system

Abstract

We provide the system. [Solution] The present invention relates to a sales support system that aims to improve the work efficiency and maximize the performance of sales staff, and comprises a schedule management department, a customer analysis department, an information gathering department, and a communication support department, with each department coordinating using generative AI. The schedule management department centrally manages work schedules and remaining tasks, the customer analysis department automatically generates optimal proposals for each customer, the information gathering department summarizes and organizes the latest product and campaign information, and the communication support department optimizes information sharing within the team. As a result, sales staff can grasp "when" and "what" to do in real time and in detail, creating an environment where they can concentrate on customer service and new initiatives.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method executed by at least one processor, the method comprising: a step of receiving a user utterance; a step of adding the user utterance to a prompt including an instruction text associated with a description relating to a character of the chatbot; a step of encoding the prompt; and a step of inputting the encoded prompt into a language model to generate a chatbot utterance that responds to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The problems that this invention aims to solve are a combination of challenges that hinder operational efficiency and performance maximization in the sales field. These challenges include the difficulty of prioritizing and allocating time due to the large volume and complexity of tasks that salespeople face on a daily basis, the difficulty of determining the optimal approach method and timing for each customer, the inability to allocate sufficient time to planning and executing measures for acquiring new customers, the need to quickly and accurately grasp ever-changing product and campaign information, and the decline in overall team performance due to inefficient information sharing and collaboration with superiors and colleagues. The invention aims to solve these challenges by having multiple AI agents work together to navigate salespeople in real time and specifically on "when" and "what" to do, and by automating and optimizing customer analysis, information gathering, and communication support, thereby providing an environment in which salespeople can concentrate on customer service and new initiatives that they should be focusing on, and comprehensively and efficiently solving all aspects of task prioritization, time management, information gathering, and team collaboration. [Means for solving the problem]

[0005] The means for solving the problems according to the present invention is to configure a sales support system equipped with a schedule management unit, a customer analysis unit, an information gathering unit, and a communication support unit. The schedule management unit centrally manages sales staff's work schedules, remaining tasks, and recommended actions in chronological order, and has the function of integrating information from other units to show sales staff "when" and "what" they should do in real time. The customer analysis unit analyzes information such as customer attributes, purchase history, and interests, and has the function of automatically generating optimal product and service proposals for each customer using generative AI and providing these proposals to the schedule management unit. The information gathering unit collects the latest product information, campaign information, and business-related information from internal and external sources, organizes the information using generative AI so that sales staff can check it at the necessary time, and provides it to the schedule management unit. The communication support unit promotes the sharing of information such as work communications, goals, and meeting schedules between sales staff and their superiors and colleagues, and has the function of optimizing information transmission using generative AI so that sales staff can appropriately grasp the necessary information within the team. These units work together to improve the work efficiency and maximize the performance of sales staff. [Brief explanation of the drawing]

[0006] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7]This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0007] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0008] First, let's explain the terminology used in the following explanation.

[0009] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0010] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0011] In the following embodiments, the storage with a reference sign is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include a flash memory (SSD (Solid State Drive)), a magnetic disk (for example, a hard disk), or a magnetic tape and the like.

[0012] In the following embodiments, the communication I / F (Interface) with a reference sign is an interface including a communication processor, an antenna, and the like. The communication I / F manages communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark) and the like.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, may be only B, or may be a combination of A and B. Further, in the present specification, when three or more matters are expressed in association with each other by using "and / or", the same concept as that for "A and / or B" is applied.

[0014] [First Embodiment]

[0015] FIG. 1 illustrates an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] As illustrated in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 includes a server.

[0017] 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 the "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), and the like.

[0018] 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, the camera 42, and the communication I / F 44 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user inputs. The touch panel 38A receives a user input from a pointer by detecting contact of the pointer (for example, a pen, a finger, or the like). The microphone 38B receives a voice-based user input by detecting the user's voice. A control unit 46A in the processor 46 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, a specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0022] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0024] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0026] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0027] (Example 1)

[0028] The flow of a specific process in Example 1 will now be described. Each part of the system described below is implemented by a data processing device 12 and a smart device 14. The data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0029] (Embodiments for carrying out the present invention)

[0030] As an embodiment for implementing the present invention, the sales support system is configured with a server and terminals connected by a network. The server side implements a schedule management unit, a customer analysis unit, an information collection unit, and a communication support unit, while the terminal side implements a user interface unit. The server can be configured in either a cloud environment or an on-premise environment, and various devices such as smartphones, tablets, personal computers, and wearable devices can be used as terminals. Sales staff can access the system from their terminals regardless of location or time, whether in the store, on the go, or working from home.

[0031] The Schedule Management Department operates on a server and centrally manages information such as work schedules, remaining tasks, recommended actions, progress, priorities, urgency, required time, assigned personnel, and related customers for each salesperson in a database. For example, when a salesperson checks "Today's Schedule" on their terminal, the Schedule Management Department integrates the latest information from the Customer Analysis Department and Information Gathering Department to generate a detailed action plan organized chronologically, such as "9:00: Store cleaning," "9:30: Inventory check," "10:00: Propose the latest smartphone to customer A," "10:30: Propose high-speed internet service to customer B," "11:00: Inform customer C about the new campaign," "13:00: Lunch break," "14:00: Follow-up call to customer D," "15:00: Review the new product manual," and "16:00: Meeting with supervisor," and sends it to the terminal. The Schedule Management Department utilizes generative AI to comprehensively analyze various factors such as sales staff's past work history, task completion status, customer feedback, the importance and urgency of each task, store congestion, weather, traffic information, and event information, and automatically performs optimal prioritization and rescheduling. For example, if customer E makes a last-minute appointment, the generative AI reconstructs the overall schedule, automatically adjusting the order and allocated time of other tasks, and immediately reflects the adjustments on the terminal, such as "adding customer E's visit to 11:00" or "changing the 11:00 appointment with customer C to 12:00." Furthermore, when sales staff input task progress from the terminal, the Schedule Management Department uses generative AI to automatically evaluate the progress and issues reminders or reprioritizes incomplete or delayed tasks.

[0032] The Customer Analysis Department operates on a server and stores and manages a variety of data in a database, including attribute information of customers handled by sales staff (age, gender, family structure, occupation, residential area, hobbies and preferences), past purchase history (purchased products, purchase timing, purchase frequency, purchase amount), interests (survey responses, inquiries, social media posts), store visit history, contract status, complaint history, satisfaction ratings, and referral history. Based on this data, the generative AI automatically generates optimal proposals and approaches for each customer, such as "Customer A has changed smartphone models four times in the past two years and has a high interest in the latest models," "Customer B is subscribed to a family discount plan and should be offered a new plan in accordance with changes in family structure," "Customer C is dissatisfied with the speed of their internet connection and is at high risk of switching to a competitor," and "Customer D has filed multiple complaints in the past and requires careful follow-up." Furthermore, the generative AI analyzes past communication history with customers (email, phone, face-to-face, chat), response trends (response speed, conversion rate, complaint rate), purchase cycle, and event information such as birthdays and anniversaries. It automatically optimizes the approach methods and timing, such as determining that "contacting customer A in the morning results in a higher conversion rate," "customer B prefers phone calls over emails," and "customer C should receive a special coupon on their birthday." For example, if a salesperson asks from their terminal, "What products should I suggest to customer A?", the customer analysis department uses the generative AI to analyze customer A's attributes and past responses, and automatically generates specific suggestion texts and example conversations, such as "a suggestion text emphasizing the camera features of the latest smartphone" or "a talk script explaining the benefits of a family discount plan," and displays them on the terminal.

[0033] The information gathering unit operates on a server and automatically collects and stores the latest product information, campaign information, competitor information, industry trends, FAQs, manual updates, and event information from internal systems (product database, campaign management system, FAQ system, manual management system) and external information sources (industry news sites, competitor websites, social media, review sites, weather forecast sites, traffic information sites). The generative AI extracts useful and necessary information for sales staff from the vast amount of data, summarizing and organizing it at the appropriate time according to the sales staff's work schedule and the status of their assigned customers. For example, it provides the schedule management unit with information such as "an overview of a new campaign starting today and its target customers," "features and selling points of newly released products," "a comparison of new service information from competitors with our own services," "examples of the latest answers to frequently asked customer questions," "information on events held around the store," and "predictions of store visits based on weather and traffic conditions." For example, if a new product is released in the morning, the generative AI immediately summarizes the information and reflects it as specific action instructions such as "check new product information at 10:00" and "propose the new product to the relevant customer after 11:00." Furthermore, if a salesperson requests "the latest campaign information" from their terminal, the information gathering department uses a generative AI to extract the most relevant campaign information based on the salesperson's assigned customers and past sales history, and displays a summary of it on the terminal.

[0034] The Communication Support Department operates on a server and manages necessary information sharing, work communication, goal communication, meeting scheduling, progress reporting, complaint sharing, success story sharing, and know-how sharing between salespeople and their superiors and colleagues. The generative AI automatically organizes and summarizes multiple pieces of information, such as "Today's new contract target is 3," "There is a company-wide meeting at 2pm," "Feedback from superior: Strengthen your approach to customer B," "Success story from a colleague: Cross-sell proposal to customer C resulted in a deal," and "Complaint handling manual," and notifies salespeople and relevant parties via their terminals at the appropriate time. In addition, when a salesperson enters progress status or issues from their terminal, the generative AI analyzes the content and automatically shares it with superiors and team members as needed. For example, if a salesperson enters "Customer C has made a complaint," the generative AI summarizes the content and immediately notifies the relevant departments and superiors. Furthermore, if a salesperson requests to learn about their colleagues' success stories via their terminal, the communication support department uses generative AI to extract similar cases from a database of past success stories, including those involving the salesperson's clients and proposals, summarizes them, and presents them on the terminal.

[0035] The terminals are expected to be smartphones, tablets, or PCs that sales staff use daily, and a user interface will be implemented. Sales staff can intuitively perform a wide range of operations from their terminals, including checking schedules, viewing customer information, obtaining the latest information, entering task progress, checking communication history, contacting superiors and colleagues, registering information via voice or image input, and making inquiries via chatbot. For example, if a sales staff member asks "What are today's priority tasks?" on their terminal, the schedule management unit on the server will use generative AI to instantly generate the optimal action plan and present it on the terminal. If a sales staff member records the content of a conversation with a customer via voice or text input, the generative AI will analyze the content, automatically extract reference information for the next approach and necessary follow-up tasks, and reflect them in the schedule management unit. For example, if a sales staff member takes a picture of a business card received from a customer with their smartphone, the generative AI can use image recognition and natural language processing to automatically extract the business card information and register it in the customer database.

[0036] Furthermore, for example, if a salesperson wants to check new campaign information from their terminal while out and about, the Information Gathering Department uses generative AI to summarize the latest information, highlighting points relevant to the salesperson's assigned customers and displaying them on the terminal. For example, if a salesperson asks from their terminal, "What products should I propose to customer A?", the Customer Analysis Department uses generative AI to analyze customer A's attributes and past responses, automatically generating and displaying the optimal proposal and talk script on the terminal. For example, if a salesperson inputs from their terminal, "I want to report my progress to my supervisor," the Communication Support Department uses generative AI to summarize the report, extracting the points important to the supervisor and automatically notifying them. For example, if a salesperson asks from their terminal, "I want to know the status of achieving this week's sales target," the Schedule Management Department uses generative AI to analyze sales data and progress, automatically summarizing the achievement rate, reasons for non-achievement, and future action plans and displaying them on the terminal.

[0037] As described above, in the embodiments of the present invention, various AI agent functions are centrally executed on the server side, and generative AI is essentially utilized in the core processing of each department. This automates the analysis, summarization, proposal, scheduling, notification, sharing, input assistance, image recognition, speech recognition, and natural language generation of vast and diverse information, allowing sales staff to receive real-time and optimized work support through their terminals. The generative AI plays an indispensable role in realizing the functions of each department, such as natural language processing, summary generation, automatic task generation, automatic customer response text generation, schedule optimization, summarization and extraction of communication content, business card information extraction by image recognition, and recording of conversation content by speech recognition. This makes it possible to comprehensively and concretely solve all kinds of on-site challenges, such as improving the work efficiency of sales staff, enhancing customer service capabilities, accelerating information acquisition, strengthening team collaboration, promoting new customer acquisition measures, accelerating complaint handling, sharing success stories, accumulating know-how, automating work reporting, and supporting the achievement of sales targets.

[0038] (System Configuration)

[0039] The system according to this embodiment comprises a schedule management unit, a customer analysis unit, an information gathering unit, a communication support unit, a user interface unit, a database unit, and a generative AI integration unit. The schedule management unit centrally manages information such as each salesperson's work schedule, remaining tasks, recommended actions, progress status, priority, urgency, required time, person in charge, and related customers. For example, when a salesperson checks "Today's Schedule" from their terminal, the system integrates the latest information from the customer analysis unit and the information gathering unit to generate a detailed action plan organized chronologically, such as "9:00: Store cleaning," "10:00: Propose the latest smartphone to customer A," "11:00: Propose high-speed internet service to customer B," "13:00: Inventory check," and "15:00: Check new campaign information," and sends it to the terminal. The schedule management unit utilizes generative AI to comprehensively analyze various factors such as the salesperson's past work history, task completion status, customer feedback, the importance and urgency of each task, store congestion, weather, traffic information, and event information, and automatically performs optimal prioritization and rescheduling. For example, if a customer makes a last-minute appointment, the generative AI restructures the overall schedule, automatically adjusting the order and allocation time of other tasks, and immediately reflecting the adjustments on the terminal, such as "Add customer E's appointment to 11:00" or "Change customer C's appointment from 11:00 to 12:00." Furthermore, when a salesperson inputs task progress from the terminal, the schedule management unit uses the generative AI to automatically evaluate the progress and issues reminders or reprioritizes incomplete or delayed tasks. Prompts such as "Restructure salesperson A's task list and priority for today, taking into account customer appointments and weather information" and "Generate reminder messages if there are incomplete tasks" are used for the generative AI.

[0040] The Customer Analysis Department accumulates and manages diverse data such as customer attribute information, past purchase history, interests, visit history, contract status, complaint history, satisfaction ratings, and referral history for customers handled by sales staff. Using generative AI, it automatically generates optimal proposals and approaches for each customer, such as "Customer A has changed smartphone models four times in the past two years and has a high interest in the latest models," "Customer B is subscribed to a family discount plan and should be offered a new plan in accordance with changes in family structure," "Customer C is dissatisfied with the speed of their internet connection and is at high risk of switching to a competitor," and "Customer D has filed multiple complaints in the past and requires careful follow-up." Furthermore, it analyzes past communication history and response trends with customers, purchase cycles, and event information such as birthdays and anniversaries, and automatically optimizes approach methods and timing, such as "Customer A has a higher conversion rate when contacted in the morning," "Customer B prefers phone calls over emails," and "Customer C should receive a special coupon on their birthday." When a salesperson inquires from their terminal, "What product should I suggest to customer A?", the customer analysis department uses generative AI to analyze customer A's attributes and past responses, and automatically generates specific suggestion statements and example conversations, such as "a suggestion statement emphasizing the camera features of the latest smartphone" or "a talk script explaining the benefits of a family discount plan," and displays them on the terminal. Prompts such as "Generate the optimal discount plan suggestion statement based on customer B's past purchase history and family structure" or "Create a follow-up email based on customer C's complaint history" are used for the generative AI.

[0041] The Information Gathering Department automatically collects and stores the latest product information, campaign information, competitor information, industry trends, FAQs, manual updates, event information, etc., from internal systems and external information sources. Using generative AI, it summarizes and organizes information such as "an overview of a new campaign starting today and its target customers," "features and selling points of newly released products," "a comparison of new services from competitors with our own services," "examples of the latest answers to frequently asked customer questions," "information on events held around the store," and "predictions of store visits based on weather and traffic conditions" at the appropriate time according to the sales staff's work schedule and the status of their assigned customers, and provides it to the Schedule Management Department. For example, if a new product is released in the morning, the generative AI immediately summarizes the information and reflects it as specific action instructions such as "check new product information at 10:00" and "propose the new product to the relevant customer after 11:00." If a sales staff member requests "the latest campaign information" from their terminal, the Information Gathering Department uses generative AI to extract the most relevant campaign information based on the sales staff member's assigned customers and past proposal history, and displays a summary on the terminal. For generative AI, prompts such as "Summarize the new campaign information starting today, highlighting points relevant to salesperson A's clients" and "Create a comparison table of a competitor's new service and our own service" are used.

[0042] The Communication Support Department manages necessary information sharing, work communication, goal communication, meeting scheduling, progress reporting, complaint sharing, success story sharing, and know-how sharing between sales staff and their superiors and colleagues. Using generative AI, it automatically organizes and summarizes multiple pieces of information, such as "Today's new contract target is 3," "There is a company-wide meeting at 2pm," "Feedback from superior: Strengthen your approach to customer B," "Success story from a colleague: Cross-sell proposal to customer C resulted in a sale," and "Complaint handling manual," and notifies sales staff and relevant parties via their terminals at the appropriate time. When a sales staff member inputs progress or issues from their terminal, the generative AI analyzes the content and automatically shares it with superiors and team members as needed. For example, if a sales staff member inputs "Customer C has made a complaint," the generative AI summarizes the content and immediately notifies the relevant departments and superiors. If a sales staff member inquires via their terminal, "I want to know about a colleague's success story," the Communication Support Department uses generative AI to extract similar cases from a database of past success stories, including the sales staff member's assigned customers and proposals, summarizes them, and presents them on the terminal. For generative AI, prompts such as "Summarize salesperson B's progress report and generate a report for the supervisor" and "Extract and summarize suitable approach examples for customer D from the past month's success stories" are used.

[0043] The user interface operates on devices such as smartphones, tablets, and PCs that salespeople use daily, allowing for intuitive operation of all tasks, including checking schedules, viewing customer information, obtaining the latest information, inputting task progress, checking communication history, contacting superiors and colleagues, registering information via voice or image input, and making inquiries via chatbot. For example, if a salesperson asks "What are today's priority tasks?" on their device, the schedule management unit on the server uses generative AI to instantly generate the optimal action plan and present it on the device. If a salesperson records the content of a conversation with a customer via voice or text input, the generative AI analyzes the content, automatically extracts reference information for the next approach and necessary follow-up tasks, and reflects them in the schedule management unit. If a salesperson takes a picture of a business card received from a customer with their smartphone, the generative AI can also automatically extract the business card information using image recognition and natural language processing and register it in the customer database. Prompts such as "Extract customer A's requests from this voice recording and generate the next proposal" or "Convert customer information to text from this business card image" are used with the generative AI.

[0044] The database department integrates and manages all data necessary for the entire system, including sales staff, customers, products, campaigns, tasks, communication history, progress, success stories, complaint history, FAQs, manuals, and event information. For example, it systematically records customer purchase history, past interaction history, task progress, sales performance for each product, conversion rates for each campaign, number of complaints, and details of success stories, allowing each department to quickly access and update this information when needed.

[0045] The Generative AI Integration Department receives prompts and data from each department, queries the Generative AI Engine via API, and returns the generated natural language text, summaries, proposals, talk scripts, reminders, progress reports, image recognition results, etc., to each department. For example, it receives a prompt from the Schedule Management Department to "prioritize and summarize salesperson A's tasks," sends it to the Generative AI Engine, and passes the returned summary to the Schedule Management Department. It receives a prompt from the Customer Analysis Department to "generate the optimal proposal based on customer B's attributes and purchase history," sends it to the Generative AI Engine, and passes the returned proposal to the Customer Analysis Department. It receives a prompt from the Information Gathering Department to "summarize new campaign information and highlight points relevant to salesperson C's assigned customers," sends it to the Generative AI Engine, and passes the returned summary to the Information Gathering Department. It receives a prompt from the Communication Support Department to "summarize salesperson D's progress report and generate a report for their supervisor," sends it to the Generative AI Engine, and passes the returned report to the Communication Support Department.

[0046] Thus, the system according to this embodiment, by having each part work together and utilizing generative AI at its core, can comprehensively and concretely solve a wide range of on-site challenges, including improving the work efficiency of sales staff, enhancing customer service capabilities, accelerating information gathering, strengthening team collaboration, promoting new customer acquisition measures, accelerating complaint handling, sharing success stories, accumulating know-how, automating business reporting, and supporting the achievement of sales targets.

[0047] (Implementation Steps)

[0048] Step 1: Register and update salesperson and customer information. Sales staff access the system from a terminal to input or update their profile information, customer list, work schedule, past task history, and progress status. Customer information includes customer attributes (age, gender, family structure, occupation, residential area, hobbies and preferences), past purchase history (purchased items, purchase date, purchase frequency, purchase amount), interests, visit history, contract status, complaint history, satisfaction rating, and referral history, which are entered from the terminal or automatically retrieved from an existing database. If a sales staff member records the content of a conversation with a customer via voice input or text input, the system saves that content to the database.

[0049] Step 2: Automated generation and optimization of work schedules The scheduling department centrally manages information such as sales staff's work schedules, remaining tasks, recommended actions, progress, priorities, urgency, required time, assigned staff, and related customers, and automatically generates optimal work schedules using generative AI. For example, it comprehensively analyzes various factors such as sales staff's past work history, task completion status, customer feedback, the importance and urgency of each task, store congestion, weather, traffic information, and event information to prioritize and reschedule. Examples of prompts for the generative AI include, "Reconstruct sales staff A's task list and priorities for today, taking into account customer appointment bookings and weather information," and "Generate reminder messages if there are any incomplete tasks."

[0050] Step 3: Generating optimal proposals for each customer The Customer Analysis Department uses generative AI to automatically generate optimal product and service suggestions for each customer based on data such as customer attribute information, purchase history, interests, visit history, contract status, complaint history, satisfaction ratings, and referral history. For example, based on analysis results such as "Customer A is highly interested in the latest smartphones," "Customer B is interested in family discount plans," and "Customer C is dissatisfied with the speed of their internet connection," the AI ​​generates specific suggestion texts and talk scripts. Examples of prompts for the generative AI include "Generate the optimal discount plan suggestion text based on Customer B's past purchase history and family structure," and "Create a follow-up email text based on Customer C's complaint history."

[0051] Step 4: Gathering and summarizing the latest information and external sources. The Information Gathering Department automatically collects the latest product information, campaign information, competitor information, industry trends, FAQs, manual updates, event information, etc., from internal systems and external sources, and uses generative AI to extract and summarize information that is useful and necessary for sales staff. For example, it organizes information such as "an overview of the new campaign starting today," "features and selling points of newly released products," "a comparison of new services from competitors with our own services," and "examples of the latest answers to frequently asked customer questions," and provides this information in a summarized and organized manner according to the sales staff's work schedule and the status of their assigned customers. Examples of prompts for the generative AI include "summarize the new campaign information starting today and highlight the points relevant to sales staff A's assigned customers" and "create a comparison table of new services from competitors and our own services."

[0052] Step 5: Communication support and information sharing The Communication Support Department manages necessary information sharing, work communication, goal communication, meeting scheduling, progress reporting, complaint sharing, success story sharing, and know-how sharing between sales staff and their superiors and colleagues. Using generative AI, it automatically organizes and summarizes multiple pieces of information and notifies sales staff and relevant parties at the appropriate time. For example, it automatically summarizes and notifies users of things like "Today's new contract target is 3," "There is a company-wide meeting at 2pm," "Feedback from superior: Strengthen your approach to customer B," and "Success story from a colleague: Cross-sell proposal to customer C resulted in a sale." Examples of prompts for the generative AI include "Summarize sales staff B's ​​progress report and generate a report for the superior" and "Extract and summarize suitable approach examples for customer D from the success stories of the past month."

[0053] Step 6: User interface operation and feedback Salespeople use the user interface on their terminals to check their schedules, view customer information, obtain the latest information, input task progress, check communication history, contact supervisors and colleagues, register information via voice or image input, and make inquiries via chatbot. For example, if a salesperson asks "What are today's priority tasks?" on the terminal, the schedule management unit on the server uses generative AI to instantly generate the optimal action plan and present it on the terminal. If a salesperson records the content of a conversation with a customer via voice or text input, the generative AI analyzes the content, automatically extracts reference information for the next approach and necessary follow-up tasks, and reflects them in the schedule management unit. If a salesperson takes a picture of a business card received from a customer with their smartphone, the generative AI can also automatically extract the business card information using image recognition and natural language processing and register it in the customer database. Examples of prompts for the generative AI include "Extract customer A's requests from this voice recording and generate the content of the next proposal" and "Convert customer information to text from this business card image."

[0054] (Specific use cases)

[0055] For example, when a salesperson arrives at work in the morning and accesses the system from their terminal, and inputs "Show today's work schedule" through the user interface unit, the schedule management unit retrieves the salesperson's customer list, task progress up to the previous day, today's customer reservations, store congestion forecast, weather information, traffic information, and company event information from the database unit. The AI ​​generation unit then sends a prompt message to the generation AI via the generation AI integration unit, stating, "Reconstruct salesperson A's task list and priorities for today, taking into account customer reservations and weather information." The generation AI analyzes this information and automatically generates a detailed schedule considering priorities and time allocation, such as "9:00: Store cleaning," "9:30: Inventory check," "10:00: Propose the latest smartphone to customer X," "11:00: Propose high-speed internet service to customer Y," "13:00: Check new campaign information," "14:00: Follow-up call to customer Z," and "15:00: Meeting with supervisor," and presents it to the terminal via the schedule management unit.

[0056] Furthermore, if a salesperson asks via the terminal, "What product should I suggest to customer X?", the customer analysis department retrieves customer X's attribute information, past purchase history, interests, visit history, contract status, complaint history, and social media posts from the database department. This prompt is then sent via the generation AI integration department to "Generate the optimal product suggestion based on customer X's attributes and purchase history." Based on analysis results such as "Customer X has changed smartphone models three times in the past two years and has a high interest in the latest models" or "Customer X is subscribed to a family discount plan, so we should introduce the new family plan," the generation AI automatically generates specific suggestion texts and example conversations, such as "Suggestion text emphasizing the camera features of the latest smartphone" or "Talk script explaining the benefits of the family discount plan," and presents them to the terminal via the customer analysis department.

[0057] Furthermore, if a salesperson requests the latest campaign information via a terminal, the information gathering department collects new campaign information, competitor information, industry trends, etc., from internal systems and external sources, and sends a prompt message via the generation AI integration department stating, "Summarize the new campaign information starting today and highlight the points relevant to salesperson A's customers." The generation AI then summarizes, for example, "an overview of the new campaign starting today," "the target customer base," "differences from competitors," and "points that are particularly effective for salesperson A's customers," and displays them on the terminal via the information gathering department.

[0058] Furthermore, if a salesperson inputs "I want to send a progress report to my supervisor" from their terminal, the Communication Support Department retrieves the salesperson's daily task progress, number of deals closed, unfinished tasks, customer feedback, and complaint status from the Database Department, and sends a prompt message via the Generation AI Integration Department saying, "Summarize salesperson A's progress for today and generate a report for the supervisor." The Generation AI summarizes "tasks completed today," "unfinished tasks and the reasons for them," "number of deals closed and target achievement rate," "positive customer feedback," and "dealings taken when complaints occurred," and automatically sends it to the supervisor via the Communication Support Department.

[0059] Furthermore, if a salesperson records the content of a conversation with a customer via voice or text input, the user interface unit sends that data to the generation AI integration unit and sends a prompt message to the generation AI saying, "Extract customer X's requests from this voice recording and generate the content of the next proposal." The generation AI analyzes the conversation content and automatically generates a specific action plan, such as "Customer X is dissatisfied with the battery life of their smartphone, so we should propose a model with a large-capacity battery next time," and reflects this in the schedule management unit and customer analysis unit.

[0060] Furthermore, if a salesperson takes a picture of a business card received from a customer with their smartphone, the user interface unit sends the image data to the generation AI integration unit and sends a prompt message to the generation AI saying, "Convert customer information into text from this business card image." The generation AI automatically extracts the business card information using image recognition and natural language processing and registers it in the customer database.

[0061] Thus, the system of the present invention utilizes generating AI at each step, from the start of a salesperson's work to customer service, information gathering, progress reporting, data entry, task management, and communication support, automatically providing real-time and optimal information, generating proposals, summarizing, scheduling, and extracting data for all business requests entered by the salesperson from a terminal. Specific examples of prompts to be fed into the generating AI include: "Reconstruct salesperson A's task list and priorities for today, taking into account customer appointment bookings and weather information," "Generate the optimal product proposal from customer X's attributes and purchase history," "Summarize the new campaign information starting today, highlighting points relevant to salesperson A's assigned customers," "Summarize salesperson A's progress for today and generate a report for their supervisor," "Extract customer X's requests from this audio recording and generate the content of the next proposal," and "Convert customer information from this business card image into text."

[0062] (Application Example 1) The flow of a specific process in Application Example 1 will be explained below. Each part of the system described below is implemented by a data processing device 12 and a smart device 14. The data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0063] (Embodiments for carrying out the present invention)

[0064] As an embodiment for carrying out the present invention, the caregiving support system is configured with a server and terminals connected by a network. The server side implements a schedule management unit, a care analysis unit, an information collection unit, and a communication support unit, while the terminal side implements a user interface unit. The server can be configured in either a cloud environment or an on-premise environment, and the terminals can be a variety of devices carried by care staff, such as smartphones, tablets, personal computers, wearable devices, voice input devices, barcode readers, and automatic vital sign recording devices. Care staff can access this system from their terminals regardless of location or time, such as within the facility, at home care sites, visiting care sites, day services, short-stay facilities, night shifts, and during emergency responses.

[0065] The scheduling department operates on a server and centrally manages information for each care staff member in a database, including work schedules, remaining tasks, recommended actions, progress status, priorities, urgency, required time, assigned clients, related medical institutions, family contact information, shift information, night / day shift classification, assigned area, handover items between staff, care plans for each client, emergency response manuals, and accident / complaint history. For example, when a caregiver checks "Today's Schedule" on their terminal, the Schedule Management Department integrates the latest information from the Care Analysis Department and the Information Gathering Department to generate a detailed action plan organized chronologically, such as "8:30 AM: Morning temperature measurement," "9:00 AM: Position change and pressure ulcer prevention care for user A," "9:30 AM: Excretion assistance for user B," "10:00 AM: Medication confirmation and hydration for user C," "10:30 AM: Walking training for user D," "11:00 AM: Bathing assistance for user E," "11:30 AM: Lunch preparation," "12:00 PM: Meal assistance," "1:00 PM: Rehabilitation for user F," "2:00 PM: Support for user G's participation in recreation," "3:00 PM: Manual check of the care record system," "4:00 PM: Regular report to family," and "5:00 PM: Handover to night shift staff," and sends this plan to the terminal. The Schedule Management Department utilizes generative AI to comprehensively analyze a variety of factors, including the past work history of care staff, task completion status, feedback from users, the importance and urgency of each task, facility congestion, weather, traffic information, event information, urgent instructions from doctors, requests from families, nighttime accident history, staff health information, and shift change requests, and automatically performs optimal prioritization and rescheduling. For example, if user H reports a sudden fever, the generative AI reconstructs the overall schedule, automatically adjusting the order and allocation time of other tasks, and immediately reflects the adjustments on the terminal, such as "add emergency response for user H at 10:00," "change user C's medication check at 10:00 to 10:30," and "move bathing assistance at 11:00 to the afternoon." Furthermore, when care staff input task completion or progress from the terminal, the Schedule Management Department uses generative AI to automatically evaluate the progress and issues reminders or reprioritizes incomplete or delayed tasks.For example, it allows for flexible management tailored to on-site operations, such as "If bathing assistance for user E at 11:00 is not completed, a reminder will be displayed at 12:00" or "If handover information for night shift staff has not been entered, other tasks will be temporarily suspended until the handover is complete."

[0066] The Care Analysis Department operates on a server and stores and manages a variety of data in a database, including the health status of users under the care of care staff (vital signs, temperature, blood pressure, pulse, respiratory rate, SpO2, blood glucose level, weight, BMI), level of care required, presence or absence of dementia, medication status, rehabilitation history, dietary restrictions, allergy information, requests and instructions from family and doctors, nighttime behavior, past care history, fall and accident history, infection risk, lifestyle rhythm, hobbies and preferences, psychological state, sleep patterns, excretion patterns, food intake, water intake, pressure ulcer risk assessment, motor function assessment, cognitive function assessment, QOL indicators, feedback from family, and medical information reports from medical institutions. Based on this data, the generative AI will, for example, "User A has a high level of care needs and is at risk of pressure ulcers, so we recommend changing their position and providing skin care every two hours, and taking photographic records of their skin condition daily," "User B has dementia, so we will focus on reminiscence therapy rehabilitation and supervision in the morning, and encourage participation in recreation in the afternoon," "User C has a mild case, but requires medication management and reminders about hydration, so we will use barcode authentication to prevent medication errors," "User D needs walking training, so we will conduct it in the afternoon in cooperation with the rehabilitation staff, and record walking distance and fall risk each time," "User E at night The system automatically generates optimal care plans, timing, rehabilitation suggestions, medication management, monitoring plans, emergency response measures, family support measures, and QOL improvement measures for each user, such as: "Due to wandering in between, we recommend strengthening morning monitoring and managing location information using GPS tags"; "User F's food intake is on a downward trend, so we instruct that nutritional supplements be suggested and that meal content be modified"; "User G's family has requested an outing, so we automatically suggest a risk assessment for outings and the assignment of accompanying staff"; and "User H has been prescribed a new medication, so we recommend monitoring for side effect risks and recording changes in physical condition after taking the medication." Furthermore, the generating AI reflects the user's vital signs, previous care records, nighttime condition, latest instructions from doctors, requests from families, psychological changes, seasonal variations, infectious disease outbreaks, and the number of infected people in the facility in real time, and automatically adjusts the care content as needed.For example, if user A has a slightly elevated body temperature, the system can "provide additional hydration and report to a doctor"; if user B wanders around at night, it can "strengthen monitoring in the morning and report the situation to the family"; if user C has a decreased appetite, it can "adjust the content of meals and suggest nutritional supplements"; if user D's rehabilitation progress is good, it can "reset the walking distance target"; and if user E has a fall, it can "automatically generate an accident report and suggest measures to prevent recurrence." This allows for flexible responses tailored to the situation.

[0067] The information gathering unit operates on a server and automatically collects and stores the latest care guidelines, legal revisions, infectious disease control measures, manual updates, new findings on rehabilitation methods, drug information, accident prevention warnings, the latest trends in care techniques, new dementia care methods, fall prevention measures, diet and nutrition management guidelines, family support measures, ICT utilization case studies, care fee revision information, subsidy and grant information, regional collaboration case studies, disaster response manuals, special response measures during infectious disease outbreaks, zoning guidelines in the event of an infection within a facility, behavioral and psychological symptom management measures for elderly people with dementia, the latest guidelines for pressure ulcer prevention, new product information on welfare equipment, care robot implementation case studies, telemedicine utilization case studies, and new function information for care record systems, all from sources such as the Ministry of Health, Labour and Welfare, local governments, medical institutions, care robot implementation case studies, and more. Generative AI extracts useful and necessary information for care staff from a vast amount of data, such as "Key points of the new care guidelines that will be applied from today," "Response manuals during infectious disease outbreaks," "Information on side effects of new drugs," "Latest precautions for preventing falls," "New rehabilitation methods for dementia care," "Latest guidelines for meal assistance," "New systems for family support," "Examples of introducing monitoring technology using ICT," "Changes in operations due to revisions in care fees," "Points to consider when formulating evacuation plans in the event of a disaster," "Zoning procedures in the event of an infection outbreak in the facility," "Introduction of new pressure-relieving mats for pressure ulcer prevention," "Points to note when introducing telemedicine," "Effects and challenges of introducing care robots," and "How to utilize the new functions of the care record system." This information is then summarized and organized at the appropriate time according to the care staff's work schedule and the situation of the users they are responsible for, and provided to the schedule management department. For example, if a new infectious disease control manual is released in the morning, the generative AI will immediately summarize the information and reflect it as specific action instructions such as "Check the new manual at 10:00" and "Strengthen support for the affected users from 11:00 onwards." Furthermore, if a care staff member requests from their terminal to "please tell me the latest care guidelines," "I want to know the key points of the new rehabilitation methods," or "please summarize the impact of the care fee revision," the information gathering department uses a generative AI to extract the most relevant guidelines, points to note, and changes in operations based on the assigned users, past care history, and the facility's operational status, and displays a summary on the terminal.

[0068] The Communication Support Department operates on a server and manages necessary information sharing and work communication between care staff and doctors, nurses, rehabilitation therapists, family members, other care staff, administrators, community comprehensive support centers, care managers, pharmacists, nutritionists, welfare equipment specialists, government officials, volunteers, and external lecturers. This includes confirming care policies, giving instructions for emergency response, sharing success stories and precautions, providing regular reports to family members, coordinating with medical institutions, responding to accidents and complaints, sharing know-how, adjusting shifts, providing training information, coordinating with the community, establishing a disaster contact network, sharing information during infectious disease outbreaks, emergency contact during night shifts, requesting support during ICT problems, and reporting malfunctions of welfare equipment. The generative AI automatically organizes and summarizes multiple pieces of information, such as "Today's focus care is pressure ulcer prevention," "Message from doctor: Change in medication for user B," "Request from family: User C wants to go out," "Manual for responding to falls at night," "Feedback from rehabilitation staff: Improvement in user D's walking ability," "Success story from a colleague: New reminiscence therapy rehabilitation is effective for dementia users," "Automatic generation of regular reports to family members," "Contact for shift adjustments," "Evacuation instructions in case of disaster," "Zoning instructions in case of infectious disease outbreak," "Notification of malfunction of welfare equipment and arrangement of replacements," and "Generation of support request messages in case of ICT trouble," and notifies care staff and related parties via their terminals at the appropriate time. When care staff input progress or issues from their terminals, the generative AI analyzes the content and automatically shares it as needed with doctors, supervisors, family members, other staff, community comprehensive support centers, care managers, and administrative officials. For example, if a care staff member inputs "User E had a fall," the generative AI summarizes the content and immediately notifies relevant departments, doctors, family members, administrators, and administrative officials. Furthermore, if a care staff member requests from their terminal to "learn about successful cases among colleagues," "share practical examples of new rehabilitation methods," or "get the latest information on disaster evacuation plans," the Communication Support Department uses generative AI to extract similar cases and the latest information from a database of past success stories, the latest training materials, government notices, and community collaboration cases, summarizes them, and presents them on the terminal.

[0069] The terminals are expected to include smartphones, tablets, PCs, wearable devices, voice input devices, barcode readers, and automatic vital sign recording devices used daily by care staff, and a user interface will be implemented. From the terminal, care staff can intuitively perform a wide range of operations, such as checking schedules, viewing user information, obtaining the latest information, inputting task progress, checking communication history, contacting doctors and family members, registering information via voice or image input, making inquiries via chatbot, automatically recording vital signs, recording care with photos and videos, identifying users with QR codes, managing medication with barcodes, monitoring with GPS tags, receiving evacuation orders in case of disaster, receiving zoning orders in case of infectious disease outbreaks, requesting support in case of ICT trouble, reporting malfunctions of welfare equipment, making emergency contacts during night shifts, watching training videos, and using a know-how sharing bulletin board. For example, if a care staff member asks "What are today's priority tasks?" on the terminal, the schedule management unit on the server will immediately generate the optimal action plan using generative AI and present it to the terminal. When care staff record conversations with users via voice or text input, a generative AI analyzes the content, automatically extracts reference information for the next approach and necessary follow-up tasks, and reflects them in the schedule management department. For example, if care staff take photos of medical cards or medication information received from users with their smartphones, the generative AI can automatically extract the information using image recognition and natural language processing and register it in the user database. Furthermore, by reading medication barcodes with a barcode reader, it is possible to prevent medication errors and automatically record medication history. Monitoring using GPS tags allows for real-time tracking of users' locations, supporting the safety of users at high risk of wandering. In the event of a disaster or infectious disease outbreak, evacuation orders and zoning instructions are automatically notified to the terminal, enabling staff to respond quickly and accurately.

[0070] Thus, in the embodiments of the present invention, various AI agent functions are centrally executed on the server side, and generative AI is essentially utilized in the core processing of each part, thereby automating the analysis, summarization, proposal, scheduling, notification, sharing, input assistance, image recognition, speech recognition, natural language generation, barcode recognition, GPS integration, disaster response, and infectious disease response of vast and diverse information, allowing care staff to receive real-time and optimized work support through their terminals. The generative AI plays an indispensable role in realizing the functions of each part, such as natural language processing, summary generation, automatic task generation, automatic generation of care proposal texts, schedule optimization, summarization and extraction of communication content, extraction of medical card information by image recognition, recording of conversation content by speech recognition, medication management by barcode recognition, monitoring by GPS integration, automatic instruction generation during disasters and infectious diseases, and automatic summarization of know-how sharing bulletin boards. This will enable comprehensive and concrete solutions to a wide range of on-site challenges, including improving the efficiency of care staff's work, enhancing the quality of care for users, accelerating information gathering, strengthening team collaboration, strengthening cooperation with families and medical institutions, expediting accident and complaint response, sharing success stories, accumulating know-how, automating work reporting, optimizing care plans, accelerating disaster and infectious disease response, streamlining ICT troubleshooting, and enhancing welfare equipment management.

[0071] (System Configuration)

[0072] The system according to this embodiment comprises a schedule management unit, a care analysis unit, an information gathering unit, a communication support unit, a user interface unit, a database unit, and a generation AI integration unit. The schedule management unit centrally manages information such as the work schedule, remaining tasks, recommended actions, progress status, priority, urgency, required time, assigned users, related medical institutions, family contact information, shift information, night / day shift classification, assigned area, handover items between staff, care plans for each user, emergency response manuals, and accident / complaint history. It generates detailed action plans organized chronologically, such as "8:30: Morning temperature measurement," "9:00: Changing user A's position and pressure ulcer prevention care," "10:00: Assisting user B with excretion," "11:00: Checking user C's medication and hydration," "13:00: Walking training for user D," "15:00: Checking the care record system manual," and "17:00: Handover to night shift staff," and sends them to the terminal. The Schedule Management Department, via the Generation AI Integration Department, sends prompt messages to the Generation AI, such as "Summarize all staff tasks for today with priority," "Generate reminder messages if there are incomplete tasks," and "Reorganize the schedule if there is a sudden change in a user's health," thereby automatically achieving optimal scheduling, reminders, and prioritization.

[0073] The Care Analysis Department collects diverse data from the Database Department, including the user's health status (vital signs, temperature, blood pressure, pulse, respiratory rate, SpO2, blood glucose level, weight, BMI), level of care required, presence or absence of dementia, medication status, rehabilitation history, dietary restrictions, allergy information, requests and instructions from family and doctors, nighttime behavior, past care history, fall / accident history, infection risk, lifestyle rhythm, hobbies and preferences, psychological state, sleep patterns, excretion patterns, food intake, water intake, pressure ulcer risk assessment, motor function assessment, cognitive function assessment, QOL indicators, feedback from family, and medical information reports from healthcare institutions. The system acquires data and sends prompt messages to the AI ​​generation unit via the AI ​​generation unit, such as "Suggest the necessary care for this morning based on user A's health status and past care history," "Generate an optimal rehabilitation plan based on user B's dementia progression and lifestyle," "Extract points to note regarding medication management from user C's medication history and allergy information," and "Suggest recurrence prevention measures based on user D's fall accident history." The AI ​​then automatically generates optimal care content and timing, rehabilitation suggestions, medication management, monitoring plans, emergency response measures, family support measures, and QOL improvement measures for each user, and provides them to the schedule management unit.

[0074] The Information Gathering Department collects the latest care guidelines, legal revisions, infectious disease control measures, manual updates, new findings in rehabilitation methods, drug information, accident prevention warnings, the latest trends in care techniques, new dementia care methods, fall prevention measures, diet and nutrition management guidelines, family support measures, ICT utilization examples, care fee revision information, subsidy and grant information, regional collaboration examples, disaster response manuals, special response measures during infectious disease outbreaks, zoning guidelines in the event of an infection within a facility, and cognitive impairment. These are all sourced from the Ministry of Health, Labour and Welfare, local governments, medical institutions, care-related organizations, academic societies, research institutions, pharmaceutical companies, care product manufacturers, insurance companies, family associations, community comprehensive support centers, ICT vendors, and welfare equipment rental companies. The system automatically collects and stores information such as behavioral and psychological symptom management strategies for elderly patients, the latest guidelines for pressure ulcer prevention, new product information on welfare equipment, case studies of care robot implementation, case studies of telemedicine utilization, and information on new functions of care record systems. Through the AI ​​generation and collaboration department, prompts such as "Summarize the key points of the new care guidelines that will be applied from today," "Summarize the response manual for infectious disease outbreaks for on-site staff," "Extract side effect information for new drugs and summarize the points to note regarding medication management," and "Summarize the latest points to note regarding fall prevention for on-site staff" are sent to the AI ​​generation department. This extracts and summarizes useful and necessary information for care staff and provides it to the schedule management department and the care analysis department.

[0075] The Communication Support Department facilitates necessary information sharing and operational communication between care staff and doctors, nurses, rehabilitation therapists, family members, other care staff, managers, community comprehensive support centers, care managers, pharmacists, nutritionists, welfare equipment specialists, government officials, volunteers, and external lecturers. This includes confirming care policies, providing instructions for emergency response, sharing success stories and precautions, regular reporting to family members, coordinating with medical institutions, handling accidents and complaints, sharing know-how, adjusting shifts, providing training information, collaborating with the community, establishing a disaster contact network, sharing information during infectious disease outbreaks, emergency contact during night shifts, and providing support during ICT problems. The system manages reports of malfunctions in welfare equipment and sends prompt messages to the AI ​​generation unit via the AI ​​generation unit. These prompts include "Summarize today's key care needs and the reasons why, and notify all staff," "Generate a document explaining medication change instructions from the doctor for family members," "Summarize the response manual for nighttime fall accidents and notify night shift staff," "Extract successful case studies from colleagues and summarize the points that should be shared on-site," and "Summarize the latest information on disaster evacuation plans and notify all staff." The system automatically organizes and summarizes multiple pieces of information and notifies and shares them with care staff and relevant parties at the appropriate time via their devices.

[0076] The user interface operates on smartphones, tablets, PCs, wearable devices, voice input devices, barcode readers, and automatic vital sign recording devices that care staff use daily. It allows for intuitive operation of all tasks, including checking schedules, viewing user information, obtaining the latest information, inputting task progress, checking communication history, contacting doctors and family members, registering information via voice or image input, making inquiries via chatbot, automatically recording vital signs, recording care with photos and videos, identifying users with QR codes, managing medication with barcodes, monitoring with GPS tags, receiving evacuation orders during disasters, receiving zoning orders during infectious disease outbreaks, requesting support in case of ICT troubles, reporting malfunctions of welfare equipment, making emergency contacts during night shifts, watching training videos, and using a know-how sharing bulletin board. For example, it can handle diverse on-site needs such as "recording user A's vital signs with voice input," "managing user B's medication with barcodes," "monitoring user C with GPS tags when they go out," "registering user D's care records with photos," "receiving evacuation orders in real time during disasters," and "making emergency contacts by voice during night shifts."

[0077] The database department integrates and manages all data necessary for the entire system, including care staff, users, medical institutions, families, work schedules, tasks, care history, vital signs, medication history, rehabilitation history, accident / complaint history, shift information, family contact history, medical institution collaboration history, training history, know-how sharing history, disaster / infectious disease response history, welfare equipment management history, and ICT trouble response history, enabling each department to quickly access and update this data when needed.

[0078] The Generation AI Integration Unit receives prompts and data from each unit, queries the Generation AI engine via API, and returns generated natural language text, summaries, suggestions, talk scripts, reminders, progress reports, image recognition results, barcode recognition results, GPS integration results, etc., to each unit. For example, prompts such as "Suggest the necessary care for this morning based on user A's health condition and past care history," "Summarize the key points of the new care guidelines that will be applied from today," "Generate an explanatory document for the family regarding the doctor's medication change order," "Summarize the response manual for nighttime fall accidents and notify the night shift staff," and "Extract successful case studies from colleagues and summarize the points that should be shared on-site" are used.

[0079] Thus, the system according to this embodiment, by having each part work together and utilizing generating AI at its core, can comprehensively and concretely solve a wide range of on-site challenges, including improving the work efficiency of care staff, improving the quality of user care, accelerating information gathering, strengthening team collaboration, strengthening cooperation with families and medical institutions, accelerating accident and complaint response, sharing success stories, accumulating know-how, automating work reporting, optimizing care plans, accelerating disaster and infectious disease response, streamlining ICT trouble response, and enhancing welfare equipment management.

[0080] (Implementation Steps)

[0081] Step 1: Register and update user and staff information. Care staff access the system from a terminal to input or update their profile information, list of assigned clients, work schedule, past task history, progress status, shift information, assigned area, night / day shift classification, handover information, etc. Client information includes health status (vital signs, temperature, blood pressure, pulse, respiratory rate, SpO2, blood glucose level, weight, BMI), level of care required, presence or absence of dementia, medication status, rehabilitation history, dietary restrictions, allergy information, requests / instructions from family and doctors, nighttime behavior, past care history, fall / accident history, infection risk, lifestyle rhythm, hobbies and preferences, psychological state, sleep patterns, excretion patterns, food intake, water intake, pressure ulcer risk assessment, motor function assessment, cognitive function assessment, QOL indicators, feedback from family, and medical information referral letters from medical institutions, which are input from the terminal or automatically retrieved from an existing database.

[0082] Step 2: Automated generation and optimization of work schedules The scheduling department centrally manages information such as care staff's work schedules, remaining tasks, recommended actions, progress, priorities, urgency, required time, assigned clients, related medical institutions, family contact information, shift information, night / day shift classifications, assigned areas, handover items, individual client care plans, emergency response manuals, and accident / complaint history, and uses a generation AI to automatically generate the optimal work schedule. For example, it comprehensively analyzes various factors such as care staff's past work history, task completion status, client feedback, importance and urgency of each task, facility congestion, weather, traffic information, event information, urgent instructions from doctors, requests from families, nighttime accident history, staff health information, and shift change requests to prioritize and reschedule. Examples of prompts for the generation AI include: "Summarize all staff tasks for today with priority," "Generate reminder messages if there are incomplete tasks," and "Reorganize the schedule if there is a sudden change in a client's health."

[0083] Step 3: Generating optimal care content and rehabilitation proposals for each user. The Care Analysis Department uses a generation AI to automatically generate optimal care content and timing, rehabilitation suggestions, medication management, monitoring plans, emergency response measures, family support measures, and QOL improvement measures for each user, based on diverse data such as the user's health status, level of care required, presence or absence of dementia, medication status, rehabilitation history, dietary restrictions, allergy information, requests and instructions from family and doctors, nighttime behavior, past care history, fall and accident history, infection risk, lifestyle rhythm, hobbies and preferences, psychological state, sleep patterns, excretion patterns, food intake, water intake, pressure ulcer risk assessment, motor function assessment, cognitive function assessment, QOL indicators, feedback from family, and medical information reports from medical institutions. Examples of prompts to the generation AI include: "Suggest the necessary care content for this morning based on user A's health status and past care history," "Generate an optimal rehabilitation plan based on user B's dementia progression and lifestyle rhythm," "Extract points to note regarding medication management from user C's medication history and allergy information," and "Suggest recurrence prevention measures based on user D's fall accident history."

[0084] Step 4: Collection and summarization of the latest caregiving knowledge, laws, manuals, etc. The Information Gathering Department automatically collects and stores the latest care guidelines, legal revisions, infectious disease control measures, manual updates, new findings in rehabilitation methods, drug information, accident prevention warnings, the latest trends in care techniques, new dementia care methods, fall prevention measures, diet and nutrition management guidelines, family support measures, ICT utilization case studies, care fee revision information, subsidy and grant information, regional collaboration case studies, disaster response manuals, special response measures during infectious disease outbreaks, zoning guidelines in the event of an infection within a facility, behavioral and psychological symptom management measures for elderly people with dementia, the latest guidelines for pressure ulcer prevention, new product information on welfare equipment, care robot implementation case studies, telemedicine utilization case studies, and new function information for care record systems. This information is then extracted and summarized using AI generation to provide useful and necessary information to care staff and the Schedule Management Department and Care Analysis Department. Examples of prompts for the generating AI include: "Summarize the key points of the new care guidelines that will be applied from today," "Summarize the infectious disease outbreak response manual for on-site staff," "Extract information on the side effects of the new drug and summarize the precautions for medication management," and "Summarize the latest precautions for preventing falls for on-site staff."

[0085] Step 5: Communication support and information sharing The Communication Support Department manages necessary information sharing and work communication between care staff and doctors, nurses, rehabilitation therapists, family members, other care staff, managers, community comprehensive support centers, care managers, pharmacists, nutritionists, welfare equipment specialists, government officials, volunteers, and external lecturers. This includes confirming care policies, providing instructions for emergency response, sharing success stories and precautions, providing regular reports to family members, coordinating with medical institutions, responding to accidents and complaints, sharing know-how, adjusting shifts, providing training information, collaborating with local communities, establishing a disaster contact network, sharing information during infectious disease outbreaks, emergency contact during night shifts, requesting support during ICT problems, and reporting welfare equipment malfunctions. Using AI generation, it automatically organizes and summarizes multiple pieces of information and notifies and shares them with care staff and relevant parties at the appropriate time via their devices. Examples of prompts for the generating AI include: "Summarize today's key care needs and the reasons why, and notify all staff," "Generate a text explanation for families regarding medication change instructions from a doctor," "Summarize the response manual for nighttime falls and notify night shift staff," "Extract successful case studies from colleagues and summarize the points that should be shared on-site," and "Summarize the latest information on disaster evacuation plans and notify all staff."

[0086] Step 6: On-site operation and feedback using the terminal Care staff can intuitively perform a wide range of operations from their terminals, including checking schedules, viewing user information, obtaining the latest information, entering task progress, checking communication history, contacting doctors and family members, registering information via voice or image input, making inquiries via chatbot, automatically recording vital signs, recording care with photos and videos, identifying users with QR codes, managing medication with barcodes, monitoring with GPS tags, receiving evacuation orders during disasters, receiving zoning orders during infectious disease outbreaks, requesting support in case of ICT troubles, reporting malfunctions of welfare equipment, making emergency contacts during night shifts, watching training videos, and using a know-how sharing bulletin board. For example, it can respond to diverse on-site needs such as "recording user A's vital signs with voice input," "managing user B's medication with barcodes," "monitoring user C with GPS tags when they go out," "registering user D's care records with photos," "receiving evacuation orders in real time during disasters," and "making emergency contacts by voice during night shifts."

[0087] (Specific use cases)

[0088] For example, in a nursing care facility where multiple care staff work in shifts, and each staff member accesses this system from a terminal to begin their work, the Schedule Management Department retrieves each staff member's shift information, assigned residents, handover items from the previous day, facility event schedules, nighttime accident history, latest instructions from doctors, and requests from families from the Database Department. It then sends prompt messages to the Generating AI via the Generation AI Integration Department, such as "Summarize all tasks for today's daytime staff with priority," "Consider the nighttime accident history and extract key care items for the morning," and "Reorganize the schedule if there is a sudden change in a resident's condition." The AI ​​analyzes this information and automatically generates a detailed schedule that takes priorities and time allocation into consideration, such as "8:30: Measure vital signs for all users," "9:00: Change user A's position and provide pressure ulcer prevention care," "9:30: Assist user B with toileting," "10:00: Confirm user C's medication and provide hydration," "10:30: Walking training for user D," "11:00: Assist user E with bathing," "11:30: Prepare lunch," "12:00: Assist with meals," "13:00: Rehabilitation for user F," "14:00: Support user G in participating in recreational activities," "15:00: Check the care record system manual," "16:00: Regular report to family," and "17:00: Handover to night shift staff," and displays it on the terminal.

[0089] Furthermore, the Care Analysis Department comprehensively analyzes each user's health status, level of care required, presence or absence of dementia, medication status, rehabilitation history, dietary restrictions, allergy information, requests and instructions from family and doctors, nighttime behavior, past care history, fall / accident history, infection risk, lifestyle rhythm, hobbies and preferences, psychological state, sleep patterns, excretion patterns, food intake, water intake, pressure ulcer risk assessment, motor function assessment, cognitive function assessment, QOL indicators, feedback from family, and medical information reports from medical institutions. Through the Generation AI Collaboration Department, it then generates suggestions such as, "Based on user A's health status and past care history, propose the necessary care for this morning," and "Based on user B's dementia progression and lifestyle rhythm, propose the necessary care for this morning." The system sends prompts such as "Generate an appropriate rehabilitation plan," "Extract points to note regarding medication management from user C's medication history and allergy information," and "Propose recurrence prevention measures based on user D's fall accident history" to the AI. The AI ​​then automatically generates optimal care content and timing, rehabilitation suggestions, medication management, monitoring plans, and emergency response measures for each user, such as "Recommend changing user A's position every two hours and taking photographic records of their skin condition," "Focus on reminiscence therapy rehabilitation and supervision for user B in the mornings," "Utilize barcode authentication to prevent medication errors for user C," and "Record fall risk each time user D is undergoing walking training," and provides these plans to the schedule management department.

[0090] Furthermore, the Information Gathering Department collects the latest care guidelines, legal revisions, infectious disease control measures, manual updates, new findings in rehabilitation methods, drug information, accident prevention warnings, the latest trends in care techniques, new dementia care methods, fall prevention measures, diet and nutrition management guidelines, family support measures, ICT utilization examples, care fee revision information, subsidy and grant information, regional collaboration examples, disaster response manuals, special response measures during infectious disease outbreaks, zoning guidelines in the event of an infection within a facility, and other information disseminated from the Ministry of Health, Labour and Welfare, local governments, medical institutions, care-related organizations, academic societies, research institutions, pharmaceutical companies, care product manufacturers, insurance companies, family associations, community comprehensive support centers, ICT vendors, welfare equipment rental companies, etc. The system automatically collects and stores information such as behavioral and psychological symptom management strategies for elderly people with intellectual disabilities, the latest guidelines for pressure ulcer prevention, new product information on welfare equipment, case studies of care robot implementation, case studies of telemedicine utilization, and new function information for care record systems. Through the AI ​​generation and collaboration department, prompt messages such as "Summarize the key points of the new care guidelines that will be applied from today," "Summarize the response manual for infectious disease outbreaks for on-site staff," "Extract side effect information for new drugs and summarize the points to note regarding medication management," and "Summarize the latest points to note regarding fall prevention for on-site staff" are sent to the AI ​​generation department. This extracts and summarizes useful and necessary information for care staff and provides it to the schedule management department and the care analysis department.

[0091] Furthermore, the Communication Support Department facilitates necessary information sharing and operational communication between care staff and doctors, nurses, rehabilitation therapists, family members, other care staff, managers, community comprehensive support centers, care managers, pharmacists, nutritionists, welfare equipment specialists, government officials, volunteers, and external lecturers. This includes confirming care policies, providing instructions for emergency response, sharing success stories and precautions, regular reporting to family members, coordinating with medical institutions, handling accidents and complaints, sharing know-how, adjusting shifts, providing training information, collaborating with the community, establishing a disaster contact network, sharing information during infectious disease outbreaks, emergency contact during night shifts, and providing support during ICT problems. The system manages requests, reports of malfunctions of welfare equipment, and sends prompt messages to the AI ​​generation unit via the AI ​​generation unit. These prompts include "Summarize today's key care needs and the reasons why, and notify all staff," "Generate a document explaining medication change instructions from a doctor for family members," "Summarize the response manual for nighttime fall accidents and notify night shift staff," "Extract successful case studies from colleagues and summarize the points that should be shared on-site," and "Summarize the latest information on disaster evacuation plans and notify all staff." The system automatically organizes and summarizes multiple pieces of information and notifies and shares them with care staff and relevant parties at the appropriate time via their devices.

[0092] Thus, the system of the present invention utilizes generating AI at each step, from the start of care staff's work to individual care plans, the latest care knowledge and legal information, internal and external team communications, task progress, emergency response, coordination with families and medical institutions, accident and complaint handling, know-how sharing, disaster and infectious disease response, ICT trouble response, and welfare equipment management. It automatically provides real-time and optimal information, generates suggestions, summarizes, schedules, extracts data, notifies, and shares information in response to all work requests entered by care staff from their terminals. Specific examples of prompts to be fed into the generating AI include: "Summarize all tasks for the daytime staff today with priority," "Suggest necessary care for this morning based on user A's health condition and past care history," "Summarize the key points of the new care guidelines that will be applied from today," "Generate a document explaining the doctor's medication change instructions for family members," "Summarize the response manual for nighttime fall accidents and notify night shift staff," "Extract successful case studies from colleagues and summarize the points to be shared on-site," and "Summarize the latest information on disaster evacuation plans and notify all staff."

[0093] The specific processing unit 290 transmits the result of the specific processing obtained in the embodiment 1 or application example 1 described above to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0094] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0095] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0096] For example, the data collection unit is implemented by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing device 12. For example, the acquisition unit acquires step count data using the camera 42 and communication I / F 44 of the smart device 14 and processes it with the specific processing unit 290 of the data processing device 12. For example, the analysis unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the data from the data collection unit and the acquisition unit. For example, the generation unit is implemented by the specific processing unit 290 of the data processing device 12 and generates a cooking menu using generation AI. For example, the serving unit is implemented by the output device 40 of the smart device 14 or the specific processing unit 290 of the data processing device 12 and provides the generated cooking menu to the user. The correspondence between each unit and the devices and control units is not limited to the examples described above and can be modified in various ways.

[0097] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0098] [Second Embodiment]

[0099] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0100] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0101] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0102] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and communication interface 44 are also connected to the bus 52.

[0103] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0104] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0105] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0106] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0107] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0108] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0109] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the identification processing unit 290 using these models.

[0110] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. Each part of the system described below is realized by the data processing device 12 and the smart glasses 214. 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".

[0111] (Example 1)

[0112] Since the process flow is the same as in Example 1 described in the First Embodiment above, the explanation will be omitted.

[0113] (Application Example 1) Since the process flow is the same as in Application Example 1 described in the first embodiment above, the explanation will be omitted.

[0114] The specific processing unit 290 transmits the result of the specific processing obtained in the embodiment 1 or application example 1 described above to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0115] Furthermore, the processing by the data processing system 10 described above is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0116] For example, the data collection unit is implemented by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing device 12. For example, the acquisition unit acquires step count data using the camera 42 and communication I / F 44 of the smart glasses 214 and processes it using the specific processing unit 290 of the data processing device 12. For example, the analysis unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the data from the data collection unit and the acquisition unit. For example, the generation unit is implemented by the specific processing unit 290 of the data processing device 12 and generates a cooking menu using generation AI. For example, the serving unit is implemented by the speaker 240 of the smart glasses 214 or the specific processing unit 290 of the data processing device 12 and provides the generated cooking menu to the user. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0117] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0118] [Third Embodiment]

[0119] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0120] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0121] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0122] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, display 343, and communication interface 44 are also connected to the bus 52.

[0123] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0124] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0125] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0126] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0127] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0128] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0129] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0130] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. Each part of the system described below is implemented by the data processing device 12 and the headset terminal 314. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0131] (Example 1) Since the process flow is the same as in Example 1 described in the First Embodiment above, the explanation will be omitted.

[0132] (Application Example 1) Since the process flow is the same as in Application Example 1 described in the first embodiment above, the explanation will be omitted.

[0133] The specific processing unit 290 transmits the result of the specific processing obtained in the embodiment 1 or application example 1 described above to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0134] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0135] For example, the data collection unit is implemented by the control unit 46A of the headset terminal 314 or the specific processing unit 290 of the data processing device 12. For example, the acquisition unit acquires step count data using the camera 42 and communication I / F 44 of the headset terminal 314 and processes it using the specific processing unit 290 of the data processing device 12. For example, the analysis unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the data from the data collection unit and the acquisition unit. For example, the generation unit is implemented by the specific processing unit 290 of the data processing device 12 and generates a cooking menu using generation AI. For example, the serving unit is implemented by the speaker 240 and display 343 of the headset terminal 314 or the specific processing unit 290 of the data processing device 12 and provides the generated cooking menu to the user. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0136] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0137] [Fourth Embodiment]

[0138] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0139] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0140] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0141] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, controlled object 443, and communication interface 44 are also connected to the bus 52.

[0142] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0143] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0144] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0145] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0146] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0147] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0148] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0149] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0150] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. Each part of the system described below is implemented by the data processing device 12 and the robot 414. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0151] (Example 1) Since the process flow is the same as in Example 1 described in the First Embodiment above, the explanation will be omitted.

[0152] (Application Example 1) Since the process flow is the same as in Application Example 1 described in the first embodiment above, the explanation will be omitted.

[0153] The specific processing unit 290 transmits the result of the specific processing obtained in the embodiment 1 or application example 1 described above to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0154] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or external devices, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or external devices.

[0155] For example, the data collection unit is implemented by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing device 12. For example, the acquisition unit acquires step count data using the camera 42 and communication I / F 44 of the robot 414 and processes it using the specific processing unit 290 of the data processing device 12. For example, the analysis unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the data from the data collection unit and the acquisition unit. For example, the generation unit is implemented by the specific processing unit 290 of the data processing device 12 and generates a cooking menu using a generation AI. For example, the serving unit is implemented by the speaker 240 and controlled object 443 of the robot 414 and the specific processing unit 290 of the data processing device 12 and provides the generated cooking menu to the user. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0156] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0157] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0158] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0159] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0160] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0161] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0162] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0163] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0164] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0165] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0166] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0167] 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.

[0168] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0169] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using this memory.

[0170] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0171] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0172] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0173] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0174] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0175] Furthermore, the following additional information is disclosed regarding the above explanation.

[0176] (Claim 1)

[0177] This caregiving support system comprises a Schedule Management Department, a Care Analysis Department, an Information Gathering Department, and a Communication Support Department. The Schedule Management Department centrally manages information such as each care staff member's work schedule, remaining tasks, recommended actions, progress status, priority, urgency, required time, assigned users, and related medical institutions, and integrates information from other departments to present in real time "when" and "what" care staff should do. The Care Analysis Department analyzes diverse data such as each user's health status, care level, presence or absence of dementia, medication status, rehabilitation history, dietary restrictions, allergy information, requests and instructions from family and doctors, vital signs, nighttime condition, and past care history, and automatically generates optimal care content and timing, rehabilitation suggestions, medication management, and monitoring plans for each user using a generative AI. This caregiving support system features a schedule management department that provides information, an information gathering department that automatically collects the latest care guidelines, legal revisions, infectious disease control measures, manual updates, new findings on rehabilitation methods, drug information, and accident prevention warnings from the Ministry of Health, Labour and Welfare, local governments, medical institutions, and care-related organizations, and uses generative AI to summarize and organize the information needed on-site and provide it to the schedule management department, and a communication support department that facilitates necessary information sharing, work communication, confirmation of care policies, instructions for emergency response, and sharing of success stories and precautions among doctors, nurses, rehabilitation staff, family members, and other care staff, and uses generative AI to optimize information transmission, summarization, and notifications. These departments work together to improve the efficiency of care staff's work and the quality of care for users. (Claim 2)

[0178] The system according to claim 1, characterized in that the Care Analysis Department uses generative AI to analyze diverse data such as each user's health status, level of care required, presence or absence of dementia, medication status, rehabilitation history, dietary restrictions, allergy information, requests and instructions from family and doctors, vital signs, nighttime condition, and past care history, and automatically generates optimal care content and timing, rehabilitation suggestions, medication management, monitoring plans, emergency response measures, etc. for each user, and provides this content to the Schedule Management Department in real time. (Claim 3)

[0179] The system according to claim 1 is characterized in that the Communication Support Department automatically organizes and summarizes necessary information sharing, work communication, confirmation of care policies, emergency response instructions, and sharing of success stories and precautions among doctors, nurses, rehabilitation therapists, family members, and other care staff using generative AI, and notifies and shares this information with care staff and relevant parties at the appropriate time, thereby facilitating information transmission and collaboration both within and outside the team. [Explanation of symbols]

[0180] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. A sales support system comprising a Schedule Management Department, a Customer Analysis Department, an Information Gathering Department, and a Communication Support Department, wherein the Schedule Management Department manages sales staff's work schedules, remaining tasks, and various recommended actions in chronological order, and integrates information from other departments to provide sales staff with real-time information on "when" and "what" they should do; the Customer Analysis Department analyzes information such as each customer's attributes, past purchase history, and interests, and automatically generates optimal product and service proposals for each customer using generative AI, and provides these proposals to the Schedule Management Department; the Information Gathering Department collects the latest product information, campaign information, and business-related information from internal and external sources, organizes the information using generative AI so that sales staff can check it at the necessary time, and provides it to the Schedule Management Department; and the Communication Support Department promotes the sharing of information such as business communications, goals, and meeting schedules between sales staff and their superiors and colleagues, and optimizes information transmission using generative AI so that sales staff can appropriately grasp the necessary information within the team, thereby achieving improved work efficiency and maximizing the performance of sales staff.

2. The system according to claim 1, characterized in that the Schedule Management Department integrates optimal proposal information for each customer and the latest product and campaign information received from the Customer Analysis Department and the Information Gathering Department, combines this with the salesperson's work schedule and remaining tasks, and automatically generates a specific action plan that the salesperson should prioritize at the current time using a generative AI, and presents it to the salesperson in real time.

3. The system according to claim 1, characterized in that the Communication Support Department automatically organizes and summarizes information such as business communications, goals, meeting schedules, and progress status that should be shared between sales staff and their superiors and colleagues, using a generative AI, and notifies and shares this information with sales staff and relevant parties at an appropriate time, thereby facilitating information transmission and collaboration within the team.

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