

[0250] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0251] In this invention, the server includes means for collecting management information provided by the local government and storing it in a data storage device, means for generating optimal management proposals based on the management information stored in the data storage device, means for notifying members of the local government of the generated management proposals, means for recognizing the emotional state of users using an emotion analysis system and reflecting this in the management proposals, and means for users to input feedback and update the data storage device. This makes it possible to streamline the management operations of the local government, facilitate information sharing and communication between members, and make optimal proposals that take into consideration the emotions of members.

[0252] A "local government" is an organization that operates and manages a local community and is composed of local residents and their representatives.

[0253] A "generative AI system" is an artificial intelligence system that analyzes input data and automatically generates suggestions and information tailored to specific purposes.

[0254] A "data store" is a database or storage system for storing collected data or information.

[0255] An "emotion analysis system" is a system that recognizes and analyzes a user's emotional state based on input, dialogue history, facial expression analysis, etc.

[0256] "Users" are individuals or members involved in the operation of the local government, who operate the system to input information and receive suggestions.

[0257] "Feedback" refers to information such as evaluations, opinions, and improvements provided by users regarding proposals and activities carried out.

[0258] A "bulletin board" is a digital platform for publishing and sharing information over the Internet or a local network.

[0259] "Communication tools" are software and applications for sending and receiving messages and for real-time communication.

[0260] This invention relates to a system that efficiently supports the management of local governments by combining a generative AI system and an emotion analysis system. This system has the function of collecting and accumulating management information about local governments and generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among local government members by utilizing electronic bulletin boards and communication tools. Furthermore, in addition to functions that support specific local government management tasks such as event planning, financial management, and activity feedback collection, it also has a means for recognizing user emotions using an emotion analysis system and making management proposals and communication support based on those emotions.

[0261] System hardware and software configuration

[0262] This system consists of a server, a terminal, and a user. Details of each component are shown below.

[0263] server

[0264] The server includes a data storage device, a generative AI system, and an emotion analysis system. The data storage device functions as a database, storing the municipality's operational information and feedback information. The generative AI system analyzes the collected data and generates optimal operational proposals. The emotion analysis system analyzes the user's emotional state and reflects it in the operational proposals.

[0265] Terminal

[0266] The terminal is a device that allows users to access the system and input information. The information entered by the user is sent from the terminal to the server in real time. The terminal also displays suggestions and notifications generated as responses from the server. The terminal supports information sharing and communication between members through electronic bulletin boards and communication tools.

[0267] User

[0268] Users are individuals or members involved in the operation of the local government, who input information through their terminals and receive proposals from the server. Users log in to access the dashboard and input the necessary operational information (e.g., the name of the "Summer Festival," the budget, the number of participants, the date and time, etc.). They also have the role of sending feedback on the proposals.

[0269] Specific examples of behavior

[0270] For example, when members of a local government plan a "summer festival," the process is as follows:

[0271] 1. The user logs in to the device and enters details about the "Summer Festival," including the budget, number of participants, date and time, etc.

[0272] 2. The terminal sends the entered information to the server.

[0273] 3. The server stores the received data in a database and uses a generative AI system to generate optimal operation proposals, such as specific action plans such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[0274] 4. At the same time, the emotion analysis system analyzes the user's emotional state and, for example, if the user is feeling stressed, adds elements such as "division of roles to reduce the burden" to the suggestions.

[0275] 5. The generated proposal is sent from the server to the device and notified to the user.

[0276] 6. The user reviews the proposal and decides whether to adopt it. If necessary, the user can enter feedback and send it to the server from the device.

[0277] 7. The server stores the feedback information in a database and updates the knowledge base, which improves the accuracy of future suggestions. It also takes into account information about the user's emotional state, resulting in more personalized suggestions.

[0278] Prompt Sentence Examples

[0279] "Generate specific proposals for planning a summer festival. Please take into consideration conditions such as the budget, number of participants, date and time, etc. Also, if users are under a lot of stress, please include ideas for reducing their stress."

[0280] In this way, by combining a generative AI system with an emotion analysis system, it is possible to streamline local government management operations and, by taking into consideration the emotions of members, provide more effective and satisfying management support.

[0281] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0282] Step 1:

[0283] A user logs in to a terminal. User input: User ID and password. Output: User's dashboard. Operation: The user enters their user ID and password on the terminal's login screen. The terminal sends this information to the server, which performs authentication. If authentication is successful, the server returns the user's dashboard to the terminal.

[0284] Step 2:

[0285] The user enters operational information. User input: Details of the "Summer Festival" (name, budget, number of participants, date and time, etc.). Output: Press the send button to prepare for data transmission. Operation: The user enters detailed information about the "Summer Festival" project from the dashboard and clicks the "Send" button.

[0286] Step 3:

[0287] The terminal sends operational information from the user to the server. Input: Operational information (name, budget, number of participants, date and time, etc.). Output: Sends data to the server. Operation: The terminal sends the information entered by the user to the server in real time.

[0288] Step 4:

[0289] The server saves the received data in the database. Input: Operational information. Output: Saving to database completed. Operation: The server verifies the received data, confirms its validity, and saves it in the database.

[0290] Step 5:

[0291] The server retrieves management information from the database and generates management proposals using a generative AI system. Input: Management information stored in the database. Output: Optimal management proposals. Operation: The server's generative AI system analyzes the data and generates specific action plans such as "setting up a game corner and food stalls" and "recruiting local volunteers."

[0292] Step 6:

[0293] The emotion analysis system analyzes the user's emotional state and adjusts operational proposals. Input: User's past logs and dialogue history. Output: Proposals reflected in the emotional state. Operation: The emotion analysis system analyzes the user's emotional state based on past input data and dialogue history, and if stress is high, adds proposals such as "division of roles to reduce burden."

[0294] Step 7:

[0295] The server sends the adjusted management proposal to the terminal. Input: Adjusted management proposal. Output: Transmission to terminal completed. Operation: The server sends the final management proposal to the terminal, and the terminal notifies the user of this content.

[0296] Step 8:

[0297] The user confirms the proposal and sends feedback. User input: Proposal confirmation, feedback input. Output: Feedback data sent successfully. Operation: The user confirms the proposal, enters feedback if necessary, and presses the "Send" button. The device sends this feedback to the server.

[0298] Step 9:

[0299] The server saves the feedback information in the database and updates the knowledge base. Input: Feedback data. Output: Database and knowledge base updated. Operation: The server saves the feedback information in the database and updates the knowledge base. It also works with an emotion analysis system to add additional data based on the emotional state to the knowledge base.

[0300] (Application example 2)

[0301] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0302] Conventional management support systems for neighborhood associations and stores are limited to collecting management information and generating proposals, and have the problem of not being able to make management proposals that take into account the emotional state of members and staff. This increases stress and burden, and leads to problems such as reduced management efficiency and satisfaction.

[0303] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0304] In this invention, the server includes means for collecting management information provided by the management target using a generation AI engine and storing it in a database, means for generating optimal management proposals based on the management information stored in the database, means for notifying the members of the management target of the generated management proposals, and means for analyzing the emotional states of the members using an emotion engine and generating proposals based on the analyzed emotional states. This improves management efficiency and enables management proposals that take into account the emotional states of members and staff.

[0305] The "generative AI engine" is an artificial intelligence system that analyzes operational information and automatically generates optimal proposals.

[0306] The "Emotion Engine" is a system that analyzes the emotional state of members and staff and makes operational suggestions and communication support based on that analysis.

[0307] "Operation information" refers to data related to operations provided by the operation target (for example, sales information, shift information, event details, etc.).

[0308] A "database" is a digital storage system for storing and managing operational information and feedback information.

[0309] An "operational proposal" is a specific action plan for improving operational efficiency that is generated by the AI ​​engine based on operational information.

[0310] "Notification means" refers to a communication means for communicating the generated management proposal to members and staff.

[0311] An "electronic circular" is a tool for sharing information in digital format, with the purpose of facilitating the communication of information between members.

[0312] "Communication tools" are digital tools that support communication and information sharing between members and staff.

[0313] "Feedback information" is information about the success or failure of the management or event and areas for improvement, and is reflected in the generation of proposals from the next time onwards.

[0314] This invention relates to a system that combines a generative AI engine and an emotion engine to improve the efficiency of brick-and-mortar store operations and provide operational support that takes into account the emotions of staff and customers. This system includes the following components and processing procedures:

[0315] Supporting users' work

[0316] Users input information about the operation of their physical stores (e.g., sales information, shift information, event plans, etc.) into the system via their smartphones. For example, when entering planning information for a "Christmas sale," they also enter details of the event (date and time, sales target, budget, special product inventory information, etc.). This information is sent from the smartphone to the cloud server.

[0317] Device Role

[0318] The smartphone receives input information from users and sends it to the cloud server in real time. It also displays suggestions and information returned from the cloud server to users. Furthermore, it supports information sharing and communication among staff members via electronic circulars and communication tools.

[0319] Server Roles

[0320] The cloud server receives the operational information sent from the smartphone and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. For example, these proposals include "discounts on products in specific categories" and "implementing social media campaigns" for sales. The generated proposals are sent from the cloud server to the smartphone and notified to the user.

[0321] The role of the emotional engine

[0322] The emotion engine recognizes the emotional state of users and staff and reflects this in operational proposals and communication support. Specifically, it analyzes emotions based on user input, dialogue history, and facial expression analysis, and makes suggestions that are less stressful when stress levels are high, for example. This reduces staff stress and improves operational efficiency.

[0323] Hardware and software used

[0324] Smartphone (iOS or Android)

[0325] Cloud server (AWS or Google Cloud)

[0326] Database (MySQL or MongoDB)

[0327] Generative AI engine (OpenAI GPT-4)

[0328] Emotion engine (Affectiva or Solid Recognition technology)

[0329] Example

[0330] For example, when a brick-and-mortar store owner plans a "Christmas sale," the process goes as follows: First, the store owner logs into their smartphone and enters information about the "Christmas sale." This includes details such as the budget, sales target, and stock information for special items. The entered data is sent from the smartphone to a cloud server, which then stores it in a database.

[0331] Next, the cloud server uses a generative AI engine to generate optimal proposals based on the collected data. Specific action plans are proposed, such as "discounts on products in specific categories," "rewarding shopping points," and "implementing social media campaigns." At the same time, an emotion engine is also running to analyze the emotional state of staff. For example, if a staff member is feeling stressed, suggestions might include adjusting shifts to reduce the burden. The generated proposals are sent from the cloud server to smartphones, where they are notified to the owner and staff.

[0332] Example prompt sentence:

[0333] Generate optimal store management proposals based on the following data:

[0334] (Event name) Christmas Sale

[0335] (Date and time) December 24, 2023 - December 25, 2023

[0336] (Target sales) 1 million yen

[0337] (Budget) 200,000 yen

[0338] (Special product) Christmas limited edition cake, gift set

[0339] (Discount information) 10% off all products, 20% off some products

[0340] (Staff shift) 4 people / day

[0341] We trust the suggestions made by the generative AI engine, so please make suggestions that take into consideration increasing sales and reducing the burden on staff.

[0342] In this way, by combining a generative AI engine and an emotion engine, it is possible to improve operational efficiency and provide operational support that takes into account the emotional state of staff.

[0343] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0344] Step 1:

[0345] Users input store operation information (e.g., sales information, shift information, event plans, etc.) into the system via their smartphones. This input includes detailed information about the "Christmas sale" (date and time, sales target, budget, special product inventory information, etc.). The input information is sent from the smartphone to the cloud server.

[0346] Input: Sales information, shift information, event planning and other operational information

[0347] Data calculation and processing: Collects information provided by users and sends it to the cloud server

[0348] Output: Operational information stored on the cloud server

[0349] Step 2:

[0350] The cloud server receives the operational information sent from the smartphone and stores it in a database, allowing for centralized management of the operational information.

[0351] Input: Operational information sent from smartphone

[0352] Data calculation and processing: Received operational information is formatted and stored in a database

[0353] Output: Operational information stored in the database

[0354] Step 3:

[0355] The cloud server analyzes the operational information stored in the database and uses a generative AI engine to generate optimal operational proposals, such as discount plans to achieve sales targets, implementing social media campaigns, and managing inventory for special products.

[0356] Input: Operational information stored in the database

[0357] Data calculation and processing: Data analysis and proposal generation using a generative AI engine

[0358] Output: Optimal operational proposal

[0359] Step 4:

[0360] The emotion engine recognizes the emotional state of users and staff and reflects this in operational suggestions. For example, it generates suggestions to reduce stress based on user input, dialogue history, and facial expression analysis if stress levels are high.

[0361] Input: User emotion data, input history, facial expression information

[0362] Data Calculation and Processing: Emotional State Analysis and Adaptive Suggestion Generation by Emotion Engine

[0363] Output: Operational suggestions adapted to the user's emotional state

[0364] Step 5:

[0365] The cloud server sends the generated management proposal to the smartphone and notifies the user, who then reviews the proposal and decides whether to adopt it.

[0366] Input: Optimal operational suggestions, suggestions adapted to emotional state

[0367] Data calculation and processing: Transfer and notification of proposal contents

[0368] Output: Proposal content notified to smartphone

[0369] Step 6:

[0370] Users can input feedback on the implemented proposals into the system via their smartphones, including feedback on whether the proposal was successful or not, as well as areas for improvement. The input information is then sent back to the cloud server.

[0371] Input: Feedback information (success or failure, areas for improvement, etc.)

[0372] Data calculation and processing: Collect feedback information from users and send it to the cloud server

[0373] Output: Feedback information stored on the cloud server

[0374] Step 7:

[0375] The cloud server stores the feedback information in a database and updates the knowledge base, allowing the generative AI engine to use more accurate information to generate future management proposals.

[0376] Input: Feedback information, operational data

[0377] Data calculation and processing: Feedback information stored in a database and knowledge base updated

[0378] Output: Improved accuracy of proposals from next time onwards

[0379] This processing step efficiently executes a series of operational support processes, from collecting operational information to generating proposals, notifying proposals, collecting feedback, and updating the knowledge base.

[0380] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0381] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0382] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0383] [Second embodiment]

[0384] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0385] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0386] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0387] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0388] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0389] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0390] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0391] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0392] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0393] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0394] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0395] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0396] This invention relates to a system for efficiently supporting the management of neighborhood associations. This system uses a generative AI engine to collect and store management information about neighborhood associations, and then generates and notifies optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing electronic circulars and communication tools. Furthermore, it also has functions to support specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection.

[0397] Explanation of program processing

[0398] 1. Supporting users' business operations

[0399] Users can input information about the operation of their neighborhood association into the system through their terminals. For example, when a user inputs planning information for a "summer festival," they enter details of the event (type, budget, number of participants, date and time, etc.). This information is sent from the terminal to the server.

[0400] 2. Role of the terminal

[0401] The terminal receives information input by the user and sends it to the server. It also displays suggestions and information returned from the server to the user. Specifically, it sends data entered by the user to the server in real time and reflects the generated suggestions on the display screen. The terminal supports information sharing and communication between users via electronic circulars and communication tools.

[0402] 3. Server Roles

[0403] The server receives the operational information sent from the device and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. The generated proposals are sent from the server to the device and notified to the user. The server also receives feedback information and updates the database and knowledge base.

[0404] Specific examples

[0405] For example, when members of a neighborhood association plan a "summer festival," the process goes as follows: First, the user logs in to their device and enters information about the "summer festival." At this time, details such as the budget, number of participants, and date and time are also entered. The entered data is sent from the device to a server, which stores it in a database.

[0406] Next, the server uses a generative AI engine to generate optimal proposals based on the collected data. For example, specific action plans such as "Install a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within a budget" are proposed. These proposals are sent from the server to the device and notified to the user.

[0407] The user reviews the proposal and decides whether to adopt it. If they do, they proceed with specific preparations based on the proposal. After the event is over, the user enters feedback on whether it was successful or not and what needs to be improved, and sends it to the server from their device.

[0408] Finally, the server stores the feedback information in a database and updates the knowledge base to reflect it in future proposals.In this way, the system of the present invention is expected to efficiently support the management of neighborhood associations and contribute to the revitalization of local communities.

[0409] The processing flow will be explained below.

[0410] Step 1:

[0411] A user logs in to a terminal and accesses the dashboard. The terminal prompts the user to enter their ID and password, and sends the entered information to the server. The server performs authentication, and if authentication is successful, returns the user's dashboard information to the terminal. The terminal displays the received dashboard information to the user.

[0412] Step 2:

[0413] The user selects "Summer Festival Plan" from the event planning menu and enters event information. The items to be entered include the event type (summer festival), budget (50,000 yen), number of participants (100 people), and date and time (August 1, 2023). The device sends this input data to the server.

[0414] Step 3:

[0415] The server accumulates the event information received from the terminal in a database. Specifically, it organizes information about summer festival planning and saves it in the database in an appropriate format.

[0416] Step 4:

[0417] The server runs a generative AI engine based on the information stored in the database to generate optimal management proposals. The generative AI engine references past data and existing knowledge bases to generate specific proposals such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[0418] Step 5:

[0419] The server sends the generated management proposal to the terminal, which displays the proposal to the user. The user checks the proposal and makes corrections or approvals as necessary.

[0420] Step 6:

[0421] If the user accepts the proposal, he or she clicks the "Accept" button. The terminal sends the instruction to the server, which records in the database that the proposal has been accepted. This starts the specific preparations for the event.

[0422] Step 7:

[0423] After the event, the user enters whether the event was successful or not and what needs to be improved in the feedback form. The device then sends this feedback information to the server.

[0424] Step 8:

[0425] The server stores the feedback information in a database and updates the knowledge base. The updated knowledge base is reflected in future proposal generation, enabling more accurate operational support.

[0426] As described above, the system of the present invention streamlines the series of steps involved in running a neighborhood association and provides more effective support for running the association.

[0427] Example 1

[0428] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0429] In traditional neighborhood association management, the collection of management information, analysis, proposal generation, information sharing, communication, and feedback management are often all done separately, making efficient management difficult. In particular, since the accumulation of management information and the reflection of feedback are done manually, management tasks take time and effort, and appropriate proposals may not be provided promptly. Furthermore, many neighborhood associations lack tools for effective event planning, accounting management, and information sharing and communication between members, which reduces the efficiency of management.

[0430] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0431] In this invention, the server includes means for collecting input management information using a generation AI engine and storing it in a database, means for generating optimal management proposals based on the management information stored in the database, means for notifying users of the generated management proposals, means for users to check the proposal contents and input feedback, means for saving the feedback information in the database and knowledge base, and means for improving future proposals based on updates to the knowledge base. This enables efficient collection, analysis, and proposal generation of neighborhood association management information, facilitates information sharing and communication between users, quickly reflects feedback, and continuously improves proposals by updating the knowledge base.

[0432] A "neighborhood association" is an organization in which local residents independently manage and carry out local welfare and activities.

[0433] A "generative AI engine" is a system that uses artificial intelligence technology to analyze input data and generate optimal suggestions and answers.

[0434] "Operational information" is information necessary for running the neighborhood association, including details of events, accounting information, and feedback from participants.

[0435] A "database" is a data collection system that systematically stores collected data and allows it to be retrieved as needed.

[0436] "Management proposals" are proposals for specific actions and plans to improve and support neighborhood association management, generated by the AI ​​engine based on management information.

[0437] "User" refers to an individual or group who is a member of the neighborhood association and uses the system to input operational information, review proposals, provide feedback, etc.

[0438] "Notification means" refers to a function or process for notifying users of the generated management proposal.

[0439] "Feedback" is information that records evaluations and opinions on proposals and actions, and is used to help improve proposals and actions in the future.

[0440] A "knowledge base" is a collection of knowledge accumulated based on past experience and feedback, which is used to make future proposals and decisions.

[0441] An "electronic circular" is a tool for sharing information in a digital format, and is an electronic alternative to traditional paper circulars.

[0442] "Communication tools" are software and applications that support information exchange and communication between users.

[0443] This invention relates to a system for efficiently supporting the management of neighborhood associations. This system has the function of collecting and accumulating management information about neighborhood associations using a generative AI engine, and then generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing electronic circulars and communication tools. Furthermore, it also has the function of supporting specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection.

[0444] An embodiment of the system includes the following hardware and software.

[0445] Hardware and Software

[0446] 1. Server: Collects, stores, and generates data. Analyzes it using an AI engine, generates operational proposals, and processes feedback.

[0447] 2. Terminal: Provides functions for user information input, data transmission and reception with the server, display of management proposals and information, electronic circulars, and communication tools.

[0448] 3. Generative AI engine: Analyzes operational information and generates optimal operational proposals.

[0449] Specific examples of processing

[0450] Enter user information

[0451] The user logs in to the device and enters event information and other operational information. For example, for a "Summer Festival" event, the user enters the following details:

[0452] Type: Summer Festival

[0453] Budget: 500,000 yen

[0454] Number of participants: 300 people

[0455] Date and Time: August 5th, 5pm to 9pm

[0456] Data transmission and storage

[0457] The terminal transmits the input data in real time to the server, which then stores the received data in a database.

[0458] Generate operational proposals

[0459] The server inputs the data stored in the database into the generative AI engine, which generates optimal management proposals based on the input data. For example, it may generate proposals such as "Install a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within a budget."

[0460] Proposal Notification

[0461] The generated management proposal is sent from the server to the terminal and notified to the user, who then reviews the proposal and decides whether to adopt it.

[0462] Gathering feedback

[0463] After the event, the user inputs feedback on whether it was successful or not and what needs to be improved, and sends it from the terminal to the server, which then stores the feedback information in the database and knowledge base.

[0464] Prompt Sentence Examples

[0465] Here is an example of inputting the following prompt sentence into a generative AI model:

[0466] User input: "I'd like to plan a summer festival event for the neighborhood association. The budget is 500,000 yen, and I expect 300 participants. The event will take place on August 5th from 5:00 PM to 9:00 PM. Please provide your proposal."

[0467] Based on these prompts, the generative AI engine generates specific management proposals, which are then sent to the user via the server. In this way, the operation of the neighborhood association is efficiently supported, contributing to the revitalization of the local community.

[0468] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0469] Step 1: Enter your information

[0470] The user logs in to the terminal. The user enters the ID and password and clicks the login button. This provides the terminal with user authentication information as input.

[0471] The terminal sends authentication information to the server, which then performs authentication and returns the result to the terminal. If authentication is successful, the user can proceed to the event information input screen.

[0472] Step 2: Enter your event information

[0473] The user inputs event information. For example, for a "summer festival," the user enters the following detailed information into the form: type (summer festival), budget (500,000 yen), number of participants (300 people), and date and time (August 5th, 5:00 PM to 9:00 PM). When the user enters the information and clicks the submit button, this information is given to the terminal as input.

[0474] The terminal collects the input information, formats the data, and sends it to the server in real time. This transmitted data becomes the input to the server.

[0475] Step 3: Save your data

[0476] The server analyzes the data received from the device and stores it in a database. The server takes the received data as input and stores it in a database using SQL queries, which stores the event information.

[0477] Step 4: Generate an operational proposal

[0478] The server inputs data stored in the database into the generative AI engine. The server issues SQL queries to obtain the necessary data and provides this data to the generative AI engine. The generative AI engine analyzes the input data and generates optimal management proposals. For example, it outputs proposals such as "Set up a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within the budget."

[0479] Step 5: Proposal Notification

[0480] The generated management proposal is sent from the server to the terminal. The server sends the generated proposal to the terminal in the form of an HTTP response. The terminal receives this proposal, processes it as input, and reflects it on the display screen. The user can then confirm the proposal.

[0481] Step 6: Provide feedback

[0482] After the event, the user enters feedback on whether the event was successful or not, and on areas for improvement. The user fills in the information in the feedback form and clicks the submit button. This information is provided to the terminal as input.

[0483] Step 7: Submit your feedback

[0484] The terminal transmits feedback information to the server. The terminal collects input feedback information and transmits it to the server. This transmitted feedback information becomes input to the server.

[0485] Step 8: Save your feedback and update your knowledge base

[0486] The server receives the feedback information sent from the device and stores it in a database and knowledge base. The server takes the received feedback information as input and stores it in a database using SQL queries. It also updates the knowledge base, so that the feedback is reflected in future suggestions.

[0487] This structure efficiently supports the administrative work of the neighborhood association and revitalizes local activities.

[0488] (Application example 1)

[0489] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0490] In current factory operations, production planning and work efficiency are dependent on manual work and experience, resulting in problems such as inefficiencies and malfunctions. There is also a lack of real-time information sharing between equipment and robots, making it time-consuming to coordinate work. Furthermore, collecting feedback and incorporating it into the next plan is time-consuming, often delaying improvements. To solve these issues, a system is needed that collects and analyzes factory operation information and automatically generates and notifies optimal work plans.

[0491] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0492] In this invention, the server includes means for collecting operation information using a generation AI engine and storing it in a database, means for generating an optimal work plan based on the operation information stored in the database, and means for displaying the generated work plan on the robot terminal, thereby improving the efficiency of factory operations and enabling work optimization and real-time information sharing.

[0493] A "generative AI engine" is a computer system that uses machine learning and deep learning technologies to generate optimal suggestions and predictions from given data.

[0494] "Operational information" refers to data necessary for the operation of an organization such as a factory or local government, and includes information such as production plans, work schedules, staff allocation, budgets, and the operating status of each piece of equipment.

[0495] "Database" means an electronic data storage system for systematically storing and managing collected operational information.

[0496] An "optimal work plan" is a plan that proposes work schedules and allocations that maximize efficiency and effectiveness based on collected operational information.

[0497] A "robot terminal" is a terminal device attached to a robot or equipment in a factory, and is a device that has the function of displaying a generated work plan.

[0498] "Feedback information" is data on evaluations and areas for improvement collected after work or an event is carried out, and is important information that can be reflected in future plans.

[0499] A "knowledge base" is a knowledge database that stores past operational information and feedback information and uses it to generate future proposals and make decisions.

[0500] An "electronic circular board" is a system for sharing and circulating information electronically, rather than through the circulation of physical documents.

[0501] "Communication tools" are software and services that support information sharing and communication among members, including chat, video calls, email, etc.

[0502] This invention relates to a system for streamlining factory operations. Specifically, it is a system that uses a generative AI engine to collect and accumulate operational information, and then generates and notifies optimal work plans. Furthermore, it achieves continuous improvement by collecting feedback and reflecting it in the next plan.

[0503] The system's programs are primarily implemented in Python. The Python web framework Flask is used to build the API server that collects data and generates suggestions. The generative AI engine uses advanced natural language processing models such as OpenAI's GPT-3.

[0504] The hardware used will consist of terminals installed on the robots used in factories and a central management server. The terminals are expected to be mainly durable industrial tablets or interface devices built into the robots themselves.

[0505] First, the user (factory manager) inputs information about factory operations into the system via a terminal. Operational information includes the operating status of each piece of equipment, production plans, work plans, staff allocation, budgets, etc. This information is sent to the server in real time and stored in a database.

[0506] Next, the server uses a generative AI engine to generate an optimal work plan based on the accumulated data. The generated work plan includes specific steps, deployment, and personnel planning. The proposed results are then sent back from the server to the device and notified to the user.

[0507] For example, if a factory manager is seeking suggestions for how to run a new production line more efficiently, he might enter the following information into the system:

[0508] Number of machines in operation: 10

[0509] Number of staff: 5

[0510] Target production volume: 500 units / day

[0511] Budget: 500,000 yen

[0512] Here are some examples of prompts based on the input:

[0513] Propose the best work plan based on the factory's operational information, including:

[0514] Number of machines in operation: 10

[0515] Number of staff: 5

[0516] Target production volume: 500 units / day

[0517] Budget: 500,000 yen

[0518] Use this information to suggest an efficient work plan.

[0519] The system uses these prompts to generate a work plan using a generative AI engine. The resulting proposals include specific suggestions such as "distributing staff between machine maintenance and production line supervision," "procuring necessary materials within budget," and "prioritizing work such as frames." The generated proposals are displayed on the robot's terminal screen, allowing the user to proceed with the work based on them.

[0520] After the event is completed, users can input their feedback information into their devices and send it to the server, which then stores the collected feedback in a database and knowledge base and uses it to improve future operational proposals, thereby continuously improving operational efficiency.

[0521] In this way, the present invention not only achieves more efficient factory operations, but also enables continuous improvement through real-time information sharing and feedback collection.

[0522] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0523] Step 1:

[0524] Users input information about factory operations into the terminal. Specific information includes the number of machines in operation, the number of staff, target production volume, and budget. This information is saved on the terminal in data format such as JSON. The input data is sent to the server in real time.

[0525] input:

[0526] Number of machines in operation

[0527] Number of staff

[0528] Target production volume

[0529] budget

[0530] output:

[0531] JSON data sent to the server

[0532] Step 2:

[0533] The terminal sends the operational information entered by the user to the server. The server stores the received data in a database. Specifically, an INSERT query is issued to store each piece of operational information in the appropriate table in the database.

[0534] input:

[0535] Operational information entered by the user

[0536] output:

[0537] Operational information stored in the database

[0538] Step 3:

[0539] The server generates a prompt for the AI ​​engine based on the operational information stored in the database. The prompt text includes the operational information entered by the user and is generated in a format that encourages the proposal of an optimal work plan. This prompt text is sent to the AI ​​engine as an API request.

[0540] input:

[0541] Operational information stored in a database

[0542] output:

[0543] Prompt sent to the generative AI engine

[0544] Step 4:

[0545] The server receives the proposed work plan from the generative AI engine. The generative AI engine generates an optimal work plan based on the prompt and returns the result to the server. The server then analyzes it and stores it in a database.

[0546] input:

[0547] Work plan proposals from a generative AI engine

[0548] output:

[0549] Work plans stored in the database

[0550] Step 5:

[0551] The server sends the generated work plan to the terminal, which displays the received work plan on its screen and notifies the user. The user confirms the proposed content and begins work.

[0552] input:

[0553] Generated Work Plan

[0554] output:

[0555] Work plan displayed on the device

[0556] Step 6:

[0557] After completing a task, the user inputs feedback information into the terminal. The feedback information includes successes, problems, and areas for improvement. This feedback information is then sent back to the server.

[0558] input:

[0559] Feedback Information

[0560] output:

[0561] Feedback information sent to the server

[0562] Step 7:

[0563] The server stores the received feedback information in the database and knowledge base. Specifically, it stores the feedback information in the appropriate table of the database using an INSERT query and updates the knowledge base.

[0564] input:

[0565] Feedback Information

[0566] output:

[0567] Feedback information stored in databases and knowledge bases

[0568] These steps will streamline factory operations, enable real-time information sharing, and enable continuous improvement.

[0569] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0570] The present invention relates to a system that efficiently supports the management of neighborhood associations by combining a generative AI engine and an emotion engine. This system has the function of collecting and accumulating management information about the neighborhood association and generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing an electronic circular and communication tools. Furthermore, in addition to functions that support specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection, the system also has a means for recognizing user emotions using an emotion engine and making management proposals and communication support based on those emotions.

[0571] Explanation of program processing

[0572] 1. Supporting users' business operations

[0573] Users input information about the operation of their neighborhood association into the system via their terminal. For example, when a user inputs planning information for a "summer festival," they input details of the event (type, budget, number of participants, date and time, etc.). This information is sent from the terminal to the server.

[0574] 2. Role of the terminal

[0575] The terminal receives information input by the user and sends it to the server. It also displays suggestions and information returned from the server to the user. Specifically, it sends data entered by the user to the server in real time and reflects the generated suggestions on the display screen. The terminal supports information sharing and communication between users via electronic circulars and communication tools.

[0576] 3. Server Roles

[0577] The server receives the operational information sent from the device and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. The generated proposals are sent from the server to the device and notified to the user. The server also receives feedback information and updates the database and knowledge base.

[0578] 4. The Role of the Emotional Engine

[0579] The emotion engine recognizes the user's emotional state and reflects it in operational proposals and communication support. Specifically, it analyzes emotions based on user input, dialogue history, and facial expression analysis, and generates operational proposals that are adapted to the user's emotional state, such as making suggestions that reduce stress when the user's stress level is high.

[0580] Specific examples

[0581] For example, when members of a neighborhood association plan a "summer festival," the process goes as follows: First, the user logs in to their device and enters information about the "summer festival." At this time, details such as the budget, number of participants, and date and time are also entered. The entered data is sent from the device to a server, which stores it in a database.

[0582] Next, the server uses a generative AI engine to generate optimal suggestions based on the collected data. For example, specific action plans such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and drinks within a budget" are proposed. At the same time, an emotion engine is also running to analyze the user's emotional state. For example, if the user is feeling stressed, suggestions may include elements such as "division of tasks to reduce the burden." The generated suggestions are sent from the server to the device and notified to the user.

[0583] The user reviews the proposal and decides whether to adopt it. If they do, they proceed with specific preparations based on the proposal. After the event is over, the user enters feedback on whether it was successful or not and what needs to be improved, and sends it to the server from their device.

[0584] Finally, the server saves the feedback information in a database and updates the knowledge base. The updated knowledge base will be reflected in the next proposal generation, enabling more accurate operational support. In addition, since the feedback information also includes the user's emotional state, the emotion engine also contributes to updating the knowledge base in cooperation with the server. This will enable customized proposals to be made to individual users in the future.

[0585] In this way, the system of the present invention, which combines a generative AI engine and an emotion engine, streamlines the management operations of neighborhood associations and, by taking into consideration the emotions of members, provides more effective and satisfying management support.

[0586] The processing flow will be explained below.

[0587] Step 1:

[0588] A user logs in to a terminal and accesses the dashboard. The terminal prompts the user to enter their ID and password, and sends the entered information to the server. The server authenticates the user, and if authentication is successful, returns the user's dashboard information to the terminal. The terminal displays the received dashboard information to the user.

[0589] Step 2:

[0590] The user selects "Summer Festival Plan" from the event planning menu and enters event information. The items to be entered include the event type (summer festival), budget (50,000 yen), number of participants (100 people), and date and time (August 1, 2023). The device sends this input data to the server.

[0591] Step 3:

[0592] The server accumulates the event information received from the terminal in a database. Specifically, it organizes information about summer festival planning and saves it in the database in an appropriate format.

[0593] Step 4:

[0594] The server runs a generative AI engine based on the information stored in the database to generate optimal management proposals. The generative AI engine references past data and existing knowledge bases to generate specific proposals such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[0595] Step 5:

[0596] The emotion engine analyzes the user's emotional state based on input data, the user's dialogue history, facial expression analysis, etc. For example, if the user is feeling stressed, it will output a result that the stress level is high. The emotion engine then sends this emotional data to the server.

[0597] Step 6:

[0598] The server reflects the data from the emotion engine in the generated operational proposals and adjusts them based on the user's emotional state. For example, the proposals may include elements such as "division of roles to reduce workload" and "relaxing activities." The adjusted proposals are then sent to the device and notified to the user.

[0599] Step 7:

[0600] The user checks the proposal displayed on the terminal. If the proposal is satisfactory, they click the "Accept" button to accept the proposal. The terminal sends this instruction to the server, which records the adoption of the proposal in the database. This starts the specific preparations for the event.

[0601] Step 8:

[0602] After the event, the user fills in a feedback form to indicate whether the event was successful, what needs to be improved, and how they felt during the event. The device then sends this feedback information to the server.

[0603] Step 9:

[0604] The server saves the feedback information in a database and updates the knowledge base. The updated knowledge base is reflected in the next proposal generation, enabling more accurate operational support. In addition, since the feedback information also includes the user's emotional state, the emotion engine also works together to contribute to updating the knowledge base.

[0605] As described above, the system of the present invention not only improves the efficiency of neighborhood association management operations, but also makes the management of neighborhood associations more effective and satisfying by making individual suggestions that take into consideration the feelings of members.

[0606] Example 2

[0607] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0608] In the management of local governments, it is necessary to efficiently carry out a series of processes, from planning to execution and feedback collection, and to facilitate information sharing and communication among members. It is also important to make optimal management proposals while taking into consideration the emotional state of each member. Conventional systems have had difficulty meeting these requirements and have had problems such as a heavy workload.

[0609] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0610] In this invention, the server includes means for collecting management information provided by the local government and storing it in a data storage device, means for generating optimal management proposals based on the management information stored in the data storage device, means for notifying members of the local government of the generated management proposals, means for recognizing the emotional state of users using an emotion analysis system and reflecting this in the management proposals, and means for users to input feedback and update the data storage device. This makes it possible to streamline the management operations of the local government, facilitate information sharing and communication between members, and make optimal proposals that take into consideration the emotions of members.

[0611] A "local government" is an organization that operates and manages a local community and is composed of local residents and their representatives.

[0612] A "generative AI system" is an artificial intelligence system that analyzes input data and automatically generates suggestions and information tailored to specific purposes.

[0613] A "data store" is a database or storage system for storing collected data or information.

[0614] An "emotion analysis system" is a system that recognizes and analyzes a user's emotional state based on input, dialogue history, facial expression analysis, etc.

[0615] "Users" are individuals or members involved in the operation of the local government, who operate the system to input information and receive suggestions.

[0616] "Feedback" refers to information such as evaluations, opinions, and improvements provided by users regarding proposals and activities carried out.

[0617] A "bulletin board" is a digital platform for publishing and sharing information over the Internet or a local network.

[0618] "Communication tools" are software and applications for sending and receiving messages and for real-time communication.

[0619] This invention relates to a system that efficiently supports the management of local governments by combining a generative AI system and an emotion analysis system. This system has the function of collecting and accumulating management information about local governments and generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among local government members by utilizing electronic bulletin boards and communication tools. Furthermore, in addition to functions that support specific local government management tasks such as event planning, financial management, and activity feedback collection, it also has a means for recognizing user emotions using an emotion analysis system and making management proposals and communication support based on those emotions.

[0620] System hardware and software configuration

[0621] This system consists of a server, a terminal, and a user. Details of each component are shown below.

[0622] server

[0623] The server includes a data storage device, a generative AI system, and an emotion analysis system. The data storage device functions as a database, storing the municipality's operational information and feedback information. The generative AI system analyzes the collected data and generates optimal operational proposals. The emotion analysis system analyzes the user's emotional state and reflects it in the operational proposals.

[0624] Terminal

[0625] The terminal is a device that allows users to access the system and input information. The information entered by the user is sent from the terminal to the server in real time. The terminal also displays suggestions and notifications generated as responses from the server. The terminal supports information sharing and communication between members through electronic bulletin boards and communication tools.

[0626] User

[0627] Users are individuals or members involved in the operation of the local government, who input information through their terminals and receive proposals from the server. Users log in to access the dashboard and input the necessary operational information (e.g., the name of the "Summer Festival," the budget, the number of participants, the date and time, etc.). They also have the role of sending feedback on the proposals.

[0628] Specific examples of behavior

[0629] For example, when members of a local government plan a "summer festival," the process is as follows:

[0630] 1. The user logs in to the device and enters details about the "Summer Festival," including the budget, number of participants, date and time, etc.

[0631] 2. The terminal sends the entered information to the server.

[0632] 3. The server stores the received data in a database and uses a generative AI system to generate optimal operation proposals, such as specific action plans such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[0633] 4. At the same time, the emotion analysis system analyzes the user's emotional state and, for example, if the user is feeling stressed, adds elements such as "division of roles to reduce the burden" to the suggestions.

[0634] 5. The generated proposal is sent from the server to the device and notified to the user.

[0635] 6. The user reviews the proposal and decides whether to adopt it. If necessary, the user can enter feedback and send it to the server from the device.

[0636] 7. The server stores the feedback information in a database and updates the knowledge base, which improves the accuracy of future suggestions. It also takes into account information about the user's emotional state, resulting in more personalized suggestions.

[0637] Prompt Sentence Examples

[0638] "Generate specific proposals for planning a summer festival. Please take into consideration conditions such as the budget, number of participants, date and time, etc. Also, if users are under a lot of stress, please include ideas for reducing their stress."

[0639] In this way, by combining a generative AI system with an emotion analysis system, it is possible to streamline local government management operations and, by taking into consideration the emotions of members, provide more effective and satisfying management support.

[0640] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0641] Step 1:

[0642] A user logs in to a terminal. User input: User ID and password. Output: User's dashboard. Operation: The user enters their user ID and password on the terminal's login screen. The terminal sends this information to the server, which performs authentication. If authentication is successful, the server returns the user's dashboard to the terminal.

[0643] Step 2:

[0644] The user enters operational information. User input: Details of the "Summer Festival" (name, budget, number of participants, date and time, etc.). Output: Press the send button to prepare for data transmission. Operation: The user enters detailed information about the "Summer Festival" project from the dashboard and clicks the "Send" button.

[0645] Step 3:

[0646] The terminal sends operational information from the user to the server. Input: Operational information (name, budget, number of participants, date and time, etc.). Output: Sends data to the server. Operation: The terminal sends the information entered by the user to the server in real time.

[0647] Step 4:

[0648] The server saves the received data in the database. Input: Operational information. Output: Saving to database completed. Operation: The server verifies the received data, confirms its validity, and saves it in the database.

[0649] Step 5:

[0650] The server retrieves management information from the database and generates management proposals using a generative AI system. Input: Management information stored in the database. Output: Optimal management proposals. Operation: The server's generative AI system analyzes the data and generates specific action plans such as "setting up a game corner and food stalls" and "recruiting local volunteers."

[0651] Step 6:

[0652] The emotion analysis system analyzes the user's emotional state and adjusts operational proposals. Input: User's past logs and dialogue history. Output: Proposals reflected in the emotional state. Operation: The emotion analysis system analyzes the user's emotional state based on past input data and dialogue history, and if stress is high, adds proposals such as "division of roles to reduce burden."

[0653] Step 7:

[0654] The server sends the adjusted management proposal to the terminal. Input: Adjusted management proposal. Output: Transmission to terminal completed. Operation: The server sends the final management proposal to the terminal, and the terminal notifies the user of this content.

[0655] Step 8:

[0656] The user confirms the proposal and sends feedback. User input: Proposal confirmation, feedback input. Output: Feedback data sent successfully. Operation: The user confirms the proposal, enters feedback if necessary, and presses the "Send" button. The device sends this feedback to the server.

[0657] Step 9:

[0658] The server saves the feedback information in the database and updates the knowledge base. Input: Feedback data. Output: Database and knowledge base updated. Operation: The server saves the feedback information in the database and updates the knowledge base. It also works with an emotion analysis system to add additional data based on the emotional state to the knowledge base.

[0659] (Application example 2)

[0660] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0661] Conventional management support systems for neighborhood associations and stores are limited to collecting management information and generating proposals, and have the problem of not being able to make management proposals that take into account the emotional state of members and staff. This increases stress and burden, and leads to problems such as reduced management efficiency and satisfaction.

[0662] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0663] In this invention, the server includes means for collecting management information provided by the management target using a generation AI engine and storing it in a database, means for generating optimal management proposals based on the management information stored in the database, means for notifying the members of the management target of the generated management proposals, and means for analyzing the emotional states of the members using an emotion engine and generating proposals based on the analyzed emotional states. This improves management efficiency and enables management proposals that take into account the emotional states of members and staff.

[0664] The "generative AI engine" is an artificial intelligence system that analyzes operational information and automatically generates optimal proposals.

[0665] The "Emotion Engine" is a system that analyzes the emotional state of members and staff and makes operational suggestions and communication support based on that analysis.

[0666] "Operation information" refers to data related to operations provided by the operation target (for example, sales information, shift information, event details, etc.).

[0667] A "database" is a digital storage system for storing and managing operational information and feedback information.

[0668] An "operational proposal" is a specific action plan for improving operational efficiency that is generated by the AI ​​engine based on operational information.

[0669] "Notification means" refers to a communication means for communicating the generated management proposal to members and staff.

[0670] An "electronic circular" is a tool for sharing information in digital format, with the purpose of facilitating the communication of information between members.

[0671] "Communication tools" are digital tools that support communication and information sharing between members and staff.

[0672] "Feedback information" is information about the success or failure of the management or event and areas for improvement, and is reflected in the generation of proposals from the next time onwards.

[0673] This invention relates to a system that combines a generative AI engine and an emotion engine to improve the efficiency of brick-and-mortar store operations and provide operational support that takes into account the emotions of staff and customers. This system includes the following components and processing procedures:

[0674] Supporting users' work

[0675] Users input information about the operation of their physical stores (e.g., sales information, shift information, event plans, etc.) into the system via their smartphones. For example, when entering planning information for a "Christmas sale," they also enter details of the event (date and time, sales target, budget, special product inventory information, etc.). This information is sent from the smartphone to the cloud server.

[0676] Device Role

[0677] The smartphone receives input information from users and sends it to the cloud server in real time. It also displays suggestions and information returned from the cloud server to users. Furthermore, it supports information sharing and communication among staff members via electronic circulars and communication tools.

[0678] Server Roles

[0679] The cloud server receives the operational information sent from the smartphone and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. For example, these proposals include "discounts on products in specific categories" and "implementing social media campaigns" for sales. The generated proposals are sent from the cloud server to the smartphone and notified to the user.

[0680] The role of the emotional engine

[0681] The emotion engine recognizes the emotional state of users and staff and reflects this in operational proposals and communication support. Specifically, it analyzes emotions based on user input, dialogue history, and facial expression analysis, and makes suggestions that are less stressful when stress levels are high, for example. This reduces staff stress and improves operational efficiency.

[0682] Hardware and software used

[0683] Smartphone (iOS or Android)

[0684] Cloud server (AWS or Google Cloud)

[0685] Database (MySQL or MongoDB)

[0686] Generative AI engine (OpenAI GPT-4)

[0687] Emotion engine (Affectiva or Solid Recognition technology)

[0688] Example

[0689] For example, when a brick-and-mortar store owner plans a "Christmas sale," the process goes as follows: First, the store owner logs into their smartphone and enters information about the "Christmas sale." This includes details such as the budget, sales target, and stock information for special items. The entered data is sent from the smartphone to a cloud server, which then stores it in a database.

[0690] Next, the cloud server uses a generative AI engine to generate optimal proposals based on the collected data. Specific action plans are proposed, such as "discounts on products in specific categories," "rewarding shopping points," and "implementing social media campaigns." At the same time, an emotion engine is also running to analyze the emotional state of staff. For example, if a staff member is feeling stressed, suggestions might include adjusting shifts to reduce the burden. The generated proposals are sent from the cloud server to smartphones, where they are notified to the owner and staff.

[0691] Example prompt sentence:

[0692] Generate optimal store management proposals based on the following data:

[0693] (Event name) Christmas Sale

[0694] (Date and time) December 24, 2023 - December 25, 2023

[0695] (Target sales) 1 million yen

[0696] (Budget) 200,000 yen

[0697] (Special product) Christmas limited edition cake, gift set

[0698] (Discount information) 10% off all products, 20% off some products

[0699] (Staff shift) 4 people / day

[0700] We trust the suggestions made by the generative AI engine, so please make suggestions that take into consideration increasing sales and reducing the burden on staff.

[0701] In this way, by combining a generative AI engine and an emotion engine, it is possible to improve operational efficiency and provide operational support that takes into account the emotional state of staff.

[0702] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0703] Step 1:

[0704] Users input store operation information (e.g., sales information, shift information, event plans, etc.) into the system via their smartphones. This input includes detailed information about the "Christmas sale" (date and time, sales target, budget, special product inventory information, etc.). The input information is sent from the smartphone to the cloud server.

[0705] Input: Sales information, shift information, event planning and other operational information

[0706] Data calculation and processing: Collects information provided by users and sends it to the cloud server

[0707] Output: Operational information stored on the cloud server

[0708] Step 2:

[0709] The cloud server receives the operational information sent from the smartphone and stores it in a database, allowing for centralized management of the operational information.

[0710] Input: Operational information sent from smartphone

[0711] Data calculation and processing: Received operational information is formatted and stored in a database

[0712] Output: Operational information stored in the database

[0713] Step 3:

[0714] The cloud server analyzes the operational information stored in the database and uses a generative AI engine to generate optimal operational proposals, such as discount plans to achieve sales targets, implementing social media campaigns, and managing inventory for special products.

[0715] Input: Operational information stored in the database

[0716] Data calculation and processing: Data analysis and proposal generation using a generative AI engine

[0717] Output: Optimal operational proposal

[0718] Step 4:

[0719] The emotion engine recognizes the emotional state of users and staff and reflects this in operational suggestions. For example, it generates suggestions to reduce stress based on user input, dialogue history, and facial expression analysis if stress levels are high.

[0720] Input: User emotion data, input history, facial expression information

[0721] Data Calculation and Processing: Emotional State Analysis and Adaptive Suggestion Generation by Emotion Engine

[0722] Output: Operational suggestions adapted to the user's emotional state

[0723] Step 5:

[0724] The cloud server sends the generated management proposal to the smartphone and notifies the user, who then reviews the proposal and decides whether to adopt it.

[0725] Input: Optimal operational suggestions, suggestions adapted to emotional state

[0726] Data calculation and processing: Transfer and notification of proposal contents

[0727] Output: Proposal content notified to smartphone

[0728] Step 6:

[0729] Users can input feedback on the implemented proposals into the system via their smartphones, including feedback on whether the proposal was successful or not, as well as areas for improvement. The input information is then sent back to the cloud server.

[0730] Input: Feedback information (success or failure, areas for improvement, etc.)

[0731] Data calculation and processing: Collect feedback information from users and send it to the cloud server

[0732] Output: Feedback information stored on the cloud server

[0733] Step 7:

[0734] The cloud server stores the feedback information in a database and updates the knowledge base, allowing the generative AI engine to use more accurate information to generate future management proposals.

[0735] Input: Feedback information, operational data

[0736] Data calculation and processing: Feedback information stored in a database and knowledge base updated

[0737] Output: Improved accuracy of proposals from next time onwards

[0738] This processing step efficiently executes a series of operational support processes, from collecting operational information to generating proposals, notifying proposals, collecting feedback, and updating the knowledge base.

[0739] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0740] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0741] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0742] [Third embodiment]

[0743] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0744] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0745] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0746] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0747] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0748] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0749] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0750] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0751] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0752] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0753] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0754] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0755] This invention relates to a system for efficiently supporting the management of neighborhood associations. This system uses a generative AI engine to collect and store management information about neighborhood associations, and then generates and notifies optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing electronic circulars and communication tools. Furthermore, it also has functions to support specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection.

[0756] Explanation of program processing

[0757] 1. Supporting users' business operations

[0758] Users can input information about the operation of their neighborhood association into the system through their terminals. For example, when a user inputs planning information for a "summer festival," they enter details of the event (type, budget, number of participants, date and time, etc.). This information is sent from the terminal to the server.

[0759] 2. Role of the terminal

[0760] The terminal receives information input by the user and sends it to the server. It also displays suggestions and information returned from the server to the user. Specifically, it sends data entered by the user to the server in real time and reflects the generated suggestions on the display screen. The terminal supports information sharing and communication between users via electronic circulars and communication tools.

[0761] 3. Server Roles

[0762] The server receives the operational information sent from the device and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. The generated proposals are sent from the server to the device and notified to the user. The server also receives feedback information and updates the database and knowledge base.

[0763] Specific examples

[0764] For example, when members of a neighborhood association plan a "summer festival," the process goes as follows: First, the user logs in to their device and enters information about the "summer festival." At this time, details such as the budget, number of participants, and date and time are also entered. The entered data is sent from the device to a server, which stores it in a database.

[0765] Next, the server uses a generative AI engine to generate optimal proposals based on the collected data. For example, specific action plans such as "Install a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within a budget" are proposed. These proposals are sent from the server to the device and notified to the user.

[0766] The user reviews the proposal and decides whether to adopt it. If they do, they proceed with specific preparations based on the proposal. After the event is over, the user enters feedback on whether it was successful or not and what needs to be improved, and sends it to the server from their device.

[0767] Finally, the server stores the feedback information in a database and updates the knowledge base to reflect it in future proposals.In this way, the system of the present invention is expected to efficiently support the management of neighborhood associations and contribute to the revitalization of local communities.

[0768] The processing flow will be explained below.

[0769] Step 1:

[0770] A user logs in to a terminal and accesses the dashboard. The terminal prompts the user to enter their ID and password, and sends the entered information to the server. The server performs authentication, and if authentication is successful, returns the user's dashboard information to the terminal. The terminal displays the received dashboard information to the user.

[0771] Step 2:

[0772] The user selects "Summer Festival Plan" from the event planning menu and enters event information. The items to be entered include the event type (summer festival), budget (50,000 yen), number of participants (100 people), and date and time (August 1, 2023). The device sends this input data to the server.

[0773] Step 3:

[0774] The server accumulates the event information received from the terminal in a database. Specifically, it organizes information about summer festival planning and saves it in the database in an appropriate format.

[0775] Step 4:

[0776] The server runs a generative AI engine based on the information stored in the database to generate optimal management proposals. The generative AI engine references past data and existing knowledge bases to generate specific proposals such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[0777] Step 5:

[0778] The server sends the generated management proposal to the terminal, which displays the proposal to the user. The user checks the proposal and makes corrections or approvals as necessary.

[0779] Step 6:

[0780] If the user accepts the proposal, he or she clicks the "Accept" button. The terminal sends the instruction to the server, which records in the database that the proposal has been accepted. This starts the specific preparations for the event.

[0781] Step 7:

[0782] After the event, the user enters whether the event was successful or not and what needs to be improved in the feedback form. The device then sends this feedback information to the server.

[0783] Step 8:

[0784] The server stores the feedback information in a database and updates the knowledge base. The updated knowledge base is reflected in future proposal generation, enabling more accurate operational support.

[0785] As described above, the system of the present invention streamlines the series of steps involved in running a neighborhood association and provides more effective support for running the association.

[0786] Example 1

[0787] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0788] In traditional neighborhood association management, the collection of management information, analysis, proposal generation, information sharing, communication, and feedback management are often all done separately, making efficient management difficult. In particular, since the accumulation of management information and the reflection of feedback are done manually, management tasks take time and effort, and appropriate proposals may not be provided promptly. Furthermore, many neighborhood associations lack tools for effective event planning, accounting management, and information sharing and communication between members, which reduces the efficiency of management.

[0789] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0790] In this invention, the server includes means for collecting input management information using a generation AI engine and storing it in a database, means for generating optimal management proposals based on the management information stored in the database, means for notifying users of the generated management proposals, means for users to check the proposal contents and input feedback, means for saving the feedback information in the database and knowledge base, and means for improving future proposals based on updates to the knowledge base. This enables efficient collection, analysis, and proposal generation of neighborhood association management information, facilitates information sharing and communication between users, quickly reflects feedback, and continuously improves proposals by updating the knowledge base.

[0791] A "neighborhood association" is an organization in which local residents independently manage and carry out local welfare and activities.

[0792] A "generative AI engine" is a system that uses artificial intelligence technology to analyze input data and generate optimal suggestions and answers.

[0793] "Operational information" is information necessary for running the neighborhood association, including details of events, accounting information, and feedback from participants.

[0794] A "database" is a data collection system that systematically stores collected data and allows it to be retrieved as needed.

[0795] "Management proposals" are proposals for specific actions and plans to improve and support neighborhood association management, generated by the AI ​​engine based on management information.

[0796] "User" refers to an individual or group who is a member of the neighborhood association and uses the system to input operational information, review proposals, provide feedback, etc.

[0797] "Notification means" refers to a function or process for notifying users of the generated management proposal.

[0798] "Feedback" is information that records evaluations and opinions on proposals and actions, and is used to help improve proposals and actions in the future.

[0799] A "knowledge base" is a collection of knowledge accumulated based on past experience and feedback, which is used to make future proposals and decisions.

[0800] An "electronic circular" is a tool for sharing information in a digital format, and is an electronic alternative to traditional paper circulars.

[0801] "Communication tools" are software and applications that support information exchange and communication between users.

[0802] This invention relates to a system for efficiently supporting the management of neighborhood associations. This system has the function of collecting and accumulating management information about neighborhood associations using a generative AI engine, and then generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing electronic circulars and communication tools. Furthermore, it also has the function of supporting specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection.

[0803] An embodiment of the system includes the following hardware and software.

[0804] Hardware and Software

[0805] 1. Server: Collects, stores, and generates data. Analyzes it using an AI engine, generates operational proposals, and processes feedback.

[0806] 2. Terminal: Provides functions for user information input, data transmission and reception with the server, display of management proposals and information, electronic circulars, and communication tools.

[0807] 3. Generative AI engine: Analyzes operational information and generates optimal operational proposals.

[0808] Specific examples of processing

[0809] Enter user information

[0810] The user logs in to the device and enters event information and other operational information. For example, for a "Summer Festival" event, the user enters the following details:

[0811] Type: Summer Festival

[0812] Budget: 500,000 yen

[0813] Number of participants: 300 people

[0814] Date and Time: August 5th, 5pm to 9pm

[0815] Data transmission and storage

[0816] The terminal transmits the input data in real time to the server, which then stores the received data in a database.

[0817] Generate operational proposals

[0818] The server inputs the data stored in the database into the generative AI engine, which generates optimal management proposals based on the input data. For example, it may generate proposals such as "Install a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within a budget."

[0819] Proposal Notification

[0820] The generated management proposal is sent from the server to the terminal and notified to the user, who then reviews the proposal and decides whether to adopt it.

[0821] Gathering feedback

[0822] After the event, the user inputs feedback on whether it was successful or not and what needs to be improved, and sends it from the terminal to the server, which then stores the feedback information in the database and knowledge base.

[0823] Prompt Sentence Examples

[0824] Here is an example of inputting the following prompt sentence into a generative AI model:

[0825] User input: "I'd like to plan a summer festival event for the neighborhood association. The budget is 500,000 yen, and I expect 300 participants. The event will take place on August 5th from 5:00 PM to 9:00 PM. Please provide your proposal."

[0826] Based on these prompts, the generative AI engine generates specific management proposals, which are then sent to the user via the server. In this way, the operation of the neighborhood association is efficiently supported, contributing to the revitalization of the local community.

[0827] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0828] Step 1: Enter your information

[0829] The user logs in to the terminal. The user enters the ID and password and clicks the login button. This provides the terminal with user authentication information as input.

[0830] The terminal sends authentication information to the server, which then performs authentication and returns the result to the terminal. If authentication is successful, the user can proceed to the event information input screen.

[0831] Step 2: Enter your event information

[0832] The user inputs event information. For example, for a "summer festival," the user enters the following detailed information into the form: type (summer festival), budget (500,000 yen), number of participants (300 people), and date and time (August 5th, 5:00 PM to 9:00 PM). When the user enters the information and clicks the submit button, this information is given to the terminal as input.

[0833] The terminal collects the input information, formats the data, and sends it to the server in real time. This transmitted data becomes the input to the server.

[0834] Step 3: Save your data

[0835] The server analyzes the data received from the device and stores it in a database. The server takes the received data as input and stores it in a database using SQL queries, which stores the event information.

[0836] Step 4: Generate an operational proposal

[0837] The server inputs data stored in the database into the generative AI engine. The server issues SQL queries to obtain the necessary data and provides this data to the generative AI engine. The generative AI engine analyzes the input data and generates optimal management proposals. For example, it outputs proposals such as "Set up a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within the budget."

[0838] Step 5: Proposal Notification

[0839] The generated management proposal is sent from the server to the terminal. The server sends the generated proposal to the terminal in the form of an HTTP response. The terminal receives this proposal, processes it as input, and reflects it on the display screen. The user can then confirm the proposal.

[0840] Step 6: Provide feedback

[0841] After the event, the user enters feedback on whether the event was successful or not, and on areas for improvement. The user fills in the information in the feedback form and clicks the submit button. This information is provided to the terminal as input.

[0842] Step 7: Submit your feedback

[0843] The terminal transmits feedback information to the server. The terminal collects input feedback information and transmits it to the server. This transmitted feedback information becomes input to the server.

[0844] Step 8: Save your feedback and update your knowledge base

[0845] The server receives the feedback information sent from the device and stores it in a database and knowledge base. The server takes the received feedback information as input and stores it in a database using SQL queries. It also updates the knowledge base, so that the feedback is reflected in future suggestions.

[0846] This structure efficiently supports the administrative work of the neighborhood association and revitalizes local activities.

[0847] (Application example 1)

[0848] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0849] In current factory operations, production planning and work efficiency are dependent on manual work and experience, resulting in problems such as inefficiencies and malfunctions. There is also a lack of real-time information sharing between equipment and robots, making it time-consuming to coordinate work. Furthermore, collecting feedback and incorporating it into the next plan is time-consuming, often delaying improvements. To solve these issues, a system is needed that collects and analyzes factory operation information and automatically generates and notifies optimal work plans.

[0850] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0851] In this invention, the server includes means for collecting operation information using a generation AI engine and storing it in a database, means for generating an optimal work plan based on the operation information stored in the database, and means for displaying the generated work plan on the robot terminal, thereby improving the efficiency of factory operations and enabling work optimization and real-time information sharing.

[0852] A "generative AI engine" is a computer system that uses machine learning and deep learning technologies to generate optimal suggestions and predictions from given data.

[0853] "Operational information" refers to data necessary for the operation of an organization such as a factory or local government, and includes information such as production plans, work schedules, staff allocation, budgets, and the operating status of each piece of equipment.

[0854] "Database" means an electronic data storage system for systematically storing and managing collected operational information.

[0855] An "optimal work plan" is a plan that proposes work schedules and allocations that maximize efficiency and effectiveness based on collected operational information.

[0856] A "robot terminal" is a terminal device attached to a robot or equipment in a factory, and is a device that has the function of displaying a generated work plan.

[0857] "Feedback information" is data on evaluations and areas for improvement collected after work or an event is carried out, and is important information that can be reflected in future plans.

[0858] A "knowledge base" is a knowledge database that stores past operational information and feedback information and uses it to generate future proposals and make decisions.

[0859] An "electronic circular board" is a system for sharing and circulating information electronically, rather than through the circulation of physical documents.

[0860] "Communication tools" are software and services that support information sharing and communication among members, including chat, video calls, email, etc.

[0861] This invention relates to a system for streamlining factory operations. Specifically, it is a system that uses a generative AI engine to collect and accumulate operational information, and then generates and notifies optimal work plans. Furthermore, it achieves continuous improvement by collecting feedback and reflecting it in the next plan.

[0862] The system's programs are primarily implemented in Python. The Python web framework Flask is used to build the API server that collects data and generates suggestions. The generative AI engine uses advanced natural language processing models such as OpenAI's GPT-3.

[0863] The hardware used will consist of terminals installed on the robots used in factories and a central management server. The terminals are expected to be mainly durable industrial tablets or interface devices built into the robots themselves.

[0864] First, the user (factory manager) inputs information about factory operations into the system via a terminal. Operational information includes the operating status of each piece of equipment, production plans, work plans, staff allocation, budgets, etc. This information is sent to the server in real time and stored in a database.

[0865] Next, the server uses a generative AI engine to generate an optimal work plan based on the accumulated data. The generated work plan includes specific steps, deployment, and personnel planning. The proposed results are then sent back from the server to the device and notified to the user.

[0866] For example, if a factory manager is seeking suggestions for how to run a new production line more efficiently, he might enter the following information into the system:

[0867] Number of machines in operation: 10

[0868] Number of staff: 5

[0869] Target production volume: 500 units / day

[0870] Budget: 500,000 yen

[0871] Here are some examples of prompts based on the input:

[0872] Propose the best work plan based on the factory's operational information, including:

[0873] Number of machines in operation: 10

[0874] Number of staff: 5

[0875] Target production volume: 500 units / day

[0876] Budget: 500,000 yen

[0877] Use this information to suggest an efficient work plan.

[0878] The system uses these prompts to generate a work plan using a generative AI engine. The resulting proposals include specific suggestions such as "distributing staff between machine maintenance and production line supervision," "procuring necessary materials within budget," and "prioritizing work such as frames." The generated proposals are displayed on the robot's terminal screen, allowing the user to proceed with the work based on them.

[0879] After the event is completed, users can input their feedback information into their devices and send it to the server, which then stores the collected feedback in a database and knowledge base and uses it to improve future operational proposals, thereby continuously improving operational efficiency.

[0880] In this way, the present invention not only achieves more efficient factory operations, but also enables continuous improvement through real-time information sharing and feedback collection.

[0881] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0882] Step 1:

[0883] Users input information about factory operations into the terminal. Specific information includes the number of machines in operation, the number of staff, target production volume, and budget. This information is saved on the terminal in data format such as JSON. The input data is sent to the server in real time.

[0884] input:

[0885] Number of machines in operation

[0886] Number of staff

[0887] Target production volume

[0888] budget

[0889] output:

[0890] JSON data sent to the server

[0891] Step 2:

[0892] The terminal sends the operational information entered by the user to the server. The server stores the received data in a database. Specifically, an INSERT query is issued to store each piece of operational information in the appropriate table in the database.

[0893] input:

[0894] Operational information entered by the user

[0895] output:

[0896] Operational information stored in the database

[0897] Step 3:

[0898] The server generates a prompt for the AI ​​engine based on the operational information stored in the database. The prompt text includes the operational information entered by the user and is generated in a format that encourages the proposal of an optimal work plan. This prompt text is sent to the AI ​​engine as an API request.

[0899] input:

[0900] Operational information stored in a database

[0901] output:

[0902] Prompt sent to the generative AI engine

[0903] Step 4:

[0904] The server receives the proposed work plan from the generative AI engine. The generative AI engine generates an optimal work plan based on the prompt and returns the result to the server. The server then analyzes it and stores it in a database.

[0905] input:

[0906] Work plan proposals from a generative AI engine

[0907] output:

[0908] Work plans stored in the database

[0909] Step 5:

[0910] The server sends the generated work plan to the terminal, which displays the received work plan on its screen and notifies the user. The user confirms the proposed content and begins work.

[0911] input:

[0912] Generated Work Plan

[0913] output:

[0914] Work plan displayed on the device

[0915] Step 6:

[0916] After completing a task, the user inputs feedback information into the terminal. The feedback information includes successes, problems, and areas for improvement. This feedback information is then sent back to the server.

[0917] input:

[0918] Feedback Information

[0919] output:

[0920] Feedback information sent to the server

[0921] Step 7:

[0922] The server stores the received feedback information in the database and knowledge base. Specifically, it stores the feedback information in the appropriate table of the database using an INSERT query and updates the knowledge base.

[0923] input:

[0924] Feedback Information

[0925] output:

[0926] Feedback information stored in databases and knowledge bases

[0927] These steps will streamline factory operations, enable real-time information sharing, and enable continuous improvement.

[0928] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0929] The present invention relates to a system that efficiently supports the management of neighborhood associations by combining a generative AI engine and an emotion engine. This system has the function of collecting and accumulating management information about the neighborhood association and generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing an electronic circular and communication tools. Furthermore, in addition to functions that support specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection, the system also has a means for recognizing user emotions using an emotion engine and making management proposals and communication support based on those emotions.

[0930] Explanation of program processing

[0931] 1. Supporting users' business operations

[0932] Users input information about the operation of their neighborhood association into the system via their terminal. For example, when a user inputs planning information for a "summer festival," they input details of the event (type, budget, number of participants, date and time, etc.). This information is sent from the terminal to the server.

[0933] 2. Role of the terminal

[0934] The terminal receives information input by the user and sends it to the server. It also displays suggestions and information returned from the server to the user. Specifically, it sends data entered by the user to the server in real time and reflects the generated suggestions on the display screen. The terminal supports information sharing and communication between users via electronic circulars and communication tools.

[0935] 3. Server Roles

[0936] The server receives the operational information sent from the device and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. The generated proposals are sent from the server to the device and notified to the user. The server also receives feedback information and updates the database and knowledge base.

[0937] 4. The Role of the Emotional Engine

[0938] The emotion engine recognizes the user's emotional state and reflects it in operational proposals and communication support. Specifically, it analyzes emotions based on user input, dialogue history, and facial expression analysis, and generates operational proposals that are adapted to the user's emotional state, such as making suggestions that reduce stress when the user's stress level is high.

[0939] Specific examples

[0940] For example, when members of a neighborhood association plan a "summer festival," the process goes as follows: First, the user logs in to their device and enters information about the "summer festival." At this time, details such as the budget, number of participants, and date and time are also entered. The entered data is sent from the device to a server, which stores it in a database.

[0941] Next, the server uses a generative AI engine to generate optimal suggestions based on the collected data. For example, specific action plans such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and drinks within a budget" are proposed. At the same time, an emotion engine is also running to analyze the user's emotional state. For example, if the user is feeling stressed, suggestions may include elements such as "division of tasks to reduce the burden." The generated suggestions are sent from the server to the device and notified to the user.

[0942] The user reviews the proposal and decides whether to adopt it. If they do, they proceed with specific preparations based on the proposal. After the event is over, the user enters feedback on whether it was successful or not and what needs to be improved, and sends it to the server from their device.

[0943] Finally, the server saves the feedback information in a database and updates the knowledge base. The updated knowledge base will be reflected in the next proposal generation, enabling more accurate operational support. In addition, since the feedback information also includes the user's emotional state, the emotion engine also contributes to updating the knowledge base in cooperation with the server. This will enable customized proposals to be made to individual users in the future.

[0944] In this way, the system of the present invention, which combines a generative AI engine and an emotion engine, streamlines the management operations of neighborhood associations and, by taking into consideration the emotions of members, provides more effective and satisfying management support.

[0945] The processing flow will be explained below.

[0946] Step 1:

[0947] A user logs in to a terminal and accesses the dashboard. The terminal prompts the user to enter their ID and password, and sends the entered information to the server. The server authenticates the user, and if authentication is successful, returns the user's dashboard information to the terminal. The terminal displays the received dashboard information to the user.

[0948] Step 2:

[0949] The user selects "Summer Festival Plan" from the event planning menu and enters event information. The items to be entered include the event type (summer festival), budget (50,000 yen), number of participants (100 people), and date and time (August 1, 2023). The device sends this input data to the server.

[0950] Step 3:

[0951] The server accumulates the event information received from the terminal in a database. Specifically, it organizes information about summer festival planning and saves it in the database in an appropriate format.

[0952] Step 4:

[0953] The server runs a generative AI engine based on the information stored in the database to generate optimal management proposals. The generative AI engine references past data and existing knowledge bases to generate specific proposals such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[0954] Step 5:

[0955] The emotion engine analyzes the user's emotional state based on input data, the user's dialogue history, facial expression analysis, etc. For example, if the user is feeling stressed, it will output a result that the stress level is high. The emotion engine then sends this emotional data to the server.

[0956] Step 6:

[0957] The server reflects the data from the emotion engine in the generated operational proposals and adjusts them based on the user's emotional state. For example, the proposals may include elements such as "division of roles to reduce workload" and "relaxing activities." The adjusted proposals are then sent to the device and notified to the user.

[0958] Step 7:

[0959] The user checks the proposal displayed on the terminal. If the proposal is satisfactory, they click the "Accept" button to accept the proposal. The terminal sends this instruction to the server, which records the adoption of the proposal in the database. This starts the specific preparations for the event.

[0960] Step 8:

[0961] After the event, the user fills in a feedback form to indicate whether the event was successful, what needs to be improved, and how they felt during the event. The device then sends this feedback information to the server.

[0962] Step 9:

[0963] The server saves the feedback information in a database and updates the knowledge base. The updated knowledge base is reflected in the next proposal generation, enabling more accurate operational support. In addition, since the feedback information also includes the user's emotional state, the emotion engine also works together to contribute to updating the knowledge base.

[0964] As described above, the system of the present invention not only improves the efficiency of neighborhood association management operations, but also makes the management of neighborhood associations more effective and satisfying by making individual suggestions that take into consideration the feelings of members.

[0965] Example 2

[0966] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0967] In the management of local governments, it is necessary to efficiently carry out a series of processes, from planning to execution and feedback collection, and to facilitate information sharing and communication among members. It is also important to make optimal management proposals while taking into consideration the emotional state of each member. Conventional systems have had difficulty meeting these requirements and have had problems such as a heavy workload.

[0968] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0969] In this invention, the server includes means for collecting management information provided by the local government and storing it in a data storage device, means for generating optimal management proposals based on the management information stored in the data storage device, means for notifying members of the local government of the generated management proposals, means for recognizing the emotional state of users using an emotion analysis system and reflecting this in the management proposals, and means for users to input feedback and update the data storage device. This makes it possible to streamline the management operations of the local government, facilitate information sharing and communication between members, and make optimal proposals that take into consideration the emotions of members.

[0970] A "local government" is an organization that operates and manages a local community and is composed of local residents and their representatives.

[0971] A "generative AI system" is an artificial intelligence system that analyzes input data and automatically generates suggestions and information tailored to specific purposes.

[0972] A "data store" is a database or storage system for storing collected data or information.

[0973] An "emotion analysis system" is a system that recognizes and analyzes a user's emotional state based on input, dialogue history, facial expression analysis, etc.

[0974] "Users" are individuals or members involved in the operation of the local government, who operate the system to input information and receive suggestions.

[0975] "Feedback" refers to information such as evaluations, opinions, and improvements provided by users regarding proposals and activities carried out.

[0976] A "bulletin board" is a digital platform for publishing and sharing information over the Internet or a local network.

[0977] "Communication tools" are software and applications for sending and receiving messages and for real-time communication.

[0978] This invention relates to a system that efficiently supports the management of local governments by combining a generative AI system and an emotion analysis system. This system has the function of collecting and accumulating management information about local governments and generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among local government members by utilizing electronic bulletin boards and communication tools. Furthermore, in addition to functions that support specific local government management tasks such as event planning, financial management, and activity feedback collection, it also has a means for recognizing user emotions using an emotion analysis system and making management proposals and communication support based on those emotions.

[0979] System hardware and software configuration

[0980] This system consists of a server, a terminal, and a user. Details of each component are shown below.

[0981] server

[0982] The server includes a data storage device, a generative AI system, and an emotion analysis system. The data storage device functions as a database, storing the municipality's operational information and feedback information. The generative AI system analyzes the collected data and generates optimal operational proposals. The emotion analysis system analyzes the user's emotional state and reflects it in the operational proposals.

[0983] Terminal

[0984] The terminal is a device that allows users to access the system and input information. The information entered by the user is sent from the terminal to the server in real time. The terminal also displays suggestions and notifications generated as responses from the server. The terminal supports information sharing and communication between members through electronic bulletin boards and communication tools.

[0985] User

[0986] Users are individuals or members involved in the operation of the local government, who input information through their terminals and receive proposals from the server. Users log in to access the dashboard and input the necessary operational information (e.g., the name of the "Summer Festival," the budget, the number of participants, the date and time, etc.). They also have the role of sending feedback on the proposals.

[0987] Specific examples of behavior

[0988] For example, when members of a local government plan a "summer festival," the process is as follows:

[0989] 1. The user logs in to the device and enters details about the "Summer Festival," including the budget, number of participants, date and time, etc.

[0990] 2. The terminal sends the entered information to the server.

[0991] 3. The server stores the received data in a database and uses a generative AI system to generate optimal operation proposals, such as specific action plans such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[0992] 4. At the same time, the emotion analysis system analyzes the user's emotional state and, for example, if the user is feeling stressed, adds elements such as "division of roles to reduce the burden" to the suggestions.

[0993] 5. The generated proposal is sent from the server to the device and notified to the user.

[0994] 6. The user reviews the proposal and decides whether to adopt it. If necessary, the user can enter feedback and send it to the server from the device.

[0995] 7. The server stores the feedback information in a database and updates the knowledge base, which improves the accuracy of future suggestions. It also takes into account information about the user's emotional state, resulting in more personalized suggestions.

[0996] Prompt Sentence Examples

[0997] "Generate specific proposals for planning a summer festival. Please take into consideration conditions such as the budget, number of participants, date and time, etc. Also, if users are under a lot of stress, please include ideas for reducing their stress."

[0998] In this way, by combining a generative AI system with an emotion analysis system, it is possible to streamline local government management operations and, by taking into consideration the emotions of members, provide more effective and satisfying management support.

[0999] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1000] Step 1:

[1001] A user logs in to a terminal. User input: User ID and password. Output: User's dashboard. Operation: The user enters their user ID and password on the terminal's login screen. The terminal sends this information to the server, which performs authentication. If authentication is successful, the server returns the user's dashboard to the terminal.

[1002] Step 2:

[1003] The user enters operational information. User input: Details of the "Summer Festival" (name, budget, number of participants, date and time, etc.). Output: Press the send button to prepare for data transmission. Operation: The user enters detailed information about the "Summer Festival" project from the dashboard and clicks the "Send" button.

[1004] Step 3:

[1005] The terminal sends operational information from the user to the server. Input: Operational information (name, budget, number of participants, date and time, etc.). Output: Sends data to the server. Operation: The terminal sends the information entered by the user to the server in real time.

[1006] Step 4:

[1007] The server saves the received data in the database. Input: Operational information. Output: Saving to database completed. Operation: The server verifies the received data, confirms its validity, and saves it in the database.

[1008] Step 5:

[1009] The server retrieves management information from the database and generates management proposals using a generative AI system. Input: Management information stored in the database. Output: Optimal management proposals. Operation: The server's generative AI system analyzes the data and generates specific action plans such as "setting up a game corner and food stalls" and "recruiting local volunteers."

[1010] Step 6:

[1011] The emotion analysis system analyzes the user's emotional state and adjusts operational proposals. Input: User's past logs and dialogue history. Output: Proposals reflected in the emotional state. Operation: The emotion analysis system analyzes the user's emotional state based on past input data and dialogue history, and if stress is high, adds proposals such as "division of roles to reduce burden."

[1012] Step 7:

[1013] The server sends the adjusted management proposal to the terminal. Input: Adjusted management proposal. Output: Transmission to terminal completed. Operation: The server sends the final management proposal to the terminal, and the terminal notifies the user of this content.

[1014] Step 8:

[1015] The user confirms the proposal and sends feedback. User input: Proposal confirmation, feedback input. Output: Feedback data sent successfully. Operation: The user confirms the proposal, enters feedback if necessary, and presses the "Send" button. The device sends this feedback to the server.

[1016] Step 9:

[1017] The server saves the feedback information in the database and updates the knowledge base. Input: Feedback data. Output: Database and knowledge base updated. Operation: The server saves the feedback information in the database and updates the knowledge base. It also works with an emotion analysis system to add additional data based on the emotional state to the knowledge base.

[1018] (Application example 2)

[1019] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1020] Conventional management support systems for neighborhood associations and stores are limited to collecting management information and generating proposals, and have the problem of not being able to make management proposals that take into account the emotional state of members and staff. This increases stress and burden, and leads to problems such as reduced management efficiency and satisfaction.

[1021] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1022] In this invention, the server includes means for collecting management information provided by the management target using a generation AI engine and storing it in a database, means for generating optimal management proposals based on the management information stored in the database, means for notifying the members of the management target of the generated management proposals, and means for analyzing the emotional states of the members using an emotion engine and generating proposals based on the analyzed emotional states. This improves management efficiency and enables management proposals that take into account the emotional states of members and staff.

[1023] The "generative AI engine" is an artificial intelligence system that analyzes operational information and automatically generates optimal proposals.

[1024] The "Emotion Engine" is a system that analyzes the emotional state of members and staff and makes operational suggestions and communication support based on that analysis.

[1025] "Operation information" refers to data related to operations provided by the operation target (for example, sales information, shift information, event details, etc.).

[1026] A "database" is a digital storage system for storing and managing operational information and feedback information.

[1027] An "operational proposal" is a specific action plan for improving operational efficiency that is generated by the AI ​​engine based on operational information.

[1028] "Notification means" refers to a communication means for communicating the generated management proposal to members and staff.

[1029] An "electronic circular" is a tool for sharing information in digital format, with the purpose of facilitating the communication of information between members.

[1030] "Communication tools" are digital tools that support communication and information sharing between members and staff.

[1031] "Feedback information" is information about the success or failure of the management or event and areas for improvement, and is reflected in the generation of proposals from the next time onwards.

[1032] This invention relates to a system that combines a generative AI engine and an emotion engine to improve the efficiency of brick-and-mortar store operations and provide operational support that takes into account the emotions of staff and customers. This system includes the following components and processing procedures:

[1033] Supporting users' work

[1034] Users input information about the operation of their physical stores (e.g., sales information, shift information, event plans, etc.) into the system via their smartphones. For example, when entering planning information for a "Christmas sale," they also enter details of the event (date and time, sales target, budget, special product inventory information, etc.). This information is sent from the smartphone to the cloud server.

[1035] Device Role

[1036] The smartphone receives input information from users and sends it to the cloud server in real time. It also displays suggestions and information returned from the cloud server to users. Furthermore, it supports information sharing and communication among staff members via electronic circulars and communication tools.

[1037] Server Roles

[1038] The cloud server receives the operational information sent from the smartphone and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. For example, these proposals include "discounts on products in specific categories" and "implementing social media campaigns" for sales. The generated proposals are sent from the cloud server to the smartphone and notified to the user.

[1039] The role of the emotional engine

[1040] The emotion engine recognizes the emotional state of users and staff and reflects this in operational proposals and communication support. Specifically, it analyzes emotions based on user input, dialogue history, and facial expression analysis, and makes suggestions that are less stressful when stress levels are high, for example. This reduces staff stress and improves operational efficiency.

[1041] Hardware and software used

[1042] Smartphone (iOS or Android)

[1043] Cloud server (AWS or Google Cloud)

[1044] Database (MySQL or MongoDB)

[1045] Generative AI engine (OpenAI GPT-4)

[1046] Emotion engine (Affectiva or Solid Recognition technology)

[1047] Example

[1048] For example, when a brick-and-mortar store owner plans a "Christmas sale," the process goes as follows: First, the store owner logs into their smartphone and enters information about the "Christmas sale." This includes details such as the budget, sales target, and stock information for special items. The entered data is sent from the smartphone to a cloud server, which then stores it in a database.

[1049] Next, the cloud server uses a generative AI engine to generate optimal proposals based on the collected data. Specific action plans are proposed, such as "discounts on products in specific categories," "rewarding shopping points," and "implementing social media campaigns." At the same time, an emotion engine is also running to analyze the emotional state of staff. For example, if a staff member is feeling stressed, suggestions might include adjusting shifts to reduce the burden. The generated proposals are sent from the cloud server to smartphones, where they are notified to the owner and staff.

[1050] Example prompt sentence:

[1051] Generate optimal store management proposals based on the following data:

[1052] (Event name) Christmas Sale

[1053] (Date and time) December 24, 2023 - December 25, 2023

[1054] (Target sales) 1 million yen

[1055] (Budget) 200,000 yen

[1056] (Special product) Christmas limited edition cake, gift set

[1057] (Discount information) 10% off all products, 20% off some products

[1058] (Staff shift) 4 people / day

[1059] We trust the suggestions made by the generative AI engine, so please make suggestions that take into consideration increasing sales and reducing the burden on staff.

[1060] In this way, by combining a generative AI engine and an emotion engine, it is possible to improve operational efficiency and provide operational support that takes into account the emotional state of staff.

[1061] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1062] Step 1:

[1063] Users input store operation information (e.g., sales information, shift information, event plans, etc.) into the system via their smartphones. This input includes detailed information about the "Christmas sale" (date and time, sales target, budget, special product inventory information, etc.). The input information is sent from the smartphone to the cloud server.

[1064] Input: Sales information, shift information, event planning and other operational information

[1065] Data calculation and processing: Collects information provided by users and sends it to the cloud server

[1066] Output: Operational information stored on the cloud server

[1067] Step 2:

[1068] The cloud server receives the operational information sent from the smartphone and stores it in a database, allowing for centralized management of the operational information.

[1069] Input: Operational information sent from smartphone

[1070] Data calculation and processing: Received operational information is formatted and stored in a database

[1071] Output: Operational information stored in the database

[1072] Step 3:

[1073] The cloud server analyzes the operational information stored in the database and uses a generative AI engine to generate optimal operational proposals, such as discount plans to achieve sales targets, implementing social media campaigns, and managing inventory for special products.

[1074] Input: Operational information stored in the database

[1075] Data calculation and processing: Data analysis and proposal generation using a generative AI engine

[1076] Output: Optimal operational proposal

[1077] Step 4:

[1078] The emotion engine recognizes the emotional state of users and staff and reflects this in operational suggestions. For example, it generates suggestions to reduce stress based on user input, dialogue history, and facial expression analysis if stress levels are high.

[1079] Input: User emotion data, input history, facial expression information

[1080] Data Calculation and Processing: Emotional State Analysis and Adaptive Suggestion Generation by Emotion Engine

[1081] Output: Operational suggestions adapted to the user's emotional state

[1082] Step 5:

[1083] The cloud server sends the generated management proposal to the smartphone and notifies the user, who then reviews the proposal and decides whether to adopt it.

[1084] Input: Optimal operational suggestions, suggestions adapted to emotional state

[1085] Data calculation and processing: Transfer and notification of proposal contents

[1086] Output: Proposal content notified to smartphone

[1087] Step 6:

[1088] Users can input feedback on the implemented proposals into the system via their smartphones, including feedback on whether the proposal was successful or not, as well as areas for improvement. The input information is then sent back to the cloud server.

[1089] Input: Feedback information (success or failure, areas for improvement, etc.)

[1090] Data calculation and processing: Collect feedback information from users and send it to the cloud server

[1091] Output: Feedback information stored on the cloud server

[1092] Step 7:

[1093] The cloud server stores the feedback information in a database and updates the knowledge base, allowing the generative AI engine to use more accurate information to generate future management proposals.

[1094] Input: Feedback information, operational data

[1095] Data calculation and processing: Feedback information stored in a database and knowledge base updated

[1096] Output: Improved accuracy of proposals from next time onwards

[1097] This processing step efficiently executes a series of operational support processes, from collecting operational information to generating proposals, notifying proposals, collecting feedback, and updating the knowledge base.

[1098] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1099] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1100] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1101] [Fourth embodiment]

[1102] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1103] 7, a 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.

[1104] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1105] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1106] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1107] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1108] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1109] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1110] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1111] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1112] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1113] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1114] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1115] This invention relates to a system for efficiently supporting the management of neighborhood associations. This system uses a generative AI engine to collect and store management information about neighborhood associations, and then generates and notifies optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing electronic circulars and communication tools. Furthermore, it also has functions to support specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection.

[1116] Explanation of program processing

[1117] 1. Supporting users' business operations

[1118] Users can input information about the operation of their neighborhood association into the system through their terminals. For example, when a user inputs planning information for a "summer festival," they enter details of the event (type, budget, number of participants, date and time, etc.). This information is sent from the terminal to the server.

[1119] 2. Role of the terminal

[1120] The terminal receives information input by the user and sends it to the server. It also displays suggestions and information returned from the server to the user. Specifically, it sends data entered by the user to the server in real time and reflects the generated suggestions on the display screen. The terminal supports information sharing and communication between users via electronic circulars and communication tools.

[1121] 3. Server Roles

[1122] The server receives the operational information sent from the device and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. The generated proposals are sent from the server to the device and notified to the user. The server also receives feedback information and updates the database and knowledge base.

[1123] Specific examples

[1124] For example, when members of a neighborhood association plan a "summer festival," the process goes as follows: First, the user logs in to their device and enters information about the "summer festival." At this time, details such as the budget, number of participants, and date and time are also entered. The entered data is sent from the device to a server, which stores it in a database.

[1125] Next, the server uses a generative AI engine to generate optimal proposals based on the collected data. For example, specific action plans such as "Install a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within a budget" are proposed. These proposals are sent from the server to the device and notified to the user.

[1126] The user reviews the proposal and decides whether to adopt it. If they do, they proceed with specific preparations based on the proposal. After the event is over, the user enters feedback on whether it was successful or not and what needs to be improved, and sends it to the server from their device.

[1127] Finally, the server stores the feedback information in a database and updates the knowledge base to reflect it in future proposals.In this way, the system of the present invention is expected to efficiently support the management of neighborhood associations and contribute to the revitalization of local communities.

[1128] The processing flow will be explained below.

[1129] Step 1:

[1130] A user logs in to a terminal and accesses the dashboard. The terminal prompts the user to enter their ID and password, and sends the entered information to the server. The server performs authentication, and if authentication is successful, returns the user's dashboard information to the terminal. The terminal displays the received dashboard information to the user.

[1131] Step 2:

[1132] The user selects "Summer Festival Plan" from the event planning menu and enters event information. The items to be entered include the event type (summer festival), budget (50,000 yen), number of participants (100 people), and date and time (August 1, 2023). The device sends this input data to the server.

[1133] Step 3:

[1134] The server accumulates the event information received from the terminal in a database. Specifically, it organizes information about summer festival planning and saves it in the database in an appropriate format.

[1135] Step 4:

[1136] The server runs a generative AI engine based on the information stored in the database to generate optimal management proposals. The generative AI engine references past data and existing knowledge bases to generate specific proposals such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[1137] Step 5:

[1138] The server sends the generated management proposal to the terminal, which displays the proposal to the user. The user checks the proposal and makes corrections or approvals as necessary.

[1139] Step 6:

[1140] If the user accepts the proposal, he or she clicks the "Accept" button. The terminal sends the instruction to the server, which records in the database that the proposal has been accepted. This starts the specific preparations for the event.

[1141] Step 7:

[1142] After the event, the user enters whether the event was successful or not and what needs to be improved in the feedback form. The device then sends this feedback information to the server.

[1143] Step 8:

[1144] The server stores the feedback information in a database and updates the knowledge base. The updated knowledge base is reflected in future proposal generation, enabling more accurate operational support.

[1145] As described above, the system of the present invention streamlines the series of steps involved in running a neighborhood association and provides more effective support for running the association.

[1146] Example 1

[1147] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1148] In traditional neighborhood association management, the collection of management information, analysis, proposal generation, information sharing, communication, and feedback management are often all done separately, making efficient management difficult. In particular, since the accumulation of management information and the reflection of feedback are done manually, management tasks take time and effort, and appropriate proposals may not be provided promptly. Furthermore, many neighborhood associations lack tools for effective event planning, accounting management, and information sharing and communication between members, which reduces the efficiency of management.

[1149] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1150] In this invention, the server includes means for collecting input management information using a generation AI engine and storing it in a database, means for generating optimal management proposals based on the management information stored in the database, means for notifying users of the generated management proposals, means for users to check the proposal contents and input feedback, means for saving the feedback information in the database and knowledge base, and means for improving future proposals based on updates to the knowledge base. This enables efficient collection, analysis, and proposal generation of neighborhood association management information, facilitates information sharing and communication between users, quickly reflects feedback, and continuously improves proposals by updating the knowledge base.

[1151] A "neighborhood association" is an organization in which local residents independently manage and carry out local welfare and activities.

[1152] A "generative AI engine" is a system that uses artificial intelligence technology to analyze input data and generate optimal suggestions and answers.

[1153] "Operational information" is information necessary for running the neighborhood association, including details of events, accounting information, and feedback from participants.

[1154] A "database" is a data collection system that systematically stores collected data and allows it to be retrieved as needed.

[1155] "Management proposals" are proposals for specific actions and plans to improve and support neighborhood association management, generated by the AI ​​engine based on management information.

[1156] "User" refers to an individual or group who is a member of the neighborhood association and uses the system to input operational information, review proposals, provide feedback, etc.

[1157] "Notification means" refers to a function or process for notifying users of the generated management proposal.

[1158] "Feedback" is information that records evaluations and opinions on proposals and actions, and is used to help improve proposals and actions in the future.

[1159] A "knowledge base" is a collection of knowledge accumulated based on past experience and feedback, which is used to make future proposals and decisions.

[1160] An "electronic circular" is a tool for sharing information in a digital format, and is an electronic alternative to traditional paper circulars.

[1161] "Communication tools" are software and applications that support information exchange and communication between users.

[1162] This invention relates to a system for efficiently supporting the management of neighborhood associations. This system has the function of collecting and accumulating management information about neighborhood associations using a generative AI engine, and then generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing electronic circulars and communication tools. Furthermore, it also has the function of supporting specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection.

[1163] An embodiment of the system includes the following hardware and software.

[1164] Hardware and Software

[1165] 1. Server: Collects, stores, and generates data. Analyzes it using an AI engine, generates operational proposals, and processes feedback.

[1166] 2. Terminal: Provides functions for user information input, data transmission and reception with the server, display of management proposals and information, electronic circulars, and communication tools.

[1167] 3. Generative AI engine: Analyzes operational information and generates optimal operational proposals.

[1168] Specific examples of processing

[1169] Enter user information

[1170] The user logs in to the device and enters event information and other operational information. For example, for a "Summer Festival" event, the user enters the following details:

[1171] Type: Summer Festival

[1172] Budget: 500,000 yen

[1173] Number of participants: 300 people

[1174] Date and Time: August 5th, 5pm to 9pm

[1175] Data transmission and storage

[1176] The terminal transmits the input data in real time to the server, which then stores the received data in a database.

[1177] Generate operational proposals

[1178] The server inputs the data stored in the database into the generative AI engine, which generates optimal management proposals based on the input data. For example, it may generate proposals such as "Install a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within a budget."

[1179] Proposal Notification

[1180] The generated management proposal is sent from the server to the terminal and notified to the user, who then reviews the proposal and decides whether to adopt it.

[1181] Gathering feedback

[1182] After the event, the user inputs feedback on whether it was successful or not and what needs to be improved, and sends it from the terminal to the server, which then stores the feedback information in the database and knowledge base.

[1183] Prompt Sentence Examples

[1184] Here is an example of inputting the following prompt sentence into a generative AI model:

[1185] User input: "I'd like to plan a summer festival event for the neighborhood association. The budget is 500,000 yen, and I expect 300 participants. The event will take place on August 5th from 5:00 PM to 9:00 PM. Please provide your proposal."

[1186] Based on these prompts, the generative AI engine generates specific management proposals, which are then sent to the user via the server. In this way, the operation of the neighborhood association is efficiently supported, contributing to the revitalization of the local community.

[1187] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1188] Step 1: Enter your information

[1189] The user logs in to the terminal. The user enters the ID and password and clicks the login button. This provides the terminal with user authentication information as input.

[1190] The terminal sends authentication information to the server, which then performs authentication and returns the result to the terminal. If authentication is successful, the user can proceed to the event information input screen.

[1191] Step 2: Enter your event information

[1192] The user inputs event information. For example, for a "summer festival," the user enters the following detailed information into the form: type (summer festival), budget (500,000 yen), number of participants (300 people), and date and time (August 5th, 5:00 PM to 9:00 PM). When the user enters the information and clicks the submit button, this information is given to the terminal as input.

[1193] The terminal collects the input information, formats the data, and sends it to the server in real time. This transmitted data becomes the input to the server.

[1194] Step 3: Save your data

[1195] The server analyzes the data received from the device and stores it in a database. The server takes the received data as input and stores it in a database using SQL queries, which stores the event information.

[1196] Step 4: Generate an operational proposal

[1197] The server inputs data stored in the database into the generative AI engine. The server issues SQL queries to obtain the necessary data and provides this data to the generative AI engine. The generative AI engine analyzes the input data and generates optimal management proposals. For example, it outputs proposals such as "Set up a game corner and food stalls," "Recruit local volunteers," and "Procure food and drinks within the budget."

[1198] Step 5: Proposal Notification

[1199] The generated management proposal is sent from the server to the terminal. The server sends the generated proposal to the terminal in the form of an HTTP response. The terminal receives this proposal, processes it as input, and reflects it on the display screen. The user can then confirm the proposal.

[1200] Step 6: Provide feedback

[1201] After the event, the user enters feedback on whether the event was successful or not, and on areas for improvement. The user fills in the information in the feedback form and clicks the submit button. This information is provided to the terminal as input.

[1202] Step 7: Submit your feedback

[1203] The terminal transmits feedback information to the server. The terminal collects input feedback information and transmits it to the server. This transmitted feedback information becomes input to the server.

[1204] Step 8: Save your feedback and update your knowledge base

[1205] The server receives the feedback information sent from the device and stores it in a database and knowledge base. The server takes the received feedback information as input and stores it in a database using SQL queries. It also updates the knowledge base, so that the feedback is reflected in future suggestions.

[1206] This structure efficiently supports the administrative work of the neighborhood association and revitalizes local activities.

[1207] (Application example 1)

[1208] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1209] In current factory operations, production planning and work efficiency are dependent on manual work and experience, resulting in problems such as inefficiencies and malfunctions. There is also a lack of real-time information sharing between equipment and robots, making it time-consuming to coordinate work. Furthermore, collecting feedback and incorporating it into the next plan is time-consuming, often delaying improvements. To solve these issues, a system is needed that collects and analyzes factory operation information and automatically generates and notifies optimal work plans.

[1210] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1211] In this invention, the server includes means for collecting operation information using a generation AI engine and storing it in a database, means for generating an optimal work plan based on the operation information stored in the database, and means for displaying the generated work plan on the robot terminal, thereby improving the efficiency of factory operations and enabling work optimization and real-time information sharing.

[1212] A "generative AI engine" is a computer system that uses machine learning and deep learning technologies to generate optimal suggestions and predictions from given data.

[1213] "Operational information" refers to data necessary for the operation of an organization such as a factory or local government, and includes information such as production plans, work schedules, staff allocation, budgets, and the operating status of each piece of equipment.

[1214] "Database" means an electronic data storage system for systematically storing and managing collected operational information.

[1215] An "optimal work plan" is a plan that proposes work schedules and allocations that maximize efficiency and effectiveness based on collected operational information.

[1216] A "robot terminal" is a terminal device attached to a robot or equipment in a factory, and is a device that has the function of displaying a generated work plan.

[1217] "Feedback information" is data on evaluations and areas for improvement collected after work or an event is carried out, and is important information that can be reflected in future plans.

[1218] A "knowledge base" is a knowledge database that stores past operational information and feedback information and uses it to generate future proposals and make decisions.

[1219] An "electronic circular board" is a system for sharing and circulating information electronically, rather than through the circulation of physical documents.

[1220] "Communication tools" are software and services that support information sharing and communication among members, including chat, video calls, email, etc.

[1221] This invention relates to a system for streamlining factory operations. Specifically, it is a system that uses a generative AI engine to collect and accumulate operational information, and then generates and notifies optimal work plans. Furthermore, it achieves continuous improvement by collecting feedback and reflecting it in the next plan.

[1222] The system's programs are primarily implemented in Python. The Python web framework Flask is used to build the API server that collects data and generates suggestions. The generative AI engine uses advanced natural language processing models such as OpenAI's GPT-3.

[1223] The hardware used will consist of terminals installed on the robots used in factories and a central management server. The terminals are expected to be mainly durable industrial tablets or interface devices built into the robots themselves.

[1224] First, the user (factory manager) inputs information about factory operations into the system via a terminal. Operational information includes the operating status of each piece of equipment, production plans, work plans, staff allocation, budgets, etc. This information is sent to the server in real time and stored in a database.

[1225] Next, the server uses a generative AI engine to generate an optimal work plan based on the accumulated data. The generated work plan includes specific steps, deployment, and personnel planning. The proposed results are then sent back from the server to the device and notified to the user.

[1226] For example, if a factory manager is seeking suggestions for how to run a new production line more efficiently, he might enter the following information into the system:

[1227] Number of machines in operation: 10

[1228] Number of staff: 5

[1229] Target production volume: 500 units / day

[1230] Budget: 500,000 yen

[1231] Here are some examples of prompts based on the input:

[1232] Propose the best work plan based on the factory's operational information, including:

[1233] Number of machines in operation: 10

[1234] Number of staff: 5

[1235] Target production volume: 500 units / day

[1236] Budget: 500,000 yen

[1237] Use this information to suggest an efficient work plan.

[1238] The system uses these prompts to generate a work plan using a generative AI engine. The resulting proposals include specific suggestions such as "distributing staff between machine maintenance and production line supervision," "procuring necessary materials within budget," and "prioritizing work such as frames." The generated proposals are displayed on the robot's terminal screen, allowing the user to proceed with the work based on them.

[1239] After the event is completed, users can input their feedback information into their devices and send it to the server, which then stores the collected feedback in a database and knowledge base and uses it to improve future operational proposals, thereby continuously improving operational efficiency.

[1240] In this way, the present invention not only achieves more efficient factory operations, but also enables continuous improvement through real-time information sharing and feedback collection.

[1241] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1242] Step 1:

[1243] Users input information about factory operations into the terminal. Specific information includes the number of machines in operation, the number of staff, target production volume, and budget. This information is saved on the terminal in data format such as JSON. The input data is sent to the server in real time.

[1244] input:

[1245] Number of machines in operation

[1246] Number of staff

[1247] Target production volume

[1248] budget

[1249] output:

[1250] JSON data sent to the server

[1251] Step 2:

[1252] The terminal sends the operational information entered by the user to the server. The server stores the received data in a database. Specifically, an INSERT query is issued to store each piece of operational information in the appropriate table in the database.

[1253] input:

[1254] Operational information entered by the user

[1255] output:

[1256] Operational information stored in the database

[1257] Step 3:

[1258] The server generates a prompt for the AI ​​engine based on the operational information stored in the database. The prompt text includes the operational information entered by the user and is generated in a format that encourages the proposal of an optimal work plan. This prompt text is sent to the AI ​​engine as an API request.

[1259] input:

[1260] Operational information stored in a database

[1261] output:

[1262] Prompt sent to the generative AI engine

[1263] Step 4:

[1264] The server receives the proposed work plan from the generative AI engine. The generative AI engine generates an optimal work plan based on the prompt and returns the result to the server. The server then analyzes it and stores it in a database.

[1265] input:

[1266] Work plan proposals from a generative AI engine

[1267] output:

[1268] Work plans stored in the database

[1269] Step 5:

[1270] The server sends the generated work plan to the terminal, which displays the received work plan on its screen and notifies the user. The user confirms the proposed content and begins work.

[1271] input:

[1272] Generated Work Plan

[1273] output:

[1274] Work plan displayed on the device

[1275] Step 6:

[1276] After completing a task, the user inputs feedback information into the terminal. The feedback information includes successes, problems, and areas for improvement. This feedback information is then sent back to the server.

[1277] input:

[1278] Feedback Information

[1279] output:

[1280] Feedback information sent to the server

[1281] Step 7:

[1282] The server stores the received feedback information in the database and knowledge base. Specifically, it stores the feedback information in the appropriate table of the database using an INSERT query and updates the knowledge base.

[1283] input:

[1284] Feedback Information

[1285] output:

[1286] Feedback information stored in databases and knowledge bases

[1287] These steps will streamline factory operations, enable real-time information sharing, and enable continuous improvement.

[1288] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1289] The present invention relates to a system that efficiently supports the management of neighborhood associations by combining a generative AI engine and an emotion engine. This system has the function of collecting and accumulating management information about the neighborhood association and generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among neighborhood association members by utilizing an electronic circular and communication tools. Furthermore, in addition to functions that support specific neighborhood association management tasks such as event planning, accounting management, and activity feedback collection, the system also has a means for recognizing user emotions using an emotion engine and making management proposals and communication support based on those emotions.

[1290] Explanation of program processing

[1291] 1. Supporting users' business operations

[1292] Users input information about the operation of their neighborhood association into the system via their terminal. For example, when a user inputs planning information for a "summer festival," they input details of the event (type, budget, number of participants, date and time, etc.). This information is sent from the terminal to the server.

[1293] 2. Role of the terminal

[1294] The terminal receives information input by the user and sends it to the server. It also displays suggestions and information returned from the server to the user. Specifically, it sends data entered by the user to the server in real time and reflects the generated suggestions on the display screen. The terminal supports information sharing and communication between users via electronic circulars and communication tools.

[1295] 3. Server Roles

[1296] The server receives the operational information sent from the device and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. The generated proposals are sent from the server to the device and notified to the user. The server also receives feedback information and updates the database and knowledge base.

[1297] 4. The Role of the Emotional Engine

[1298] The emotion engine recognizes the user's emotional state and reflects it in operational proposals and communication support. Specifically, it analyzes emotions based on user input, dialogue history, and facial expression analysis, and generates operational proposals that are adapted to the user's emotional state, such as making suggestions that reduce stress when the user's stress level is high.

[1299] Specific examples

[1300] For example, when members of a neighborhood association plan a "summer festival," the process goes as follows: First, the user logs in to their device and enters information about the "summer festival." At this time, details such as the budget, number of participants, and date and time are also entered. The entered data is sent from the device to a server, which stores it in a database.

[1301] Next, the server uses a generative AI engine to generate optimal suggestions based on the collected data. For example, specific action plans such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and drinks within a budget" are proposed. At the same time, an emotion engine is also running to analyze the user's emotional state. For example, if the user is feeling stressed, suggestions may include elements such as "division of tasks to reduce the burden." The generated suggestions are sent from the server to the device and notified to the user.

[1302] The user reviews the proposal and decides whether to adopt it. If they do, they proceed with specific preparations based on the proposal. After the event is over, the user enters feedback on whether it was successful or not and what needs to be improved, and sends it to the server from their device.

[1303] Finally, the server saves the feedback information in a database and updates the knowledge base. The updated knowledge base will be reflected in the next proposal generation, enabling more accurate operational support. In addition, since the feedback information also includes the user's emotional state, the emotion engine also contributes to updating the knowledge base in cooperation with the server. This will enable customized proposals to be made to individual users in the future.

[1304] In this way, the system of the present invention, which combines a generative AI engine and an emotion engine, streamlines the management operations of neighborhood associations and, by taking into consideration the emotions of members, provides more effective and satisfying management support.

[1305] The processing flow will be explained below.

[1306] Step 1:

[1307] A user logs in to a terminal and accesses the dashboard. The terminal prompts the user to enter their ID and password, and sends the entered information to the server. The server authenticates the user, and if authentication is successful, returns the user's dashboard information to the terminal. The terminal displays the received dashboard information to the user.

[1308] Step 2:

[1309] The user selects "Summer Festival Plan" from the event planning menu and enters event information. The items to be entered include the event type (summer festival), budget (50,000 yen), number of participants (100 people), and date and time (August 1, 2023). The device sends this input data to the server.

[1310] Step 3:

[1311] The server accumulates the event information received from the terminal in a database. Specifically, it organizes information about summer festival planning and saves it in the database in an appropriate format.

[1312] Step 4:

[1313] The server runs a generative AI engine based on the information stored in the database to generate optimal management proposals. The generative AI engine references past data and existing knowledge bases to generate specific proposals such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[1314] Step 5:

[1315] The emotion engine analyzes the user's emotional state based on input data, the user's dialogue history, facial expression analysis, etc. For example, if the user is feeling stressed, it will output a result that the stress level is high. The emotion engine then sends this emotional data to the server.

[1316] Step 6:

[1317] The server reflects the data from the emotion engine in the generated operational proposals and adjusts them based on the user's emotional state. For example, the proposals may include elements such as "division of roles to reduce workload" and "relaxing activities." The adjusted proposals are then sent to the device and notified to the user.

[1318] Step 7:

[1319] The user checks the proposal displayed on the terminal. If the proposal is satisfactory, they click the "Accept" button to accept the proposal. The terminal sends this instruction to the server, which records the adoption of the proposal in the database. This starts the specific preparations for the event.

[1320] Step 8:

[1321] After the event, the user fills in a feedback form to indicate whether the event was successful, what needs to be improved, and how they felt during the event. The device then sends this feedback information to the server.

[1322] Step 9:

[1323] The server saves the feedback information in a database and updates the knowledge base. The updated knowledge base is reflected in the next proposal generation, enabling more accurate operational support. In addition, since the feedback information also includes the user's emotional state, the emotion engine also works together to contribute to updating the knowledge base.

[1324] As described above, the system of the present invention not only improves the efficiency of neighborhood association management operations, but also makes the management of neighborhood associations more effective and satisfying by making individual suggestions that take into consideration the feelings of members.

[1325] Example 2

[1326] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1327] In the management of local governments, it is necessary to efficiently carry out a series of processes, from planning to execution and feedback collection, and to facilitate information sharing and communication among members. It is also important to make optimal management proposals while taking into consideration the emotional state of each member. Conventional systems have had difficulty meeting these requirements and have had problems such as a heavy workload.

[1328] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1329] In this invention, the server includes means for collecting management information provided by the local government and storing it in a data storage device, means for generating optimal management proposals based on the management information stored in the data storage device, means for notifying members of the local government of the generated management proposals, means for recognizing the emotional state of users using an emotion analysis system and reflecting this in the management proposals, and means for users to input feedback and update the data storage device. This makes it possible to streamline the management operations of the local government, facilitate information sharing and communication between members, and make optimal proposals that take into consideration the emotions of members.

[1330] A "local government" is an organization that operates and manages a local community and is composed of local residents and their representatives.

[1331] A "generative AI system" is an artificial intelligence system that analyzes input data and automatically generates suggestions and information tailored to specific purposes.

[1332] A "data store" is a database or storage system for storing collected data or information.

[1333] An "emotion analysis system" is a system that recognizes and analyzes a user's emotional state based on input, dialogue history, facial expression analysis, etc.

[1334] "Users" are individuals or members involved in the operation of the local government, who operate the system to input information and receive suggestions.

[1335] "Feedback" refers to information such as evaluations, opinions, and improvements provided by users regarding proposals and activities carried out.

[1336] A "bulletin board" is a digital platform for publishing and sharing information over the Internet or a local network.

[1337] "Communication tools" are software and applications for sending and receiving messages and for real-time communication.

[1338] This invention relates to a system that efficiently supports the management of local governments by combining a generative AI system and an emotion analysis system. This system has the function of collecting and accumulating management information about local governments and generating and notifying optimal management proposals based on that information. It also provides a means for smooth information sharing and communication among local government members by utilizing electronic bulletin boards and communication tools. Furthermore, in addition to functions that support specific local government management tasks such as event planning, financial management, and activity feedback collection, it also has a means for recognizing user emotions using an emotion analysis system and making management proposals and communication support based on those emotions.

[1339] System hardware and software configuration

[1340] This system consists of a server, a terminal, and a user. Details of each component are shown below.

[1341] server

[1342] The server includes a data storage device, a generative AI system, and an emotion analysis system. The data storage device functions as a database, storing the municipality's operational information and feedback information. The generative AI system analyzes the collected data and generates optimal operational proposals. The emotion analysis system analyzes the user's emotional state and reflects it in the operational proposals.

[1343] Terminal

[1344] The terminal is a device that allows users to access the system and input information. The information entered by the user is sent from the terminal to the server in real time. The terminal also displays suggestions and notifications generated as responses from the server. The terminal supports information sharing and communication between members through electronic bulletin boards and communication tools.

[1345] User

[1346] Users are individuals or members involved in the operation of the local government, who input information through their terminals and receive proposals from the server. Users log in to access the dashboard and input the necessary operational information (e.g., the name of the "Summer Festival," the budget, the number of participants, the date and time, etc.). They also have the role of sending feedback on the proposals.

[1347] Specific examples of behavior

[1348] For example, when members of a local government plan a "summer festival," the process is as follows:

[1349] 1. The user logs in to the device and enters details about the "Summer Festival," including the budget, number of participants, date and time, etc.

[1350] 2. The terminal sends the entered information to the server.

[1351] 3. The server stores the received data in a database and uses a generative AI system to generate optimal operation proposals, such as specific action plans such as "setting up a game corner and food stalls," "recruiting local volunteers," and "procuring food and beverages within a budget."

[1352] 4. At the same time, the emotion analysis system analyzes the user's emotional state and, for example, if the user is feeling stressed, adds elements such as "division of roles to reduce the burden" to the suggestions.

[1353] 5. The generated proposal is sent from the server to the device and notified to the user.

[1354] 6. The user reviews the proposal and decides whether to adopt it. If necessary, the user can enter feedback and send it to the server from the device.

[1355] 7. The server stores the feedback information in a database and updates the knowledge base, which improves the accuracy of future suggestions. It also takes into account information about the user's emotional state, resulting in more personalized suggestions.

[1356] Prompt Sentence Examples

[1357] "Generate specific proposals for planning a summer festival. Please take into consideration conditions such as the budget, number of participants, date and time, etc. Also, if users are under a lot of stress, please include ideas for reducing their stress."

[1358] In this way, by combining a generative AI system with an emotion analysis system, it is possible to streamline local government management operations and, by taking into consideration the emotions of members, provide more effective and satisfying management support.

[1359] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1360] Step 1:

[1361] A user logs in to a terminal. User input: User ID and password. Output: User's dashboard. Operation: The user enters their user ID and password on the terminal's login screen. The terminal sends this information to the server, which performs authentication. If authentication is successful, the server returns the user's dashboard to the terminal.

[1362] Step 2:

[1363] The user enters operational information. User input: Details of the "Summer Festival" (name, budget, number of participants, date and time, etc.). Output: Press the send button to prepare for data transmission. Operation: The user enters detailed information about the "Summer Festival" project from the dashboard and clicks the "Send" button.

[1364] Step 3:

[1365] The terminal sends operational information from the user to the server. Input: Operational information (name, budget, number of participants, date and time, etc.). Output: Sends data to the server. Operation: The terminal sends the information entered by the user to the server in real time.

[1366] Step 4:

[1367] The server saves the received data in the database. Input: Operational information. Output: Saving to database completed. Operation: The server verifies the received data, confirms its validity, and saves it in the database.

[1368] Step 5:

[1369] The server retrieves management information from the database and generates management proposals using a generative AI system. Input: Management information stored in the database. Output: Optimal management proposals. Operation: The server's generative AI system analyzes the data and generates specific action plans such as "setting up a game corner and food stalls" and "recruiting local volunteers."

[1370] Step 6:

[1371] The emotion analysis system analyzes the user's emotional state and adjusts operational proposals. Input: User's past logs and dialogue history. Output: Proposals reflected in the emotional state. Operation: The emotion analysis system analyzes the user's emotional state based on past input data and dialogue history, and if stress is high, adds proposals such as "division of roles to reduce burden."

[1372] Step 7:

[1373] The server sends the adjusted management proposal to the terminal. Input: Adjusted management proposal. Output: Transmission to terminal completed. Operation: The server sends the final management proposal to the terminal, and the terminal notifies the user of this content.

[1374] Step 8:

[1375] The user confirms the proposal and sends feedback. User input: Proposal confirmation, feedback input. Output: Feedback data sent successfully. Operation: The user confirms the proposal, enters feedback if necessary, and presses the "Send" button. The device sends this feedback to the server.

[1376] Step 9:

[1377] The server saves the feedback information in the database and updates the knowledge base. Input: Feedback data. Output: Database and knowledge base updated. Operation: The server saves the feedback information in the database and updates the knowledge base. It also works with an emotion analysis system to add additional data based on the emotional state to the knowledge base.

[1378] (Application example 2)

[1379] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1380] Conventional management support systems for neighborhood associations and stores are limited to collecting management information and generating proposals, and have the problem of not being able to make management proposals that take into account the emotional state of members and staff. This increases stress and burden, and leads to problems such as reduced management efficiency and satisfaction.

[1381] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1382] In this invention, the server includes means for collecting management information provided by the management target using a generation AI engine and storing it in a database, means for generating optimal management proposals based on the management information stored in the database, means for notifying the members of the management target of the generated management proposals, and means for analyzing the emotional states of the members using an emotion engine and generating proposals based on the analyzed emotional states. This improves management efficiency and enables management proposals that take into account the emotional states of members and staff.

[1383] The "generative AI engine" is an artificial intelligence system that analyzes operational information and automatically generates optimal proposals.

[1384] The "Emotion Engine" is a system that analyzes the emotional state of members and staff and makes operational suggestions and communication support based on that analysis.

[1385] "Operation information" refers to data related to operations provided by the operation target (for example, sales information, shift information, event details, etc.).

[1386] A "database" is a digital storage system for storing and managing operational information and feedback information.

[1387] An "operational proposal" is a specific action plan for improving operational efficiency that is generated by the AI ​​engine based on operational information.

[1388] "Notification means" refers to a communication means for communicating the generated management proposal to members and staff.

[1389] An "electronic circular" is a tool for sharing information in digital format, with the purpose of facilitating the communication of information between members.

[1390] "Communication tools" are digital tools that support communication and information sharing between members and staff.

[1391] "Feedback information" is information about the success or failure of the management or event and areas for improvement, and is reflected in the generation of proposals from the next time onwards.

[1392] This invention relates to a system that combines a generative AI engine and an emotion engine to improve the efficiency of brick-and-mortar store operations and provide operational support that takes into account the emotions of staff and customers. This system includes the following components and processing procedures:

[1393] Supporting users' work

[1394] Users input information about the operation of their physical stores (e.g., sales information, shift information, event plans, etc.) into the system via their smartphones. For example, when entering planning information for a "Christmas sale," they also enter details of the event (date and time, sales target, budget, special product inventory information, etc.). This information is sent from the smartphone to the cloud server.

[1395] Device Role

[1396] The smartphone receives input information from users and sends it to the cloud server in real time. It also displays suggestions and information returned from the cloud server to users. Furthermore, it supports information sharing and communication among staff members via electronic circulars and communication tools.

[1397] Server Roles

[1398] The cloud server receives the operational information sent from the smartphone and stores it in a database. The collected data is analyzed using a generative AI engine to generate optimal operational proposals. For example, these proposals include "discounts on products in specific categories" and "implementing social media campaigns" for sales. The generated proposals are sent from the cloud server to the smartphone and notified to the user.

[1399] The role of the emotional engine

[1400] The emotion engine recognizes the emotional state of users and staff and reflects this in operational proposals and communication support. Specifically, it analyzes emotions based on user input, dialogue history, and facial expression analysis, and makes suggestions that are less stressful when stress levels are high, for example. This reduces staff stress and improves operational efficiency.

[1401] Hardware and software used

[1402] Smartphone (iOS or Android)

[1403] Cloud server (AWS or Google Cloud)

[1404] Database (MySQL or MongoDB)

[1405] Generative AI engine (OpenAI GPT-4)

[1406] Emotion engine (Affectiva or Solid Recognition technology)

[1407] Example

[1408] For example, when a brick-and-mortar store owner plans a "Christmas sale," the process goes as follows: First, the store owner logs into their smartphone and enters information about the "Christmas sale." This includes details such as the budget, sales target, and stock information for special items. The entered data is sent from the smartphone to a cloud server, which then stores it in a database.

[1409] Next, the cloud server uses a generative AI engine to generate optimal proposals based on the collected data. Specific action plans are proposed, such as "discounts on products in specific categories," "rewarding shopping points," and "implementing social media campaigns." At the same time, an emotion engine is also running to analyze the emotional state of staff. For example, if a staff member is feeling stressed, suggestions might include adjusting shifts to reduce the burden. The generated proposals are sent from the cloud server to smartphones, where they are notified to the owner and staff.

[1410] Example prompt sentence:

[1411] Generate optimal store management proposals based on the following data:

[1412] (Event name) Christmas Sale

[1413] (Date and time) December 24, 2023 - December 25, 2023

[1414] (Target sales) 1 million yen

[1415] (Budget) 200,000 yen

[1416] (Special product) Christmas limited edition cake, gift set

[1417] (Discount information) 10% off all products, 20% off some products

[1418] (Staff shift) 4 people / day

[1419] We trust the suggestions made by the generative AI engine, so please make suggestions that take into consideration increasing sales and reducing the burden on staff.

[1420] In this way, by combining a generative AI engine and an emotion engine, it is possible to improve operational efficiency and provide operational support that takes into account the emotional state of staff.

[1421] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1422] Step 1:

[1423] Users input store operation information (e.g., sales information, shift information, event plans, etc.) into the system via their smartphones. This input includes detailed information about the "Christmas sale" (date and time, sales target, budget, special product inventory information, etc.). The input information is sent from the smartphone to the cloud server.

[1424] Input: Sales information, shift information, event planning and other operational information

[1425] Data calculation and processing: Collects information provided by users and sends it to the cloud server

[1426] Output: Operational information stored on the cloud server

[1427] Step 2:

[1428] The cloud server receives the operational information sent from the smartphone and stores it in a database, allowing for centralized management of the operational information.

[1429] Input: Operational information sent from smartphone

[1430] Data calculation and processing: Received operational information is formatted and stored in a database

[1431] Output: Operational information stored in the database

[1432] Step 3:

[1433] The cloud server analyzes the operational information stored in the database and uses a generative AI engine to generate optimal operational proposals, such as discount plans to achieve sales targets, implementing social media campaigns, and managing inventory for special products.

[1434] Input: Operational information stored in the database

[1435] Data calculation and processing: Data analysis and proposal generation using a generative AI engine

[1436] Output: Optimal operational proposal

[1437] Step 4:

[1438] The emotion engine recognizes the emotional state of users and staff and reflects this in operational suggestions. For example, it generates suggestions to reduce stress based on user input, dialogue history, and facial expression analysis if stress levels are high.

[1439] Input: User emotion data, input history, facial expression information

[1440] Data Calculation and Processing: Emotional State Analysis and Adaptive Suggestion Generation by Emotion Engine

[1441] Output: Operational suggestions adapted to the user's emotional state

[1442] Step 5:

[1443] The cloud server sends the generated management proposal to the smartphone and notifies the user, who then reviews the proposal and decides whether to adopt it.

[1444] Input: Optimal operational suggestions, suggestions adapted to emotional state

[1445] Data calculation and processing: Transfer and notification of proposal contents

[1446] Output: Proposal content notified to smartphone

[1447] Step 6:

[1448] Users can input feedback on the implemented proposals into the system via their smartphones, including feedback on whether the proposal was successful or not, as well as areas for improvement. The input information is then sent back to the cloud server.

[1449] Input: Feedback information (success or failure, areas for improvement, etc.)

[1450] Data calculation and processing: Collect feedback information from users and send it to the cloud server

[1451] Output: Feedback information stored on the cloud server

[1452] Step 7:

[1453] The cloud server stores the feedback information in a database and updates the knowledge base, allowing the generative AI engine to use more accurate information to generate future management proposals.

[1454] Input: Feedback information, operational data

[1455] Data calculation and processing: Feedback information stored in a database and knowledge base updated

[1456] Output: Improved accuracy of proposals from next time onwards

[1457] This processing step efficiently executes a series of operational support processes, from collecting operational information to generating proposals, notifying proposals, collecting feedback, and updating the knowledge base.

[1458] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1459] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1460] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1461] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1462] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1463] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1464] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1465] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1466] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1467] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1468] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1469] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1470] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1471] 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.

[1472] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1473] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1474] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1475] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1476] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1477] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1478] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1479] The following is further disclosed regarding the above embodiment.

[1480] (Claim 1)

[1481] A system for supporting the management of neighborhood associations,

[1482] A means of collecting operational information provided by residents' associations using a generative AI engine and storing it in a database;

[1483] A means for generating optimal management proposals based on the management information accumulated in the database;

[1484] a means for notifying members of the neighborhood association of the generated management proposal;

[1485] A system including:

[1486] (Claim 2)

[1487] 10. The system of claim 1, further comprising means for supporting information sharing and communication among members of the neighborhood association by utilizing electronic bulletin boards and communication tools.

[1488] (Claim 3)

[1489] 10. The system of claim 1, further comprising means for assisting the neighborhood association in event planning, accounting management, and activity feedback collection.

[1490] "Example 1"

[1491] (Claim 1)

[1492] A system for supporting the management of neighborhood associations,

[1493] A means for collecting input operational information using a generation AI engine and storing it in a database;

[1494] A means for generating optimal management proposals based on the management information accumulated in the database;

[1495] means for notifying a user of the generated management proposal;

[1496] a means for users to review the suggestions and provide feedback;

[1497] a means for storing the feedback information in a database and knowledge base;

[1498] A means to improve future suggestions based on updates to the knowledge base; and

[1499] A system including:

[1500] (Claim 2)

[1501] 10. The system of claim 1, further comprising means for supporting information sharing and communication between users by utilizing an electronic circular and communication tool.

[1502] (Claim 3)

[1503] 10. The system of claim 1, further comprising means for assisting in event planning, accounting management, and activity feedback collection.

[1504] "Application Example 1"

[1505] (Claim 1)

[1506] A system for supporting the operation of a local government,

[1507] A means for collecting operational information and storing it in a database using a generative AI engine;

[1508] A means for generating optimal management proposals based on the management information accumulated in the database;

[1509] a means for notifying members of the generated management proposal;

[1510] A means for generating an optimal work plan based on factory operation information;

[1511] a means for displaying the generated work plan on a terminal of the robot;

[1512] a means for storing and updating the collected feedback information in a database and knowledge base;

[1513] A system including:

[1514] (Claim 2)

[1515] 10. The system of claim 1, further comprising means for supporting information sharing and communication among members by utilizing electronic bulletin boards and communication tools.

[1516] (Claim 3)

[1517] 10. The system of claim 1, further comprising means for assisting in event planning, accounting management, and activity feedback collection.

[1518] "Example 2: Combining Emotion Engines"

[1519] (Claim 1)

[1520] A system for supporting the operation of a local government,

[1521] A means for collecting operational information provided by the local government using the generating AI system and storing it in a data storage device;

[1522] means for generating an optimal management proposal based on the management information stored in the data storage device;

[1523] a means of notifying the members of the municipality of the generated operational proposals;

[1524] A means for recognizing the emotional state of a user using an emotion analysis system and reflecting this in operational proposals;

[1525] means for the user to input feedback and update the data store;

[1526] A system including:

[1527] (Claim 2)

[1528] 10. The system of claim 1, further comprising means for utilizing electronic bulletin boards and communication tools to facilitate information sharing and communication among members of the local government.

[1529] (Claim 3)

[1530] 10. The system of claim 1, further comprising means for assisting a municipality in event planning, financial management, and activity feedback collection.

[1531] "Application example 2 when combining emotion engines"

[1532] (Claim 1)

[1533] A means for collecting management information provided by the management target using a generation AI engine and storing it in a database;

[1534] A means for generating optimal management proposals based on the management information accumulated in the database;

[1535] A means for notifying the generated management proposal to the members to be managed;

[1536] a means for analyzing the emotional state of members using an emotion engine and generating suggestions based thereon;

[1537] A system including:

[1538] (Claim 2)

[1539] 10. The system of claim 1, further comprising means for supporting information sharing and communication among members of the system using electronic circulars and communication tools.

[1540] (Claim 3)

[1541] 10. The system of claim 1, further comprising means for assisting in the planning, accounting, and collection of feedback on managed events. [Explanation of symbols]

[1542] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A system for supporting the management of neighborhood associations, A means of collecting operational information provided by residents' associations using a generative AI engine and storing it in a database; A means for generating optimal management proposals based on the management information accumulated in the database; a means for notifying members of the neighborhood association of the generated management proposal; A system including:

2. 10. The system according to claim 1, further comprising means for supporting information sharing and communication among members of the neighborhood association by utilizing an electronic bulletin board and communication tools.

3. The system of claim 1 further comprising means for supporting the neighborhood association in event planning, accounting management, and activity feedback collection.

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