system

Abstract

We provide the system. [Solution] An input method for entering user business information, An analysis means for analyzing the aforementioned business information using location data and artificial intelligence technology, Based on the aforementioned analysis results, a proposal means is provided to suggest the most suitable way for the user to utilize generative artificial intelligence, A means for responding to questions and inquiries that arise from the user based on the above proposal, A scheduling mechanism for scheduling and conducting regular follow-up sessions, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Although the utilization of generative artificial intelligence (AI) in enterprises is advancing, there is a problem that the application method is unclear and sufficient effects have not been obtained. In particular, it is difficult to find a specific AI utilization method based on individual business information in various operations, and business efficiency improvement and new service creation do not progress as expected. Furthermore, there is also a problem that it is difficult for employees with insufficient AI knowledge to understand and implement the proposed methods.

Means for Solving the Problems

[0005] This invention includes an input means for inputting user business information, a proposal means for analyzing business information using location data and artificial intelligence technology, and proposing the optimal AI utilization method based on the analysis results. Furthermore, it includes a response means for responding to questions and consultations based on the proposal, and a scheduling means for conducting regular follow-up sessions, thereby enabling users to easily implement AI solutions suited to their work, supporting improved work efficiency and the creation of new revenue streams.

[0006] A "user" is an entity that uses this system to input business information and receive suggestions.

[0007] "Business information" refers to information about the user's work content, activity status, and usage of the generated AI.

[0008] "Input means" refers to an interface or function that allows a user to input business information into a system.

[0009] "Location data" refers to data about a user's physical location and activity history.

[0010] "Artificial intelligence technology" refers to AI algorithms and models used for data analysis and recognition of business patterns.

[0011] "Analysis tools" refer to a function that uses AI technology to perform analysis based on business information and location data.

[0012] The "suggestion method" is a function that presents AI utilization methods tailored to the user, derived from the analysis results.

[0013] A "response mechanism" is a function that provides appropriate answers to questions and inquiries from users.

[0014] "Scheduling means" refers to the function of planning and conducting regular follow-up sessions.

[0015] The "Follow-up Session" is an interview for checking the user's AI utilization status and providing further guidance and advice.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiment for Carrying Out the Invention

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

[0018] 2]]First, the terms used in the following description will be explained.

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

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

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

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

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

[0027] 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).

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

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0031] 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.

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

[0033] 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.

[0034] 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.

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

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

[0037] This invention provides an interactive counseling system aimed at improving user work efficiency and optimizing AI utilization. This system collects user work information, utilizes location data and AI technology to propose appropriate AI usage methods, and provides follow-up support to optimize business processes.

[0038] System Overview

[0039] User: Accesses the system using their own device via a dedicated application or web interface. They input business information and current AI usage status to receive suggestions on how to utilize AI.

[0040] Terminal: Receives input from the user and sends it to the server. Displays suggestions and feedback to the user, supporting interactive dialogue.

[0041] Server: Processes user business information and analyzes it using location data and AI technology. Based on the analysis results, it proposes a suitable method for using generative AI for the user. It also provides appropriate responses to user inquiries. It plans regular follow-up sessions to continuously support the user's use of AI.

[0042] Specific example

[0043] For sales users: Users input information about their daily visits and sales routes via their devices. The server uses location data and AI analysis technology to optimize visit routes and suggest target locations. These suggestions are based on past visit effectiveness and potential for new business development. Based on user feedback, the server provides an even more optimized sales strategy.

[0044] For marketing users: Users input marketing campaign data and customer target information into their terminals. The server analyzes this information using AI technology and suggests effective campaign messages and methods. Throughout this process, the success rate of campaigns is continuously tracked, and improvement strategies for the next campaign are suggested.

[0045] In this way, this system promotes the use of generative artificial intelligence in users' work and improves operational efficiency by providing detailed consulting.

[0046] The following describes the processing flow.

[0047] Step 1:

[0048] The user accesses the system from their device and enters their authentication information on the login screen. The device sends this authentication information to the server, which verifies the user's authentication information against its database and authenticates them.

[0049] Step 2:

[0050] The user inputs necessary information into the terminal, such as their work details, usage of generated AI, and location data. The terminal then sends the collected information to the server.

[0051] Step 3:

[0052] Based on the received business information, the server analyzes the user's work situation using location data and AI technology. This allows for the extraction of work patterns and the calculation of potential improvements for efficiency.

[0053] Step 4:

[0054] Based on the analysis results, the server determines the optimal way for the user to utilize the generated AI. The suggestions include specific tools, procedures, and improvement measures. The server then sends these suggestions to the user's device.

[0055] Step 5:

[0056] The terminal displays the proposal to the user, allowing the user to review it. The user can also input questions and feedback about the proposal into the terminal.

[0057] Step 6:

[0058] The server receives questions and inquiries from users, prepares appropriate answers, and sends them back to the terminal. This allows users to resolve any uncertainties and prepare to implement their suggestions.

[0059] Step 7:

[0060] The server schedules regular follow-up sessions and notifies the user via their terminal. During these sessions, the user can review the latest work status and progress of their AI-generated content, and receive additional advice.

[0061] (Example 1)

[0062] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0063] In today's business environment, many users seek to streamline and optimize their business processes, but the solutions offered are generally not personalized and therefore fail to adequately address their specific needs. Furthermore, existing systems lack the ability to effectively gather user feedback and provide continuous improvement and follow-up based on that feedback. As a result, it is extremely difficult for users to find the optimal way to utilize generative artificial intelligence.

[0064] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0065] In this invention, the server includes an input means for users to input business-related information via a terminal, a transmission means for transferring the input information to the server using a secure protocol, and an analysis means for analyzing the business information using a location information database and a generative artificial intelligence model. This makes it possible to present users with personalized methods for using generative AI and then continuously optimize it based on feedback.

[0066] "Input means" refers to a function or device that allows a user to input work-related information into a terminal.

[0067] "Transmission means" refers to a function that includes a method or protocol for securely transferring input information from a terminal to a server.

[0068] "Analysis means" refers to a function or device for analyzing business information received from users using a location information database and a generative artificial intelligence model.

[0069] "Proposed means" refers to a function or device that presents the user with the optimal way to use the generative artificial intelligence based on the analysis results obtained by the analysis means.

[0070] "Scheduling means" refers to a function or device for planning and executing follow-up sessions based on user feedback information.

[0071] "Storage means" refers to a function or device for recording the details of tasks entered by the user on a terminal and saving them to a database.

[0072] A "generative AI model" refers to AI technology that uses user business information to analyze and propose available generative artificial intelligence techniques.

[0073] This invention is an interactive support system designed to improve the efficiency of users' work. This system consists of a user, a terminal, and a server, and proposes various methods for utilizing user-optimized generative AI.

[0074] First, the user enters their work-related information through a terminal. The terminal then uses a dedicated application or web interface to transmit the collected information to the server using a secure protocol (e.g., SSL / TLS). The information entered includes the user's sales activity information and marketing campaign data, which are recorded in detail according to the characteristics of the work.

[0075] The server uses a location database and a generative AI model to process information received from the terminal. Existing AI frameworks (e.g., TENSORFLOW®, PyTorch) can be used as the generative AI model. The server analyzes business information and proposes an AI usage method suitable for the user.

[0076] This proposal is based on the user's past information and AI-generated predictions, specifically suggesting optimal sales routes and effective marketing messages. For example, it suggests efficient routes for sales professionals and optimal campaign strategies tailored to customer segments for marketing professionals. This maximizes the capabilities of generative AI and significantly improves the efficiency of business processes.

[0077] Examples of prompts include, "Optimize the visit route based on the visit data for your sales route," and "Analyze the new customer acquisition campaign data to suggest an effective message." Based on these prompts, the system provides the user with specific and practical advice.

[0078] This invention is a system that provides a concrete and implementable solution to improve operational efficiency by promoting the use of generative artificial intelligence tailored to user needs.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] Users use their devices to input work-related information. Specifically, sales staff might input the address and date of their visits, while marketing staff might input campaign details and target customer attributes. This information is temporarily stored on the device as the user's work profile.

[0082] Step 2:

[0083] The terminal uses a secure protocol (e.g., SSL / TLS) to transfer user-entered business information to the server. The input data is converted into geographical information and marketing data formats before being transmitted. Encryption is applied during this process to maintain data integrity and confidentiality.

[0084] Step 3:

[0085] The server uses a location database and a generative AI model to analyze the received business information. First, the server extracts optimal route patterns from the database based on the user's location. Then, it utilizes the generative AI model to analyze efficient visit plans and campaign strategies. Here, predictions and recommendations are made by comparing past data with the current situation.

[0086] Step 4:

[0087] The server generates suggestions for the user based on the analysis results. For sales personnel, it provides suggestions such as the order of visits and potential new clients; for marketing personnel, it provides specific guidance on the optimal timing for messages and campaigns. These suggestions are sent from the server to the terminal.

[0088] Step 5:

[0089] The terminal displays the suggestions received from the server to the user. The user reviews the suggestions and evaluates their feasibility. Furthermore, the user enters feedback into the terminal and sends it to the server. This feedback helps determine the value of the suggestions and improve future suggestions.

[0090] Step 6:

[0091] The server analyzes user feedback and schedules follow-up sessions, which include regular check-ins and preparation of new suggestions. It also refines the AI ​​model based on the feedback, improving the quality of future suggestions. This collaboration continuously improves the user's work efficiency.

[0092] (Application Example 1)

[0093] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0094] In modern business, improving operational efficiency and enhancing security are critical challenges, but finding the right way to utilize artificial intelligence to achieve both simultaneously is difficult. Therefore, users struggle with the appropriate implementation of AI and the continuous improvement of security measures. Against this backdrop, there is a demand for effective solutions that optimize operational efficiency while reducing security risks.

[0095] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0096] In this invention, the server includes information receiving means, data processing means, strategy presentation means, dialogue means, planning means, and improvement means. This enables the proposal of optimal AI usage methods based on business information and continuous improvement of security measures.

[0097] "Information receiving means" refers to the means of receiving business information and feedback from users and collecting it as data.

[0098] "Data processing means" refers to methods for analyzing collected business information and location data to derive appropriate ways to utilize AI.

[0099] A "strategy presentation tool" is a means of proposing AI utilization methods and security measures to users based on the analysis results obtained from data processing tools.

[0100] A "dialogue method" is a means of engaging in dialogue with users in response to their questions and inquiries, and providing them with the necessary information and support.

[0101] "Planning methods" refer to the means of regularly scheduling follow-up sessions to continuously support users' use of AI.

[0102] "Improvement measures" refer to methods for continuously improving and optimizing proposed security measures based on user feedback.

[0103] In this invention, to realize the application example, the server receives business information and feedback from the user using information receiving means. This information is entered by the user through a terminal and stored in data storage means. Subsequently, the server uses data processing means to process the collected location data and business information with AI technology and analyze the optimal way to utilize AI. This analysis utilizes generative AI models and employs software such as TensorFlow or PyTorch. The server also utilizes location information services such as Google® Maps API to identify efficient routes and risks.

[0104] Based on the analysis results, the server proposes AI utilization methods and security measures to the user through strategic proposal tools. Users can receive these proposals via their smartphones and send appropriate feedback. The dialogue tools answer user questions and provide support as the user takes action based on the proposals.

[0105] For example, if a company needs to strengthen its security, the server will analyze data to determine that improvements to internal network management are necessary. Based on this, the strategic proposal tool will suggest specific measures, which the user can then implement.

[0106] As a follow-up, regular sessions are scheduled using planning tools. This ensures that users always receive the latest suggestions, and continuous optimization of security measures is achieved through improvement tools based on their feedback.

[0107] Examples of specific prompt messages include the following:

[0108] User information: {location: 'Office location', incidents: 'Past data breach incidents'}

[0109] Business content: {type: 'IT company', size: '100 people'}

[0110] Please propose the necessary security measures.

[0111] In this way, a system is realized that improves operational efficiency and security.

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] Users input data about their work information and current security status using a terminal. This input includes location information and information about past security incidents. The terminal sends this data to a server, which stores it in a data storage system.

[0115] Step 2:

[0116] The server analyzes the received data using data processing tools. It processes the input data through an AI model and uses the Google Maps API to process location information. This optimizes business processes and identifies potential security risks. The output generates a list of optimized AI applications and suggested security measures.

[0117] Step 3:

[0118] The server notifies the user of suggestions based on the analysis results through a strategic presentation system. These suggestions include specific ways to utilize AI and measures to improve security. The user reviews the suggestions on their device and selects the measures they deem necessary.

[0119] Step 4:

[0120] Users send questions and inquiries based on suggestions to the server using a dialogue mechanism. The server then uses a generative AI model to generate corresponding answers, which are provided to the user in real time.

[0121] Step 5:

[0122] The server uses planning tools to schedule regular follow-up sessions. This allows users to continue receiving new suggestions regularly. User feedback is collected through improvement tools and reflected in future suggestions.

[0123] This series of steps will lead to improved operational efficiency and enhanced security.

[0124] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0125] This invention proposes a system that combines business information and emotion recognition technology to provide users with the most optimal way to utilize generative artificial intelligence (AI). This system enables improved work efficiency for users and flexible consulting based on their individual emotional states.

[0126] System Overview

[0127] User: Inputs business information from their own device and receives suggestions for AI utilization. During this process, the emotion engine analyzes the user's facial expressions and tone of voice, and sends the emotional state to the server.

[0128] Terminal: Collects user input information and sends it to the server. Displays suggested content and collects sentiment-based feedback. Also provides users with information about follow-up sessions.

[0129] Server: Analyzes received business information and emotional data using location data and AI technology. Calculates flexible AI application methods tailored to the user's emotional state and proposes them to the user. It also generates and sends emotionally appropriate responses to the terminal. Follow-up sessions are planned at the optimal timing, taking the user's emotional state into consideration.

[0130] Specific example

[0131] For sales users: When a user starts a new sales campaign, they input business information into their terminal. Based on this information, the server proposes strategies using AI. If the user expresses anxiety or concern, the emotion engine identifies it, and the server provides detailed, emotionally sensitive explanations and reassuring responses.

[0132] For managers: When they input project progress data, the server provides project management optimization suggestions that take into account the emotional state of team members. If the emotion engine determines that the user is stressed, it adjusts the difficulty of the suggestions or recommends stress reduction measures.

[0133] This invention aims to provide more refined services than before by incorporating emotion recognition, thereby supporting the user's work environment and improving the quality of work.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] The user accesses the system from their device, enters their authentication information, and logs in. The device sends this information to the server, which then performs authentication.

[0137] Step 2:

[0138] The user inputs their work information and current AI usage status, and the device sends this information to the server. Simultaneously, the device uses an emotion engine to analyze the user's facial expressions and voice, and extracts emotional data.

[0139] Step 3:

[0140] The device sends user emotion data to the server. The server combines the received work information with the emotion data and performs a detailed analysis using location data and AI technology.

[0141] Step 4:

[0142] Based on the analysis results, the server determines the optimal way to utilize AI, adapted to the user's work situation and emotional state. This suggestion will take into account the user's current emotions.

[0143] Step 5:

[0144] The server sends the suggestions to the terminal, which then displays them to the user. The user can view the suggestions and provide emotionally appropriate questions and feedback through the terminal.

[0145] Step 6:

[0146] The server receives a question from the user, generates a response with adjusted tone and content based on sentiment data obtained by the sentiment engine, and sends it back to the terminal.

[0147] Step 7:

[0148] The server schedules regular follow-up sessions, taking into account the user's emotional state and work information. The terminal notifies the user of this schedule, ensuring that follow-ups are conducted at the optimal time.

[0149] (Example 2)

[0150] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0151] In today's business environment, simply analyzing business information is insufficient to improve the work efficiency of individual users. It is especially important to provide appropriate advice and suggestions while appropriately considering the user's emotional state. However, conventional systems lack the means to fully understand user emotions and provide optimal suggestions and follow-up accordingly. Therefore, there is a need to propose a method of utilizing individually optimized generative artificial intelligence that simultaneously considers both the user's business information and emotional state.

[0152] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0153] In this invention, the server includes means for inputting user business information via a terminal and acquiring user emotional data along with the business information; means for analyzing the business information and emotional data using location information data and generative AI technology; and means for proposing an optimal method of utilizing generative artificial intelligence that takes into account the user's emotional state based on the analysis results. This makes it possible to provide a flexible and effective method of utilizing AI that reflects the user's emotional state.

[0154] "User's work information" refers to detailed information related to the work the user is currently involved in, and specifically includes project progress, goals, and task details.

[0155] "Emotional data" refers to information obtained from a user's facial expressions and voice, and it indicates the user's psychological state and emotional tendencies.

[0156] "Generative AI technology" is an artificial intelligence technology that generates natural language text based on diverse input data, and is used to generate suggestions and responses for users.

[0157] "Analysis" is the process of using computer models to analyze collected business information and emotional data and derive meaningful results.

[0158] "Proposal methods" refer to methods and processes for presenting users with the most suitable applications and solutions based on analysis results.

[0159] A "follow-up session" is a regularly scheduled session that provides feedback and support as part of ongoing communication with the user.

[0160] "Scheduling" is the process of planning events or tasks and allocating time to carry them out at specific times.

[0161] This system uses a generative AI model to provide optimal suggestions based on the user's business information and sentiment data. The system operates according to the following procedure.

[0162] First, the user inputs work information using their own device. This device is equipped with input devices such as a camera and microphone, and emotional data is acquired by recording the user's facial expressions and voice. This data is then transmitted to the server by the device.

[0163] Next, the server processes the received business information and sentiment data for analysis. This analysis uses a generative AI model, specifically a combination of natural language processing tools and machine learning frameworks. For example, libraries such as TensorFlow are used for natural language processing to understand and analyze the user's input information.

[0164] Based on the analysis results, the server generates optimal AI usage suggestions tailored to the user's emotional state. These suggestions include adjustments to fit the user's current psychological state and provide specific procedures and guides to improve work efficiency.

[0165] For example, if sentiment analysis reveals that a sales user is feeling anxious about launching a new campaign, along with receiving business-related information, the server will propose an AI-powered strategy designed to reassure them. Furthermore, follow-up sessions will be scheduled considering the sentiment data, ensuring the user is re-engaged at the optimal time.

[0166] An example of a prompt message would be, "Please tell me the best way to use AI to make our new sales campaign a success. Also, I'm feeling anxious; how should I address this?" This allows the user to receive concrete suggestions.

[0167] In this way, the system comprehensively considers the user's emotional state and business information, providing flexible and effective AI-powered business support.

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] Users use their own devices to input work-related information. This information includes project progress and task details. While the entered work information is temporarily stored on the device, the device's camera and microphone record the user's facial expressions and voice, acquiring this as emotional data.

[0171] Step 2:

[0172] The terminal transmits acquired business information and emotional data to the server. During this process, the business information and emotional data are organized into an appropriate format and transmitted to the server via the network in an encrypted form. The input here is business information and emotional data, and the output is the secure transmission of data to the server.

[0173] Step 3:

[0174] The server analyzes received business information and emotional data. This analysis utilizes a generative AI model to generate suggestions that match the user's needs and state based on the data. The generative AI model processes the input information and outputs insights into the user's emotional state and suggestions for improving work efficiency.

[0175] Step 4:

[0176] Based on the server-generated suggestions, the system proposes the most suitable AI application methods for the user. These suggestions are tailored to the user's psychological state and include specific procedures and tool guidelines. The input is the analysis results, and the output is the user-oriented suggestions.

[0177] Step 5:

[0178] The terminal presents suggestions sent from the server to the user. It not only displays the suggestions on the screen but also provides audio explanations as needed. Furthermore, it offers an interface for the user to input additional feedback. The output consists of optimized suggestion presentations and interaction features.

[0179] Step 6:

[0180] Users can provide feedback on the suggestions they receive. This feedback will be used to improve future analyses and the content provided. The input is user feedback information.

[0181] Step 7:

[0182] Based on the feedback, the server plans a follow-up session and notifies the user of the appointment at the optimal time. This notification is sent via the terminal, and the most suitable time is selected based on the user's status and schedule. The output is a notification of the scheduled follow-up session.

[0183] (Application Example 2)

[0184] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0185] Providing flexible support based on individual emotional states while improving users' work efficiency is not easy. In particular, in face-to-face service provision, there is a lack of concrete guidelines and technologies when it is necessary to quickly understand the customer's emotions and respond accordingly. This invention aims to solve these problems and propose an optimal method of utilizing AI that is tailored to emotions.

[0186] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0187] In this invention, the server includes acquisition means for inputting user business information, analysis means for analyzing the business information using location information data and computer technology, and emotion analysis means for analyzing the user's facial expressions and voice characteristics and generating responses according to their emotional state. This allows for the proposal of the optimal AI utilization method to the user in accordance with their emotional state, and enables flexible adjustments.

[0188] "Acquisition method" refers to an interface for collecting business information from users.

[0189] "Analysis methods" refer to mechanisms that process acquired business information using location data and computer technology to evaluate the trends and usefulness of the information.

[0190] The "proposal method" is a system that, based on the analysis results, derives the optimal way for the user to use the generated artificial intelligence.

[0191] "Emotional analysis means" refers to technology that analyzes a user's facial expressions and voice data to understand their emotional state and generate an appropriate response.

[0192] A "response system" is a system designed to provide appropriate answers to user questions and concerns.

[0193] "Scheduling means" refers to the function for planning and executing follow-up sessions.

[0194] This invention is a system that combines emotion recognition technology with business information analysis to propose the optimal way for users to utilize generative artificial intelligence. The following describes the specific configuration and implementation method of the system for realizing this application example.

[0195] The server acquires business information via terminals accessed by users. This business information includes the user's job description, work processes, and past performance data. Based on this information, the server performs data analysis using computer technology. This analysis utilizes a high-performance processor as hardware, and a database management system and machine learning libraries (e.g., TensorFlow and PyTorch) as software.

[0196] In the emotion analysis system, the server collects the user's facial expressions and voice data, which are then analyzed by an emotion recognition engine. Specifically, data is acquired through a camera and microphone, and real-time analysis is performed using image recognition software algorithms (e.g., OpenCV). This analysis determines the user's emotional state (e.g., anxiety, joy, interest).

[0197] User suggestions are based on both emotional state and business information analysis. The suggestion method utilizes a generative AI model to provide user-appropriate advice and action plans. This generative AI model integrates existing data with real-time emotional input to derive the most effective approach.

[0198] As a concrete example, consider the case where this system is implemented in a physical store in Japan. Store employees wear smart glasses and analyze the facial expressions and tone of voice of visiting customers to adjust the optimal customer service approach on the spot. An example of a prompt message would be, "As the customer approaches, we observe the changes in their facial expression through the smart glasses. We evaluate their emotions based on their facial expression and voice and customize the customer service strategy." As a result, it is expected that the customer experience will improve and the store's sales efficiency will increase.

[0199] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0200] Step 1:

[0201] The terminal retrieves work information from the user. It receives job description and work process information provided by the user as input and sends it to the server as a data file.

[0202] Step 2:

[0203] The server performs data analysis using the acquired business information. It utilizes computer technology based on location data and past performance data to analyze this data. As a result of this analysis, foundational data for optimizing the user's business operations is generated.

[0204] Step 3:

[0205] The device collects the user's facial expressions and voice data. This data is acquired through cameras and microphones built into smart glasses or mobile devices and transmitted to a server in real time.

[0206] Step 4:

[0207] The server processes the received facial and audio data using an emotion analysis engine. Using image recognition software such as OpenCV, it classifies the user's emotional state in real time. The output of this process is the specific emotional state expressed by the user (e.g., anxiety, interest, joy).

[0208] Step 5:

[0209] The server integrates the results of analyzing emotional states and business information, and uses suggestion tools to generate appropriate methods for utilizing generative artificial intelligence. It leverages generative AI models to create user-optimized suggestions. These suggestions can lead to improved business efficiency and new strategic proposals.

[0210] Step 6:

[0211] The terminal provides the user with the generated suggestions. By receiving the suggestions and confirming the necessary actions, the user can improve their workflow. Further responses can be obtained by the user inputting any questions they may have during this process.

[0212] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0213] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0214] 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.

[0215] [Second Embodiment]

[0216] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0217] 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.

[0218] 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).

[0219] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0220] 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.

[0221] 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).

[0222] 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.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0228] This invention provides an interactive counseling system aimed at improving user work efficiency and optimizing AI utilization. This system collects user work information, utilizes location data and AI technology to propose appropriate AI usage methods, and provides follow-up support to optimize business processes.

[0229] System Overview

[0230] User: Accesses the system using their own device via a dedicated application or web interface. They input business information and current AI usage status to receive suggestions on how to utilize AI.

[0231] Terminal: Receives input from the user and sends it to the server. Displays suggestions and feedback to the user, supporting interactive dialogue.

[0232] Server: Processes user business information and analyzes it using location data and AI technology. Based on the analysis results, it proposes a suitable method for using generative AI for the user. It also provides appropriate responses to user inquiries. It plans regular follow-up sessions to continuously support the user's use of AI.

[0233] Specific example

[0234] For sales users: Users input information about their daily visits and sales routes via their devices. The server uses location data and AI analysis technology to optimize visit routes and suggest target locations. These suggestions are based on past visit effectiveness and potential for new business development. Based on user feedback, the server provides an even more optimized sales strategy.

[0235] For marketing users: Users input marketing campaign data and customer target information into their terminals. The server analyzes this information using AI technology and suggests effective campaign messages and methods. Throughout this process, the success rate of campaigns is continuously tracked, and improvement strategies for the next campaign are suggested.

[0236] In this way, this system promotes the use of generative artificial intelligence in users' work and improves operational efficiency by providing detailed consulting.

[0237] The following describes the processing flow.

[0238] Step 1:

[0239] The user accesses the system from their device and enters their authentication information on the login screen. The device sends this authentication information to the server, which verifies the user's authentication information against its database and authenticates them.

[0240] Step 2:

[0241] The user inputs necessary information into the terminal, such as their work details, usage of generated AI, and location data. The terminal then sends the collected information to the server.

[0242] Step 3:

[0243] Based on the received business information, the server analyzes the user's work situation using location data and AI technology. This allows for the extraction of work patterns and the calculation of potential improvements for efficiency.

[0244] Step 4:

[0245] Based on the analysis results, the server determines the optimal way for the user to utilize the generated AI. The suggestions include specific tools, procedures, and improvement measures. The server then sends these suggestions to the user's device.

[0246] Step 5:

[0247] The terminal displays the proposal to the user, allowing the user to review it. The user can also input questions and feedback about the proposal into the terminal.

[0248] Step 6:

[0249] The server receives questions and inquiries from users, prepares appropriate answers, and sends them back to the terminal. This allows users to resolve any uncertainties and prepare to implement their suggestions.

[0250] Step 7:

[0251] The server schedules regular follow-up sessions and notifies the user via their terminal. During these sessions, the user can review the latest work status and progress of their AI-generated content, and receive additional advice.

[0252] (Example 1)

[0253] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0254] In today's business environment, many users seek to streamline and optimize their business processes, but the solutions offered are generally not personalized and therefore fail to adequately address their specific needs. Furthermore, existing systems lack the ability to effectively gather user feedback and provide continuous improvement and follow-up based on that feedback. As a result, it is extremely difficult for users to find the optimal way to utilize generative artificial intelligence.

[0255] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0256] In this invention, the server includes an input means for users to input business-related information via a terminal, a transmission means for transferring the input information to the server using a secure protocol, and an analysis means for analyzing the business information using a location information database and a generative artificial intelligence model. This makes it possible to present users with personalized methods for using generative AI and then continuously optimize it based on feedback.

[0257] "Input means" refers to a function or device that allows a user to input work-related information into a terminal.

[0258] "Transmission means" refers to a function that includes a method or protocol for securely transferring input information from a terminal to a server.

[0259] "Analysis means" refers to a function or device for analyzing business information received from users using a location information database and a generative artificial intelligence model.

[0260] "Proposed means" refers to a function or device that presents the user with the optimal way to use the generative artificial intelligence based on the analysis results obtained by the analysis means.

[0261] "Scheduling means" refers to a function or device for planning and executing follow-up sessions based on user feedback information.

[0262] "Storage means" refers to a function or device for recording the details of tasks entered by the user on a terminal and saving them to a database.

[0263] A "generative AI model" refers to AI technology that uses user business information to analyze and propose available generative artificial intelligence techniques.

[0264] This invention is an interactive support system designed to improve the efficiency of users' work. This system consists of a user, a terminal, and a server, and proposes various methods for utilizing user-optimized generative AI.

[0265] First, the user enters their work-related information through a terminal. The terminal then uses a dedicated application or web interface to transmit the collected information to the server using a secure protocol (e.g., SSL / TLS). The information entered includes the user's sales activity information and marketing campaign data, which are recorded in detail according to the characteristics of the work.

[0266] The server uses a location database and a generative AI model to process information received from the terminal. Existing AI frameworks (e.g., TensorFlow, PyTorch) can be used as the generative AI model. The server analyzes business information and proposes an appropriate AI usage method for the user.

[0267] This proposal is based on the user's past information and AI-generated predictions, specifically suggesting optimal sales routes and effective marketing messages. For example, it suggests efficient routes for sales professionals and optimal campaign strategies tailored to customer segments for marketing professionals. This maximizes the capabilities of generative AI and significantly improves the efficiency of business processes.

[0268] Examples of prompts include, "Optimize the visit route based on the visit data for your sales route," and "Analyze the new customer acquisition campaign data to suggest an effective message." Based on these prompts, the system provides the user with specific and practical advice.

[0269] This invention is a system that provides a concrete and implementable solution to improve operational efficiency by promoting the use of generative artificial intelligence tailored to user needs.

[0270] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0271] Step 1:

[0272] Users use their devices to input work-related information. Specifically, sales staff might input the address and date of their visits, while marketing staff might input campaign details and target customer attributes. This information is temporarily stored on the device as the user's work profile.

[0273] Step 2:

[0274] The terminal uses a secure protocol (e.g., SSL / TLS) to transfer user-entered business information to the server. The input data is converted into geographical information and marketing data formats before being transmitted. Encryption is applied during this process to maintain data integrity and confidentiality.

[0275] Step 3:

[0276] The server uses a location database and a generative AI model to analyze the received business information. First, the server extracts optimal route patterns from the database based on the user's location. Then, it utilizes the generative AI model to analyze efficient visit plans and campaign strategies. Here, predictions and recommendations are made by comparing past data with the current situation.

[0277] Step 4:

[0278] The server generates suggestions for the user based on the analysis results. For sales personnel, it provides suggestions such as the order of visits and potential new clients; for marketing personnel, it provides specific guidance on the optimal timing for messages and campaigns. These suggestions are sent from the server to the terminal.

[0279] Step 5:

[0280] The terminal displays the suggestions received from the server to the user. The user reviews the suggestions and evaluates their feasibility. Furthermore, the user enters feedback into the terminal and sends it to the server. This feedback helps determine the value of the suggestions and improve future suggestions.

[0281] Step 6:

[0282] The server analyzes the feedback from the user and schedules a follow-up session. This includes regular check-ins and preparation of new proposals. Also, a process of fine-tuning the AI model generated based on the feedback to improve the quality of future proposals is advanced. Through this collaboration, the user's business efficiency is continuously improved.

[0283] (Application Example 1)

[0284] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0285] In modern business, improving business efficiency and security are important issues, but it is difficult to find an appropriate way to utilize artificial intelligence to achieve both at the same time. Therefore, users are struggling with the introduction of appropriate AI and the continuous improvement of security measures. Against this background, there is a need to provide an effective solution for optimizing business efficiency while reducing security risks.

[0286] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0287] In this invention, the server includes an information receiving means, a data processing means, a strategy presenting means, an interaction means, a planning means, and an improvement means. This enables the proposal of an optimal way to utilize AI based on business information and the continuous improvement of security measures.

[0288] The "information receiving means" is a means for receiving business information and feedback from the user and collecting them as data.

[0289] The "data processing means" is a means for analyzing the collected business information and location information data and deriving an appropriate way to utilize AI.

[0290] A "strategy presentation tool" is a means of proposing AI utilization methods and security measures to users based on the analysis results obtained from data processing tools.

[0291] A "dialogue method" is a means of engaging in dialogue with users in response to their questions and inquiries, and providing them with the necessary information and support.

[0292] "Planning methods" refer to the means of regularly scheduling follow-up sessions to continuously support users' use of AI.

[0293] "Improvement measures" refer to methods for continuously improving and optimizing proposed security measures based on user feedback.

[0294] In this invention, to realize the application example, the server receives business information and feedback from the user using an information receiving means. This information is entered by the user through a terminal and stored in a data storage means. Subsequently, the server uses a data processing means to process the collected location data and business information with AI technology and analyze the optimal way to utilize AI. This analysis utilizes generative AI models and employs software such as TensorFlow or PyTorch. The server also utilizes location information services such as the Google Maps API to identify efficient routes and risks.

[0295] Based on the analysis results, the server proposes AI utilization methods and security measures to the user through strategic proposal tools. Users can receive these proposals via their smartphones and send appropriate feedback. The dialogue tools answer user questions and provide support as the user takes action based on the proposals.

[0296] For example, if a company needs to strengthen its security, the server will analyze data to determine that improvements to internal network management are necessary. Based on this, the strategic proposal tool will suggest specific measures, which the user can then implement.

[0297] As a follow-up, regular sessions are scheduled using planning tools. This ensures that users always receive the latest suggestions, and continuous optimization of security measures is achieved through improvement tools based on their feedback.

[0298] Examples of specific prompt messages include the following:

[0299] User information: {location: 'Office location', incidents: 'Past data breach incidents'}

[0300] Business content: {type: 'IT company', size: '100 people'}

[0301] Please propose the necessary security measures.

[0302] In this way, a system is realized that improves operational efficiency and security.

[0303] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0304] Step 1:

[0305] Users input data about their work information and current security status using a terminal. This input includes location information and information about past security incidents. The terminal sends this data to a server, which stores it in a data storage system.

[0306] Step 2:

[0307] The server analyzes the received data using data processing means. It applies the input data to an AI model and processes the location information using the Google Maps API. This identifies the optimization of business processes and potential security risks. As output, it generates a list of candidates for optimized AI usage methods and security measures.

[0308] Step 3:

[0309] The server notifies the user of proposals based on the analysis results through strategic presentation means. These proposals include specific AI usage methods and security improvement measures. The user checks the proposals on the terminal and selects the measures they consider necessary.

[0310] Step 4:

[0311] The user uses interaction means to send questions and consultations based on the proposals to the server. The server responds to this by using a generative AI model to generate corresponding answers and providing them to the user in real time.

[0312] Step 5:

[0313] The server uses planning means to schedule regular follow-up sessions. This enables the user to continue receiving new proposals regularly. The user's feedback is accumulated by improvement means and reflected in subsequent proposals.

[0314] This series of steps realizes the improvement of business efficiency and security.

[0315] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion identification model 59 and perform specific processing using the user's emotions.

[0316] This invention proposes a system that combines business information and emotion recognition technology to provide users with the most optimal way to utilize generative artificial intelligence (AI). This system enables improved work efficiency for users and flexible consulting based on their individual emotional states.

[0317] System Overview

[0318] User: Inputs business information from their own device and receives suggestions for AI utilization. During this process, the emotion engine analyzes the user's facial expressions and tone of voice, and sends the emotional state to the server.

[0319] Terminal: Collects user input information and sends it to the server. Displays suggested content and collects sentiment-based feedback. Also provides users with information about follow-up sessions.

[0320] Server: Analyzes received business information and emotional data using location data and AI technology. Calculates flexible AI application methods tailored to the user's emotional state and proposes them to the user. It also generates and sends emotionally appropriate responses to the terminal. Follow-up sessions are planned at the optimal timing, taking the user's emotional state into consideration.

[0321] Specific example

[0322] For sales users: When a user starts a new sales campaign, they input business information into their terminal. Based on this information, the server proposes strategies using AI. If the user expresses anxiety or concern, the emotion engine identifies it, and the server provides detailed, emotionally sensitive explanations and reassuring responses.

[0323] For managers: When they input project progress data, the server provides project management optimization suggestions that take into account the emotional state of team members. If the emotion engine determines that the user is stressed, it adjusts the difficulty of the suggestions or recommends stress reduction measures.

[0324] This invention aims to provide more refined services than before by incorporating emotion recognition, thereby supporting the user's work environment and improving the quality of work.

[0325] The following describes the processing flow.

[0326] Step 1:

[0327] The user accesses the system from their device, enters their authentication information, and logs in. The device sends this information to the server, which then performs authentication.

[0328] Step 2:

[0329] The user inputs their work information and current AI usage status, and the device sends this information to the server. Simultaneously, the device uses an emotion engine to analyze the user's facial expressions and voice, and extracts emotional data.

[0330] Step 3:

[0331] The device sends user emotion data to the server. The server combines the received work information with the emotion data and performs a detailed analysis using location data and AI technology.

[0332] Step 4:

[0333] Based on the analysis results, the server determines the optimal way to utilize AI, adapted to the user's work situation and emotional state. This suggestion will take into account the user's current emotions.

[0334] Step 5:

[0335] The server sends the suggestions to the terminal, which then displays them to the user. The user can view the suggestions and provide emotionally appropriate questions and feedback through the terminal.

[0336] Step 6:

[0337] The server receives a question from the user, generates a response with adjusted tone and content based on sentiment data obtained by the sentiment engine, and sends it back to the terminal.

[0338] Step 7:

[0339] The server schedules regular follow-up sessions, taking into account the user's emotional state and work information. The terminal notifies the user of this schedule, ensuring that follow-ups are conducted at the optimal time.

[0340] (Example 2)

[0341] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0342] In today's business environment, simply analyzing business information is insufficient to improve the work efficiency of individual users. It is especially important to provide appropriate advice and suggestions while appropriately considering the user's emotional state. However, conventional systems lack the means to fully understand user emotions and provide optimal suggestions and follow-up accordingly. Therefore, there is a need to propose a method of utilizing individually optimized generative artificial intelligence that simultaneously considers both the user's business information and emotional state.

[0343] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0344] In this invention, the server includes means for inputting user business information via a terminal and acquiring user emotional data along with the business information; means for analyzing the business information and emotional data using location information data and generative AI technology; and means for proposing an optimal method of utilizing generative artificial intelligence that takes into account the user's emotional state based on the analysis results. This makes it possible to provide a flexible and effective method of utilizing AI that reflects the user's emotional state.

[0345] "User's work information" refers to detailed information related to the work the user is currently involved in, and specifically includes project progress, goals, and task details.

[0346] "Emotional data" refers to information obtained from a user's facial expressions and voice, and it indicates the user's psychological state and emotional tendencies.

[0347] "Generative AI technology" is an artificial intelligence technology that generates natural language text based on diverse input data, and is used to generate suggestions and responses for users.

[0348] "Analysis" is the process of using computer models to analyze collected business information and emotional data and derive meaningful results.

[0349] "Proposal methods" refer to methods and processes for presenting users with the most suitable applications and solutions based on analysis results.

[0350] A "follow-up session" is a regularly scheduled session that provides feedback and support as part of ongoing communication with the user.

[0351] "Scheduling" is the process of planning events or tasks and allocating time to carry them out at specific times.

[0352] This system uses a generative AI model to provide optimal suggestions based on the user's business information and sentiment data. The system operates according to the following procedure.

[0353] First, the user inputs work information using their own device. This device is equipped with input devices such as a camera and microphone, and emotional data is acquired by recording the user's facial expressions and voice. This data is then transmitted to the server by the device.

[0354] Next, the server processes the received business information and sentiment data for analysis. This analysis uses a generative AI model, specifically a combination of natural language processing tools and machine learning frameworks. For example, libraries such as TensorFlow are used for natural language processing to understand and analyze the user's input information.

[0355] Based on the analysis results, the server generates optimal AI usage suggestions tailored to the user's emotional state. These suggestions include adjustments to fit the user's current psychological state and provide specific procedures and guides to improve work efficiency.

[0356] For example, if sentiment analysis reveals that a sales user is feeling anxious about launching a new campaign, along with receiving business-related information, the server will propose an AI-powered strategy designed to reassure them. Furthermore, follow-up sessions will be scheduled considering the sentiment data, ensuring the user is re-engaged at the optimal time.

[0357] An example of a prompt message would be, "Please tell me the best way to use AI to make our new sales campaign a success. Also, I'm feeling anxious; how should I address this?" This allows the user to receive concrete suggestions.

[0358] In this way, the system comprehensively considers the user's emotional state and business information, providing flexible and effective AI-powered business support.

[0359] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0360] Step 1:

[0361] Users use their own devices to input work-related information. This information includes project progress and task details. While the entered work information is temporarily stored on the device, the device's camera and microphone record the user's facial expressions and voice, acquiring this as emotional data.

[0362] Step 2:

[0363] The terminal transmits acquired business information and emotional data to the server. During this process, the business information and emotional data are organized into an appropriate format and transmitted to the server via the network in an encrypted form. The input here is business information and emotional data, and the output is the secure transmission of data to the server.

[0364] Step 3:

[0365] The server analyzes received business information and emotional data. This analysis utilizes a generative AI model to generate suggestions that match the user's needs and state based on the data. The generative AI model processes the input information and outputs insights into the user's emotional state and suggestions for improving work efficiency.

[0366] Step 4:

[0367] Based on the server-generated suggestions, the system proposes the most suitable AI application methods for the user. These suggestions are tailored to the user's psychological state and include specific procedures and tool guidelines. The input is the analysis results, and the output is the user-oriented suggestions.

[0368] Step 5:

[0369] The terminal presents suggestions sent from the server to the user. It not only displays the suggestions on the screen but also provides audio explanations as needed. Furthermore, it offers an interface for the user to input additional feedback. The output consists of optimized suggestion presentations and interaction features.

[0370] Step 6:

[0371] Users can provide feedback on the suggestions they receive. This feedback will be used to improve future analyses and the content provided. The input is user feedback information.

[0372] Step 7:

[0373] Based on the feedback, the server plans a follow-up session and notifies the user of the appointment at the optimal time. This notification is sent via the terminal, and the most suitable time is selected based on the user's status and schedule. The output is a notification of the scheduled follow-up session.

[0374] (Application Example 2)

[0375] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0376] Providing flexible support based on individual emotional states while improving users' work efficiency is not easy. In particular, in face-to-face service provision, there is a lack of concrete guidelines and technologies when it is necessary to quickly understand the customer's emotions and respond accordingly. This invention aims to solve these problems and propose an optimal method of utilizing AI that is tailored to emotions.

[0377] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0378] In this invention, the server includes acquisition means for inputting user business information, analysis means for analyzing the business information using location information data and computer technology, and emotion analysis means for analyzing the user's facial expressions and voice characteristics and generating responses according to their emotional state. This allows for the proposal of the optimal AI utilization method to the user in accordance with their emotional state, and enables flexible adjustments.

[0379] "Acquisition method" refers to an interface for collecting business information from users.

[0380] "Analysis methods" refer to mechanisms that process acquired business information using location data and computer technology to evaluate the trends and usefulness of the information.

[0381] The "proposal method" is a system that, based on the analysis results, derives the optimal way for the user to use the generated artificial intelligence.

[0382] "Emotional analysis means" refers to technology that analyzes a user's facial expressions and voice data to understand their emotional state and generate an appropriate response.

[0383] A "response system" is a system designed to provide appropriate answers to user questions and concerns.

[0384] "Scheduling means" refers to the function for planning and executing follow-up sessions.

[0385] This invention is a system that combines emotion recognition technology with business information analysis to propose the optimal way for users to utilize generative artificial intelligence. The following describes the specific configuration and implementation method of the system for realizing this application example.

[0386] The server acquires business information via terminals accessed by users. This business information includes the user's job description, work processes, and past performance data. Based on this information, the server performs data analysis using computer technology. This analysis utilizes a high-performance processor as hardware, and a database management system and machine learning libraries (e.g., TensorFlow and PyTorch) as software.

[0387] In the emotion analysis system, the server collects the user's facial expressions and voice data, which are then analyzed by an emotion recognition engine. Specifically, data is acquired through a camera and microphone, and real-time analysis is performed using image recognition software algorithms (e.g., OpenCV). This analysis determines the user's emotional state (e.g., anxiety, joy, interest).

[0388] User suggestions are based on both emotional state and business information analysis. The suggestion method utilizes a generative AI model to provide user-appropriate advice and action plans. This generative AI model integrates existing data with real-time emotional input to derive the most effective approach.

[0389] As a concrete example, consider the case where this system is implemented in a physical store in Japan. Store employees wear smart glasses and analyze the facial expressions and tone of voice of visiting customers to adjust the optimal customer service approach on the spot. An example of a prompt message would be, "As the customer approaches, we observe the changes in their facial expression through the smart glasses. We evaluate their emotions based on their facial expression and voice and customize the customer service strategy." As a result, it is expected that the customer experience will improve and the store's sales efficiency will increase.

[0390] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0391] Step 1:

[0392] The terminal retrieves work information from the user. It receives job description and work process information provided by the user as input and sends it to the server as a data file.

[0393] Step 2:

[0394] The server performs data analysis using the acquired business information. It utilizes computer technology based on location data and past performance data to analyze this data. As a result of this analysis, foundational data for optimizing the user's business operations is generated.

[0395] Step 3:

[0396] The device collects the user's facial expressions and voice data. This data is acquired through cameras and microphones built into smart glasses or mobile devices and transmitted to a server in real time.

[0397] Step 4:

[0398] The server processes the received facial and audio data using an emotion analysis engine. Using image recognition software such as OpenCV, it classifies the user's emotional state in real time. The output of this process is the specific emotional state expressed by the user (e.g., anxiety, interest, joy).

[0399] Step 5:

[0400] The server integrates the results of analyzing emotional states and business information, and uses suggestion tools to generate appropriate methods for utilizing generative artificial intelligence. It leverages generative AI models to create user-optimized suggestions. These suggestions can lead to improved business efficiency and new strategic proposals.

[0401] Step 6:

[0402] The terminal provides the user with the generated suggestions. By receiving the suggestions and confirming the necessary actions, the user can improve their workflow. Further responses can be obtained by the user inputting any questions they may have during this process.

[0403] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0404] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0405] 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.

[0406] [Third Embodiment]

[0407] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0408] 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.

[0409] 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).

[0410] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0411] 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.

[0412] 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).

[0413] 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.

[0414] 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.

[0415] 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.

[0416] 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.

[0417] 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.

[0418] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0419] This invention provides an interactive counseling system aimed at improving user work efficiency and optimizing AI utilization. This system collects user work information, utilizes location data and AI technology to propose appropriate AI usage methods, and provides follow-up support to optimize business processes.

[0420] System Overview

[0421] User: Accesses the system using their own device via a dedicated application or web interface. They input business information and current AI usage status to receive suggestions on how to utilize AI.

[0422] Terminal: Receives input from the user and sends it to the server. Displays suggestions and feedback to the user, supporting interactive dialogue.

[0423] Server: Processes user business information and analyzes it using location data and AI technology. Based on the analysis results, it proposes a suitable method for using generative AI for the user. It also provides appropriate responses to user inquiries. It plans regular follow-up sessions to continuously support the user's use of AI.

[0424] Specific example

[0425] For sales users: Users input information about their daily visits and sales routes via their devices. The server uses location data and AI analysis technology to optimize visit routes and suggest target locations. These suggestions are based on past visit effectiveness and potential for new business development. Based on user feedback, the server provides an even more optimized sales strategy.

[0426] For marketing users: Users input marketing campaign data and customer target information into their terminals. The server analyzes this information using AI technology and suggests effective campaign messages and methods. Throughout this process, the success rate of campaigns is continuously tracked, and improvement strategies for the next campaign are suggested.

[0427] In this way, this system promotes the use of generative artificial intelligence in users' work and improves operational efficiency by providing detailed consulting.

[0428] The following describes the processing flow.

[0429] Step 1:

[0430] The user accesses the system from their device and enters their authentication information on the login screen. The device sends this authentication information to the server, which verifies the user's authentication information against its database and authenticates them.

[0431] Step 2:

[0432] The user inputs necessary information into the terminal, such as their work details, usage of generated AI, and location data. The terminal then sends the collected information to the server.

[0433] Step 3:

[0434] Based on the received business information, the server analyzes the user's work situation using location data and AI technology. This allows for the extraction of work patterns and the calculation of potential improvements for efficiency.

[0435] Step 4:

[0436] Based on the analysis results, the server determines the optimal way for the user to utilize the generated AI. The suggestions include specific tools, procedures, and improvement measures. The server then sends these suggestions to the user's device.

[0437] Step 5:

[0438] The terminal displays the proposal to the user, allowing the user to review it. The user can also input questions and feedback about the proposal into the terminal.

[0439] Step 6:

[0440] The server receives questions and inquiries from users, prepares appropriate answers, and sends them back to the terminal. This allows users to resolve any uncertainties and prepare to implement their suggestions.

[0441] Step 7:

[0442] The server schedules regular follow-up sessions and notifies the user via their terminal. During these sessions, the user can review the latest work status and progress of their AI-generated content, and receive additional advice.

[0443] (Example 1)

[0444] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0445] In today's business environment, many users seek to streamline and optimize their business processes, but the solutions offered are generally not personalized and therefore fail to adequately address their specific needs. Furthermore, existing systems lack the ability to effectively gather user feedback and provide continuous improvement and follow-up based on that feedback. As a result, it is extremely difficult for users to find the optimal way to utilize generative artificial intelligence.

[0446] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0447] In this invention, the server includes an input means for users to input business-related information via a terminal, a transmission means for transferring the input information to the server using a secure protocol, and an analysis means for analyzing the business information using a location information database and a generative artificial intelligence model. This makes it possible to present users with personalized methods for using generative AI and then continuously optimize it based on feedback.

[0448] "Input means" refers to a function or device that allows a user to input work-related information into a terminal.

[0449] "Transmission means" refers to a function that includes a method or protocol for securely transferring input information from a terminal to a server.

[0450] "Analysis means" refers to a function or device for analyzing business information received from users using a location information database and a generative artificial intelligence model.

[0451] "Proposed means" refers to a function or device that presents the user with the optimal way to use the generative artificial intelligence based on the analysis results obtained by the analysis means.

[0452] "Scheduling means" refers to a function or device for planning and executing follow-up sessions based on user feedback information.

[0453] "Storage means" refers to a function or device for recording the details of tasks entered by the user on a terminal and saving them to a database.

[0454] A "generative AI model" refers to AI technology that uses user business information to analyze and propose available generative artificial intelligence techniques.

[0455] This invention is an interactive support system designed to improve the efficiency of users' work. This system consists of a user, a terminal, and a server, and proposes various methods for utilizing user-optimized generative AI.

[0456] First, the user enters their work-related information through a terminal. The terminal then uses a dedicated application or web interface to transmit the collected information to the server using a secure protocol (e.g., SSL / TLS). The information entered includes the user's sales activity information and marketing campaign data, which are recorded in detail according to the characteristics of the work.

[0457] The server uses a location database and a generative AI model to process information received from the terminal. Existing AI frameworks (e.g., TensorFlow, PyTorch) can be used as the generative AI model. The server analyzes business information and proposes an appropriate AI usage method for the user.

[0458] This proposal is based on the user's past information and AI-generated predictions, specifically suggesting optimal sales routes and effective marketing messages. For example, it suggests efficient routes for sales professionals and optimal campaign strategies tailored to customer segments for marketing professionals. This maximizes the capabilities of generative AI and significantly improves the efficiency of business processes.

[0459] Examples of prompts include, "Optimize the visit route based on the visit data for your sales route," and "Analyze the new customer acquisition campaign data to suggest an effective message." Based on these prompts, the system provides the user with specific and practical advice.

[0460] This invention is a system that provides a concrete and implementable solution to improve operational efficiency by promoting the use of generative artificial intelligence tailored to user needs.

[0461] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0462] Step 1:

[0463] Users use their devices to input work-related information. Specifically, sales staff might input the address and date of their visits, while marketing staff might input campaign details and target customer attributes. This information is temporarily stored on the device as the user's work profile.

[0464] Step 2:

[0465] The terminal uses a secure protocol (e.g., SSL / TLS) to transfer user-entered business information to the server. The input data is converted into geographical information and marketing data formats before being transmitted. Encryption is applied during this process to maintain data integrity and confidentiality.

[0466] Step 3:

[0467] The server uses a location database and a generative AI model to analyze the received business information. First, the server extracts optimal route patterns from the database based on the user's location. Then, it utilizes the generative AI model to analyze efficient visit plans and campaign strategies. Here, predictions and recommendations are made by comparing past data with the current situation.

[0468] Step 4:

[0469] The server generates suggestions for the user based on the analysis results. For sales personnel, it provides suggestions such as the order of visits and potential new clients; for marketing personnel, it provides specific guidance on the optimal timing for messages and campaigns. These suggestions are sent from the server to the terminal.

[0470] Step 5:

[0471] The terminal displays the suggestions received from the server to the user. The user reviews the suggestions and evaluates their feasibility. Furthermore, the user enters feedback into the terminal and sends it to the server. This feedback helps determine the value of the suggestions and improve future suggestions.

[0472] Step 6:

[0473] The server analyzes user feedback and schedules follow-up sessions, which include regular check-ins and preparation of new suggestions. It also refines the AI ​​model based on the feedback, improving the quality of future suggestions. This collaboration continuously improves the user's work efficiency.

[0474] (Application Example 1)

[0475] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0476] In modern business, improving operational efficiency and enhancing security are critical challenges, but finding the right way to utilize artificial intelligence to achieve both simultaneously is difficult. Therefore, users struggle with the appropriate implementation of AI and the continuous improvement of security measures. Against this backdrop, there is a demand for effective solutions that optimize operational efficiency while reducing security risks.

[0477] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0478] In this invention, the server includes information receiving means, data processing means, strategy presentation means, dialogue means, planning means, and improvement means. This enables the proposal of optimal AI usage methods based on business information and continuous improvement of security measures.

[0479] "Information receiving means" refers to the means of receiving business information and feedback from users and collecting it as data.

[0480] "Data processing means" refers to methods for analyzing collected business information and location data to derive appropriate ways to utilize AI.

[0481] A "strategy presentation tool" is a means of proposing AI utilization methods and security measures to users based on the analysis results obtained from data processing tools.

[0482] A "dialogue method" is a means of engaging in dialogue with users in response to their questions and inquiries, and providing them with the necessary information and support.

[0483] "Planning methods" refer to the means of regularly scheduling follow-up sessions to continuously support users' use of AI.

[0484] "Improvement measures" refer to methods for continuously improving and optimizing proposed security measures based on user feedback.

[0485] In this invention, to realize the application example, the server receives business information and feedback from the user using an information receiving means. This information is entered by the user through a terminal and stored in a data storage means. Subsequently, the server uses a data processing means to process the collected location data and business information with AI technology and analyze the optimal way to utilize AI. This analysis utilizes generative AI models and employs software such as TensorFlow or PyTorch. The server also utilizes location information services such as the Google Maps API to identify efficient routes and risks.

[0486] Based on the analysis results, the server proposes AI utilization methods and security measures to the user through strategic proposal tools. Users can receive these proposals via their smartphones and send appropriate feedback. The dialogue tools answer user questions and provide support as the user takes action based on the proposals.

[0487] For example, if a company needs to strengthen its security, the server will analyze data to determine that improvements to internal network management are necessary. Based on this, the strategic proposal tool will suggest specific measures, which the user can then implement.

[0488] As a follow-up, regular sessions are scheduled using planning tools. This ensures that users always receive the latest suggestions, and continuous optimization of security measures is achieved through improvement tools based on their feedback.

[0489] Examples of specific prompt messages include the following:

[0490] User information: {location: 'Office location', incidents: 'Past data breach incidents'}

[0491] Business content: {type: 'IT company', size: '100 people'}

[0492] Please propose the necessary security measures.

[0493] In this way, a system is realized that improves operational efficiency and security.

[0494] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0495] Step 1:

[0496] Users input data about their work information and current security status using a terminal. This input includes location information and information about past security incidents. The terminal sends this data to a server, which stores it in a data storage system.

[0497] Step 2:

[0498] The server analyzes the received data using data processing tools. It processes the input data through an AI model and uses the Google Maps API to process location information. This optimizes business processes and identifies potential security risks. The output generates a list of optimized AI applications and suggested security measures.

[0499] Step 3:

[0500] The server notifies the user of suggestions based on the analysis results through a strategic presentation system. These suggestions include specific ways to utilize AI and measures to improve security. The user reviews the suggestions on their device and selects the measures they deem necessary.

[0501] Step 4:

[0502] Users send questions and inquiries based on suggestions to the server using a dialogue mechanism. The server then uses a generative AI model to generate corresponding answers, which are provided to the user in real time.

[0503] Step 5:

[0504] The server uses planning tools to schedule regular follow-up sessions. This allows users to continue receiving new suggestions regularly. User feedback is collected through improvement tools and reflected in future suggestions.

[0505] This series of steps will lead to improved operational efficiency and enhanced security.

[0506] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0507] This invention proposes a system that combines business information and emotion recognition technology to provide users with the most optimal way to utilize generative artificial intelligence (AI). This system enables improved work efficiency for users and flexible consulting based on their individual emotional states.

[0508] System Overview

[0509] User: Inputs business information from their own device and receives suggestions for AI utilization. During this process, the emotion engine analyzes the user's facial expressions and tone of voice, and sends the emotional state to the server.

[0510] Terminal: Collects user input information and sends it to the server. Displays suggested content and collects sentiment-based feedback. Also provides users with information about follow-up sessions.

[0511] Server: Analyzes received business information and emotional data using location data and AI technology. Calculates flexible AI application methods tailored to the user's emotional state and proposes them to the user. It also generates and sends emotionally appropriate responses to the terminal. Follow-up sessions are planned at the optimal timing, taking the user's emotional state into consideration.

[0512] Specific example

[0513] For sales users: When a user starts a new sales campaign, they input business information into their terminal. Based on this information, the server proposes strategies using AI. If the user expresses anxiety or concern, the emotion engine identifies it, and the server provides detailed, emotionally sensitive explanations and reassuring responses.

[0514] For managers: When they input project progress data, the server provides project management optimization suggestions that take into account the emotional state of team members. If the emotion engine determines that the user is stressed, it adjusts the difficulty of the suggestions or recommends stress reduction measures.

[0515] This invention aims to provide more refined services than before by incorporating emotion recognition, thereby supporting the user's work environment and improving the quality of work.

[0516] The following describes the processing flow.

[0517] Step 1:

[0518] The user accesses the system from their device, enters their authentication information, and logs in. The device sends this information to the server, which then performs authentication.

[0519] Step 2:

[0520] The user inputs their work information and current AI usage status, and the device sends this information to the server. Simultaneously, the device uses an emotion engine to analyze the user's facial expressions and voice, and extracts emotional data.

[0521] Step 3:

[0522] The device sends user emotion data to the server. The server combines the received work information with the emotion data and performs a detailed analysis using location data and AI technology.

[0523] Step 4:

[0524] Based on the analysis results, the server determines the optimal way to utilize AI, adapted to the user's work situation and emotional state. This suggestion will take into account the user's current emotions.

[0525] Step 5:

[0526] The server sends the suggestions to the terminal, which then displays them to the user. The user can view the suggestions and provide emotionally appropriate questions and feedback through the terminal.

[0527] Step 6:

[0528] The server receives a question from the user, generates a response with adjusted tone and content based on sentiment data obtained by the sentiment engine, and sends it back to the terminal.

[0529] Step 7:

[0530] The server schedules regular follow-up sessions, taking into account the user's emotional state and work information. The terminal notifies the user of this schedule, ensuring that follow-ups are conducted at the optimal time.

[0531] (Example 2)

[0532] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0533] In today's business environment, simply analyzing business information is insufficient to improve the work efficiency of individual users. It is especially important to provide appropriate advice and suggestions while appropriately considering the user's emotional state. However, conventional systems lack the means to fully understand user emotions and provide optimal suggestions and follow-up accordingly. Therefore, there is a need to propose a method of utilizing individually optimized generative artificial intelligence that simultaneously considers both the user's business information and emotional state.

[0534] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0535] In this invention, the server includes means for inputting user business information via a terminal and acquiring user emotional data along with the business information; means for analyzing the business information and emotional data using location information data and generative AI technology; and means for proposing an optimal method of utilizing generative artificial intelligence that takes into account the user's emotional state based on the analysis results. This makes it possible to provide a flexible and effective method of utilizing AI that reflects the user's emotional state.

[0536] "User's work information" refers to detailed information related to the work the user is currently involved in, and specifically includes project progress, goals, and task details.

[0537] "Emotional data" refers to information obtained from a user's facial expressions and voice, and it indicates the user's psychological state and emotional tendencies.

[0538] "Generative AI technology" is an artificial intelligence technology that generates natural language text based on diverse input data, and is used to generate suggestions and responses for users.

[0539] "Analysis" is the process of using computer models to analyze collected business information and emotional data and derive meaningful results.

[0540] "Proposal methods" refer to methods and processes for presenting users with the most suitable applications and solutions based on analysis results.

[0541] A "follow-up session" is a regularly scheduled session that provides feedback and support as part of ongoing communication with the user.

[0542] "Scheduling" is the process of planning events or tasks and allocating time to carry them out at specific times.

[0543] This system uses a generative AI model to provide optimal suggestions based on the user's business information and sentiment data. The system operates according to the following procedure.

[0544] First, the user inputs work information using their own device. This device is equipped with input devices such as a camera and microphone, and emotional data is acquired by recording the user's facial expressions and voice. This data is then transmitted to the server by the device.

[0545] Next, the server processes the received business information and sentiment data for analysis. This analysis uses a generative AI model, specifically a combination of natural language processing tools and machine learning frameworks. For example, libraries such as TensorFlow are used for natural language processing to understand and analyze the user's input information.

[0546] Based on the analysis results, the server generates optimal AI usage suggestions tailored to the user's emotional state. These suggestions include adjustments to fit the user's current psychological state and provide specific procedures and guides to improve work efficiency.

[0547] For example, if sentiment analysis reveals that a sales user is feeling anxious about launching a new campaign, along with receiving business-related information, the server will propose an AI-powered strategy designed to reassure them. Furthermore, follow-up sessions will be scheduled considering the sentiment data, ensuring the user is re-engaged at the optimal time.

[0548] An example of a prompt message would be, "Please tell me the best way to use AI to make our new sales campaign a success. Also, I'm feeling anxious; how should I address this?" This allows the user to receive concrete suggestions.

[0549] In this way, the system comprehensively considers the user's emotional state and business information, providing flexible and effective AI-powered business support.

[0550] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0551] Step 1:

[0552] Users use their own devices to input work-related information. This information includes project progress and task details. While the entered work information is temporarily stored on the device, the device's camera and microphone record the user's facial expressions and voice, acquiring this as emotional data.

[0553] Step 2:

[0554] The terminal transmits acquired business information and emotional data to the server. During this process, the business information and emotional data are organized into an appropriate format and transmitted to the server via the network in an encrypted form. The input here is business information and emotional data, and the output is the secure transmission of data to the server.

[0555] Step 3:

[0556] The server analyzes received business information and emotional data. This analysis utilizes a generative AI model to generate suggestions that match the user's needs and state based on the data. The generative AI model processes the input information and outputs insights into the user's emotional state and suggestions for improving work efficiency.

[0557] Step 4:

[0558] Based on the server-generated suggestions, the system proposes the most suitable AI application methods for the user. These suggestions are tailored to the user's psychological state and include specific procedures and tool guidelines. The input is the analysis results, and the output is the user-oriented suggestions.

[0559] Step 5:

[0560] The terminal presents suggestions sent from the server to the user. It not only displays the suggestions on the screen but also provides audio explanations as needed. Furthermore, it offers an interface for the user to input additional feedback. The output consists of optimized suggestion presentations and interaction features.

[0561] Step 6:

[0562] Users can provide feedback on the suggestions they receive. This feedback will be used to improve future analyses and the content provided. The input is user feedback information.

[0563] Step 7:

[0564] Based on the feedback, the server plans a follow-up session and notifies the user of the appointment at the optimal time. This notification is sent via the terminal, and the most suitable time is selected based on the user's status and schedule. The output is a notification of the scheduled follow-up session.

[0565] (Application Example 2)

[0566] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0567] Providing flexible support based on individual emotional states while improving users' work efficiency is not easy. In particular, in face-to-face service provision, there is a lack of concrete guidelines and technologies when it is necessary to quickly understand the customer's emotions and respond accordingly. This invention aims to solve these problems and propose an optimal method of utilizing AI that is tailored to emotions.

[0568] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0569] In this invention, the server includes acquisition means for inputting user business information, analysis means for analyzing the business information using location information data and computer technology, and emotion analysis means for analyzing the user's facial expressions and voice characteristics and generating responses according to their emotional state. This allows for the proposal of the optimal AI utilization method to the user in accordance with their emotional state, and enables flexible adjustments.

[0570] "Acquisition method" refers to an interface for collecting business information from users.

[0571] "Analysis methods" refer to mechanisms that process acquired business information using location data and computer technology to evaluate the trends and usefulness of the information.

[0572] The "proposal method" is a system that, based on the analysis results, derives the optimal way for the user to use the generated artificial intelligence.

[0573] "Emotional analysis means" refers to technology that analyzes a user's facial expressions and voice data to understand their emotional state and generate an appropriate response.

[0574] A "response system" is a system designed to provide appropriate answers to user questions and concerns.

[0575] "Scheduling means" refers to the function for planning and executing follow-up sessions.

[0576] This invention is a system that combines emotion recognition technology with business information analysis to propose the optimal way for users to utilize generative artificial intelligence. The following describes the specific configuration and implementation method of the system for realizing this application example.

[0577] The server acquires business information via terminals accessed by users. This business information includes the user's job description, work processes, and past performance data. Based on this information, the server performs data analysis using computer technology. This analysis utilizes a high-performance processor as hardware, and a database management system and machine learning libraries (e.g., TensorFlow and PyTorch) as software.

[0578] In the emotion analysis system, the server collects the user's facial expressions and voice data, which are then analyzed by an emotion recognition engine. Specifically, data is acquired through a camera and microphone, and real-time analysis is performed using image recognition software algorithms (e.g., OpenCV). This analysis determines the user's emotional state (e.g., anxiety, joy, interest).

[0579] User suggestions are based on both emotional state and business information analysis. The suggestion method utilizes a generative AI model to provide user-appropriate advice and action plans. This generative AI model integrates existing data with real-time emotional input to derive the most effective approach.

[0580] As a concrete example, consider the case where this system is implemented in a physical store in Japan. Store employees wear smart glasses and analyze the facial expressions and tone of voice of visiting customers to adjust the optimal customer service approach on the spot. An example of a prompt message would be, "As the customer approaches, we observe the changes in their facial expression through the smart glasses. We evaluate their emotions based on their facial expression and voice and customize the customer service strategy." As a result, it is expected that the customer experience will improve and the store's sales efficiency will increase.

[0581] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0582] Step 1:

[0583] The terminal retrieves work information from the user. It receives job description and work process information provided by the user as input and sends it to the server as a data file.

[0584] Step 2:

[0585] The server performs data analysis using the acquired business information. It utilizes computer technology based on location data and past performance data to analyze this data. As a result of this analysis, foundational data for optimizing the user's business operations is generated.

[0586] Step 3:

[0587] The device collects the user's facial expressions and voice data. This data is acquired through cameras and microphones built into smart glasses or mobile devices and transmitted to a server in real time.

[0588] Step 4:

[0589] The server processes the received facial and audio data using an emotion analysis engine. Using image recognition software such as OpenCV, it classifies the user's emotional state in real time. The output of this process is the specific emotional state expressed by the user (e.g., anxiety, interest, joy).

[0590] Step 5:

[0591] The server integrates the results of analyzing emotional states and business information, and uses suggestion tools to generate appropriate methods for utilizing generative artificial intelligence. It leverages generative AI models to create user-optimized suggestions. These suggestions can lead to improved business efficiency and new strategic proposals.

[0592] Step 6:

[0593] The terminal provides the user with the generated suggestions. By receiving the suggestions and confirming the necessary actions, the user can improve their workflow. Further responses can be obtained by the user inputting any questions they may have during this process.

[0594] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0595] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0596] 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.

[0597] [Fourth Embodiment]

[0598] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0599] 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.

[0600] 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).

[0601] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0602] 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.

[0603] 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).

[0604] 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.

[0605] 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.

[0606] 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.

[0607] 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.

[0608] 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.

[0609] 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.

[0610] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0611] This invention provides an interactive counseling system aimed at improving user work efficiency and optimizing AI utilization. This system collects user work information, utilizes location data and AI technology to propose appropriate AI usage methods, and provides follow-up support to optimize business processes.

[0612] System Overview

[0613] User: Accesses the system using their own device via a dedicated application or web interface. They input business information and current AI usage status to receive suggestions on how to utilize AI.

[0614] Terminal: Receives input from the user and sends it to the server. Displays suggestions and feedback to the user, supporting interactive dialogue.

[0615] Server: Processes user business information and analyzes it using location data and AI technology. Based on the analysis results, it proposes a suitable method for using generative AI for the user. It also provides appropriate responses to user inquiries. It plans regular follow-up sessions to continuously support the user's use of AI.

[0616] Specific example

[0617] For sales users: Users input information about their daily visits and sales routes via their devices. The server uses location data and AI analysis technology to optimize visit routes and suggest target locations. These suggestions are based on past visit effectiveness and potential for new business development. Based on user feedback, the server provides an even more optimized sales strategy.

[0618] For marketing users: Users input marketing campaign data and customer target information into their terminals. The server analyzes this information using AI technology and suggests effective campaign messages and methods. Throughout this process, the success rate of campaigns is continuously tracked, and improvement strategies for the next campaign are suggested.

[0619] In this way, this system promotes the use of generative artificial intelligence in users' work and improves operational efficiency by providing detailed consulting.

[0620] The following describes the processing flow.

[0621] Step 1:

[0622] The user accesses the system from their device and enters their authentication information on the login screen. The device sends this authentication information to the server, which verifies the user's authentication information against its database and authenticates them.

[0623] Step 2:

[0624] The user inputs necessary information into the terminal, such as their work details, usage of generated AI, and location data. The terminal then sends the collected information to the server.

[0625] Step 3:

[0626] Based on the received business information, the server analyzes the user's work situation using location data and AI technology. This allows for the extraction of work patterns and the calculation of potential improvements for efficiency.

[0627] Step 4:

[0628] Based on the analysis results, the server determines the optimal way for the user to utilize the generated AI. The suggestions include specific tools, procedures, and improvement measures. The server then sends these suggestions to the user's device.

[0629] Step 5:

[0630] The terminal displays the proposal to the user, allowing the user to review it. The user can also input questions and feedback about the proposal into the terminal.

[0631] Step 6:

[0632] The server receives questions and inquiries from users, prepares appropriate answers, and sends them back to the terminal. This allows users to resolve any uncertainties and prepare to implement their suggestions.

[0633] Step 7:

[0634] The server schedules regular follow-up sessions and notifies the user via their terminal. During these sessions, the user can review the latest work status and progress of their AI-generated content, and receive additional advice.

[0635] (Example 1)

[0636] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0637] In today's business environment, many users seek to streamline and optimize their business processes, but the solutions offered are generally not personalized and therefore fail to adequately address their specific needs. Furthermore, existing systems lack the ability to effectively gather user feedback and provide continuous improvement and follow-up based on that feedback. As a result, it is extremely difficult for users to find the optimal way to utilize generative artificial intelligence.

[0638] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0639] In this invention, the server includes an input means for users to input business-related information via a terminal, a transmission means for transferring the input information to the server using a secure protocol, and an analysis means for analyzing the business information using a location information database and a generative artificial intelligence model. This makes it possible to present users with personalized methods for using generative AI and then continuously optimize it based on feedback.

[0640] "Input means" refers to a function or device that allows a user to input work-related information into a terminal.

[0641] "Transmission means" refers to a function that includes a method or protocol for securely transferring input information from a terminal to a server.

[0642] "Analysis means" refers to a function or device for analyzing business information received from users using a location information database and a generative artificial intelligence model.

[0643] "Proposed means" refers to a function or device that presents the user with the optimal way to use the generative artificial intelligence based on the analysis results obtained by the analysis means.

[0644] "Scheduling means" refers to a function or device for planning and executing follow-up sessions based on user feedback information.

[0645] "Storage means" refers to a function or device for recording the details of tasks entered by the user on a terminal and saving them to a database.

[0646] A "generative AI model" refers to AI technology that uses user business information to analyze and propose available generative artificial intelligence techniques.

[0647] This invention is an interactive support system designed to improve the efficiency of users' work. This system consists of a user, a terminal, and a server, and proposes various methods for utilizing user-optimized generative AI.

[0648] First, the user enters their work-related information through a terminal. The terminal then uses a dedicated application or web interface to transmit the collected information to the server using a secure protocol (e.g., SSL / TLS). The information entered includes the user's sales activity information and marketing campaign data, which are recorded in detail according to the characteristics of the work.

[0649] The server uses a location database and a generative AI model to process information received from the terminal. Existing AI frameworks (e.g., TensorFlow, PyTorch) can be used as the generative AI model. The server analyzes business information and proposes an appropriate AI usage method for the user.

[0650] This proposal is based on the user's past information and AI-generated predictions, specifically suggesting optimal sales routes and effective marketing messages. For example, it suggests efficient routes for sales professionals and optimal campaign strategies tailored to customer segments for marketing professionals. This maximizes the capabilities of generative AI and significantly improves the efficiency of business processes.

[0651] Examples of prompts include, "Optimize the visit route based on the visit data for your sales route," and "Analyze the new customer acquisition campaign data to suggest an effective message." Based on these prompts, the system provides the user with specific and practical advice.

[0652] This invention is a system that provides a concrete and implementable solution to improve operational efficiency by promoting the use of generative artificial intelligence tailored to user needs.

[0653] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0654] Step 1:

[0655] Users use their devices to input work-related information. Specifically, sales staff might input the address and date of their visits, while marketing staff might input campaign details and target customer attributes. This information is temporarily stored on the device as the user's work profile.

[0656] Step 2:

[0657] The terminal uses a secure protocol (e.g., SSL / TLS) to transfer user-entered business information to the server. The input data is converted into geographical information and marketing data formats before being transmitted. Encryption is applied during this process to maintain data integrity and confidentiality.

[0658] Step 3:

[0659] The server uses a location database and a generative AI model to analyze the received business information. First, the server extracts optimal route patterns from the database based on the user's location. Then, it utilizes the generative AI model to analyze efficient visit plans and campaign strategies. Here, predictions and recommendations are made by comparing past data with the current situation.

[0660] Step 4:

[0661] The server generates suggestions for the user based on the analysis results. For sales personnel, it provides suggestions such as the order of visits and potential new clients; for marketing personnel, it provides specific guidance on the optimal timing for messages and campaigns. These suggestions are sent from the server to the terminal.

[0662] Step 5:

[0663] The terminal displays the suggestions received from the server to the user. The user reviews the suggestions and evaluates their feasibility. Furthermore, the user enters feedback into the terminal and sends it to the server. This feedback helps determine the value of the suggestions and improve future suggestions.

[0664] Step 6:

[0665] The server analyzes user feedback and schedules follow-up sessions, which include regular check-ins and preparation of new suggestions. It also refines the AI ​​model based on the feedback, improving the quality of future suggestions. This collaboration continuously improves the user's work efficiency.

[0666] (Application Example 1)

[0667] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0668] In modern business, improving operational efficiency and enhancing security are critical challenges, but finding the right way to utilize artificial intelligence to achieve both simultaneously is difficult. Therefore, users struggle with the appropriate implementation of AI and the continuous improvement of security measures. Against this backdrop, there is a demand for effective solutions that optimize operational efficiency while reducing security risks.

[0669] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0670] In this invention, the server includes information receiving means, data processing means, strategy presentation means, dialogue means, planning means, and improvement means. This enables the proposal of optimal AI usage methods based on business information and continuous improvement of security measures.

[0671] "Information receiving means" refers to the means of receiving business information and feedback from users and collecting it as data.

[0672] "Data processing means" refers to methods for analyzing collected business information and location data to derive appropriate ways to utilize AI.

[0673] A "strategy presentation tool" is a means of proposing AI utilization methods and security measures to users based on the analysis results obtained from data processing tools.

[0674] A "dialogue method" is a means of engaging in dialogue with users in response to their questions and inquiries, and providing them with the necessary information and support.

[0675] "Planning methods" refer to the means of regularly scheduling follow-up sessions to continuously support users' use of AI.

[0676] "Improvement measures" refer to methods for continuously improving and optimizing proposed security measures based on user feedback.

[0677] In this invention, to realize the application example, the server receives business information and feedback from the user using an information receiving means. This information is entered by the user through a terminal and stored in a data storage means. Subsequently, the server uses a data processing means to process the collected location data and business information with AI technology and analyze the optimal way to utilize AI. This analysis utilizes generative AI models and employs software such as TensorFlow or PyTorch. The server also utilizes location information services such as the Google Maps API to identify efficient routes and risks.

[0678] Based on the analysis results, the server proposes AI utilization methods and security measures to the user through strategic proposal tools. Users can receive these proposals via their smartphones and send appropriate feedback. The dialogue tools answer user questions and provide support as the user takes action based on the proposals.

[0679] For example, if a company needs to strengthen its security, the server will analyze data to determine that improvements to internal network management are necessary. Based on this, the strategic proposal tool will suggest specific measures, which the user can then implement.

[0680] As a follow-up, regular sessions are scheduled using planning tools. This ensures that users always receive the latest suggestions, and continuous optimization of security measures is achieved through improvement tools based on their feedback.

[0681] Examples of specific prompt messages include the following:

[0682] User information: {location: 'Office location', incidents: 'Past data breach incidents'}

[0683] Business content: {type: 'IT company', size: '100 people'}

[0684] Please propose the necessary security measures.

[0685] In this way, a system is realized that improves operational efficiency and security.

[0686] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0687] Step 1:

[0688] Users input data about their work information and current security status using a terminal. This input includes location information and information about past security incidents. The terminal sends this data to a server, which stores it in a data storage system.

[0689] Step 2:

[0690] The server analyzes the received data using data processing tools. It processes the input data through an AI model and uses the Google Maps API to process location information. This optimizes business processes and identifies potential security risks. The output generates a list of optimized AI applications and suggested security measures.

[0691] Step 3:

[0692] The server notifies the user of suggestions based on the analysis results through a strategic presentation system. These suggestions include specific ways to utilize AI and measures to improve security. The user reviews the suggestions on their device and selects the measures they deem necessary.

[0693] Step 4:

[0694] Users send questions and inquiries based on suggestions to the server using a dialogue mechanism. The server then uses a generative AI model to generate corresponding answers, which are provided to the user in real time.

[0695] Step 5:

[0696] The server uses planning tools to schedule regular follow-up sessions. This allows users to continue receiving new suggestions regularly. User feedback is collected through improvement tools and reflected in future suggestions.

[0697] This series of steps will lead to improved operational efficiency and enhanced security.

[0698] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0699] This invention proposes a system that combines business information and emotion recognition technology to provide users with the most optimal way to utilize generative artificial intelligence (AI). This system enables improved work efficiency for users and flexible consulting based on their individual emotional states.

[0700] System Overview

[0701] User: Inputs business information from their own device and receives suggestions for AI utilization. During this process, the emotion engine analyzes the user's facial expressions and tone of voice, and sends the emotional state to the server.

[0702] Terminal: Collects user input information and sends it to the server. Displays suggested content and collects sentiment-based feedback. Also provides users with information about follow-up sessions.

[0703] Server: Analyzes received business information and emotional data using location data and AI technology. Calculates flexible AI application methods tailored to the user's emotional state and proposes them to the user. It also generates and sends emotionally appropriate responses to the terminal. Follow-up sessions are planned at the optimal timing, taking the user's emotional state into consideration.

[0704] Specific example

[0705] For sales users: When a user starts a new sales campaign, they input business information into their terminal. Based on this information, the server proposes strategies using AI. If the user expresses anxiety or concern, the emotion engine identifies it, and the server provides detailed, emotionally sensitive explanations and reassuring responses.

[0706] For managers: When they input project progress data, the server provides project management optimization suggestions that take into account the emotional state of team members. If the emotion engine determines that the user is stressed, it adjusts the difficulty of the suggestions or recommends stress reduction measures.

[0707] This invention aims to provide more refined services than before by incorporating emotion recognition, thereby supporting the user's work environment and improving the quality of work.

[0708] The following describes the processing flow.

[0709] Step 1:

[0710] The user accesses the system from their device, enters their authentication information, and logs in. The device sends this information to the server, which then performs authentication.

[0711] Step 2:

[0712] The user inputs their work information and current AI usage status, and the device sends this information to the server. Simultaneously, the device uses an emotion engine to analyze the user's facial expressions and voice, and extracts emotional data.

[0713] Step 3:

[0714] The device sends user emotion data to the server. The server combines the received work information with the emotion data and performs a detailed analysis using location data and AI technology.

[0715] Step 4:

[0716] Based on the analysis results, the server determines the optimal way to utilize AI, adapted to the user's work situation and emotional state. This suggestion will take into account the user's current emotions.

[0717] Step 5:

[0718] The server sends the suggestions to the terminal, which then displays them to the user. The user can view the suggestions and provide emotionally appropriate questions and feedback through the terminal.

[0719] Step 6:

[0720] The server receives a question from the user, generates a response with adjusted tone and content based on sentiment data obtained by the sentiment engine, and sends it back to the terminal.

[0721] Step 7:

[0722] The server schedules regular follow-up sessions, taking into account the user's emotional state and work information. The terminal notifies the user of this schedule, ensuring that follow-ups are conducted at the optimal time.

[0723] (Example 2)

[0724] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0725] In today's business environment, simply analyzing business information is insufficient to improve the work efficiency of individual users. It is especially important to provide appropriate advice and suggestions while appropriately considering the user's emotional state. However, conventional systems lack the means to fully understand user emotions and provide optimal suggestions and follow-up accordingly. Therefore, there is a need to propose a method of utilizing individually optimized generative artificial intelligence that simultaneously considers both the user's business information and emotional state.

[0726] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0727] In this invention, the server includes means for inputting user business information via a terminal and acquiring user emotional data along with the business information; means for analyzing the business information and emotional data using location information data and generative AI technology; and means for proposing an optimal method of utilizing generative artificial intelligence that takes into account the user's emotional state based on the analysis results. This makes it possible to provide a flexible and effective method of utilizing AI that reflects the user's emotional state.

[0728] "User's work information" refers to detailed information related to the work the user is currently involved in, and specifically includes project progress, goals, and task details.

[0729] "Emotional data" refers to information obtained from a user's facial expressions and voice, and it indicates the user's psychological state and emotional tendencies.

[0730] "Generative AI technology" is an artificial intelligence technology that generates natural language text based on diverse input data, and is used to generate suggestions and responses for users.

[0731] "Analysis" is the process of using computer models to analyze collected business information and emotional data and derive meaningful results.

[0732] "Proposal methods" refer to methods and processes for presenting users with the most suitable applications and solutions based on analysis results.

[0733] A "follow-up session" is a regularly scheduled session that provides feedback and support as part of ongoing communication with the user.

[0734] "Scheduling" is the process of planning events or tasks and allocating time to carry them out at specific times.

[0735] This system uses a generative AI model to provide optimal suggestions based on the user's business information and sentiment data. The system operates according to the following procedure.

[0736] First, the user inputs work information using their own device. This device is equipped with input devices such as a camera and microphone, and emotional data is acquired by recording the user's facial expressions and voice. This data is then transmitted to the server by the device.

[0737] Next, the server processes the received business information and sentiment data for analysis. This analysis uses a generative AI model, specifically a combination of natural language processing tools and machine learning frameworks. For example, libraries such as TensorFlow are used for natural language processing to understand and analyze the user's input information.

[0738] Based on the analysis results, the server generates optimal AI usage suggestions tailored to the user's emotional state. These suggestions include adjustments to fit the user's current psychological state and provide specific procedures and guides to improve work efficiency.

[0739] For example, if sentiment analysis reveals that a sales user is feeling anxious about launching a new campaign, along with receiving business-related information, the server will propose an AI-powered strategy designed to reassure them. Furthermore, follow-up sessions will be scheduled considering the sentiment data, ensuring the user is re-engaged at the optimal time.

[0740] An example of a prompt message would be, "Please tell me the best way to use AI to make our new sales campaign a success. Also, I'm feeling anxious; how should I address this?" This allows the user to receive concrete suggestions.

[0741] In this way, the system comprehensively considers the user's emotional state and business information, providing flexible and effective AI-powered business support.

[0742] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0743] Step 1:

[0744] Users use their own devices to input work-related information. This information includes project progress and task details. While the entered work information is temporarily stored on the device, the device's camera and microphone record the user's facial expressions and voice, acquiring this as emotional data.

[0745] Step 2:

[0746] The terminal transmits acquired business information and emotional data to the server. During this process, the business information and emotional data are organized into an appropriate format and transmitted to the server via the network in an encrypted form. The input here is business information and emotional data, and the output is the secure transmission of data to the server.

[0747] Step 3:

[0748] The server analyzes received business information and emotional data. This analysis utilizes a generative AI model to generate suggestions that match the user's needs and state based on the data. The generative AI model processes the input information and outputs insights into the user's emotional state and suggestions for improving work efficiency.

[0749] Step 4:

[0750] Based on the server-generated suggestions, the system proposes the most suitable AI application methods for the user. These suggestions are tailored to the user's psychological state and include specific procedures and tool guidelines. The input is the analysis results, and the output is the user-oriented suggestions.

[0751] Step 5:

[0752] The terminal presents suggestions sent from the server to the user. It not only displays the suggestions on the screen but also provides audio explanations as needed. Furthermore, it offers an interface for the user to input additional feedback. The output consists of optimized suggestion presentations and interaction features.

[0753] Step 6:

[0754] Users can provide feedback on the suggestions they receive. This feedback will be used to improve future analyses and the content provided. The input is user feedback information.

[0755] Step 7:

[0756] Based on the feedback, the server plans a follow-up session and notifies the user of the appointment at the optimal time. This notification is sent via the terminal, and the most suitable time is selected based on the user's status and schedule. The output is a notification of the scheduled follow-up session.

[0757] (Application Example 2)

[0758] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0759] Providing flexible support based on individual emotional states while improving users' work efficiency is not easy. In particular, in face-to-face service provision, there is a lack of concrete guidelines and technologies when it is necessary to quickly understand the customer's emotions and respond accordingly. This invention aims to solve these problems and propose an optimal method of utilizing AI that is tailored to emotions.

[0760] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0761] In this invention, the server includes acquisition means for inputting user business information, analysis means for analyzing the business information using location information data and computer technology, and emotion analysis means for analyzing the user's facial expressions and voice characteristics and generating responses according to their emotional state. This allows for the proposal of the optimal AI utilization method to the user in accordance with their emotional state, and enables flexible adjustments.

[0762] "Acquisition method" refers to an interface for collecting business information from users.

[0763] "Analysis methods" refer to mechanisms that process acquired business information using location data and computer technology to evaluate the trends and usefulness of the information.

[0764] The "proposal method" is a system that, based on the analysis results, derives the optimal way for the user to use the generated artificial intelligence.

[0765] "Emotional analysis means" refers to technology that analyzes a user's facial expressions and voice data to understand their emotional state and generate an appropriate response.

[0766] A "response system" is a system designed to provide appropriate answers to user questions and concerns.

[0767] "Scheduling means" refers to the function for planning and executing follow-up sessions.

[0768] This invention is a system that combines emotion recognition technology with business information analysis to propose the optimal way for users to utilize generative artificial intelligence. The following describes the specific configuration and implementation method of the system for realizing this application example.

[0769] The server acquires business information via terminals accessed by users. This business information includes the user's job description, work processes, and past performance data. Based on this information, the server performs data analysis using computer technology. This analysis utilizes a high-performance processor as hardware, and a database management system and machine learning libraries (e.g., TensorFlow and PyTorch) as software.

[0770] In the emotion analysis system, the server collects the user's facial expressions and voice data, which are then analyzed by an emotion recognition engine. Specifically, data is acquired through a camera and microphone, and real-time analysis is performed using image recognition software algorithms (e.g., OpenCV). This analysis determines the user's emotional state (e.g., anxiety, joy, interest).

[0771] User suggestions are based on both emotional state and business information analysis. The suggestion method utilizes a generative AI model to provide user-appropriate advice and action plans. This generative AI model integrates existing data with real-time emotional input to derive the most effective approach.

[0772] As a concrete example, consider the case where this system is implemented in a physical store in Japan. Store employees wear smart glasses and analyze the facial expressions and tone of voice of visiting customers to adjust the optimal customer service approach on the spot. An example of a prompt message would be, "As the customer approaches, we observe the changes in their facial expression through the smart glasses. We evaluate their emotions based on their facial expression and voice and customize the customer service strategy." As a result, it is expected that the customer experience will improve and the store's sales efficiency will increase.

[0773] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0774] Step 1:

[0775] The terminal retrieves work information from the user. It receives job description and work process information provided by the user as input and sends it to the server as a data file.

[0776] Step 2:

[0777] The server performs data analysis using the acquired business information. It utilizes computer technology based on location data and past performance data to analyze this data. As a result of this analysis, foundational data for optimizing the user's business operations is generated.

[0778] Step 3:

[0779] The device collects the user's facial expressions and voice data. This data is acquired through cameras and microphones built into smart glasses or mobile devices and transmitted to a server in real time.

[0780] Step 4:

[0781] The server processes the received facial and audio data using an emotion analysis engine. Using image recognition software such as OpenCV, it classifies the user's emotional state in real time. The output of this process is the specific emotional state expressed by the user (e.g., anxiety, interest, joy).

[0782] Step 5:

[0783] The server integrates the results of analyzing emotional states and business information, and uses suggestion tools to generate appropriate methods for utilizing generative artificial intelligence. It leverages generative AI models to create user-optimized suggestions. These suggestions can lead to improved business efficiency and new strategic proposals.

[0784] Step 6:

[0785] The terminal provides the user with the generated suggestions. By receiving the suggestions and confirming the necessary actions, the user can improve their workflow. Further responses can be obtained by the user inputting any questions they may have during this process.

[0786] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0787] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] 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."

[0795] 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.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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.

[0800] 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.

[0801] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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 as being incorporated by reference.

[0807] The following is further disclosed regarding the embodiments described above.

[0808] (Claim 1)

[0809] An input method for entering user business information,

[0810] An analysis means for analyzing the aforementioned business information using location data and artificial intelligence technology,

[0811] Based on the aforementioned analysis results, a proposal means is provided to suggest the most suitable way for the user to utilize generative artificial intelligence,

[0812] A means for responding to questions and inquiries that arise from the user based on the above proposal,

[0813] A scheduling mechanism for scheduling and conducting regular follow-up sessions,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, characterized in that the input means includes a storage means for storing the user's business profile in a database.

[0817] (Claim 3)

[0818] The proposed means is characterized by providing specific tool recommendations and procedural guidelines as a method for utilizing generative artificial intelligence, as described in claim 1.

[0819] "Example 1"

[0820] (Claim 1)

[0821] An input method for users to input work-related information via a terminal,

[0822] A transmission means for transferring input information to a server using a secure protocol,

[0823] An analytical means for analyzing business information using a location information database and a generative artificial intelligence model,

[0824] Based on the analyzed results, a proposal means presents the optimal method for using the generative artificial intelligence for the user,

[0825] A scheduling means for receiving user feedback and planning and executing follow-up sessions,

[0826] A system that includes this.

[0827] (Claim 2)

[0828] The system according to claim 1, characterized in that the input means includes a storage means for the user to input details of a task on a terminal and record this in a database.

[0829] (Claim 3)

[0830] The proposed means is characterized by providing specific tools and procedural guidelines suitable for the use of generative artificial intelligence, as described in claim 1.

[0831] "Application Example 1"

[0832] (Claim 1)

[0833] A means of receiving information for inputting user business information,

[0834] A data processing means for analyzing the aforementioned business information using location data and artificial intelligence technology,

[0835] Based on the aforementioned analysis results, a means of presenting strategies for proposing the most suitable way for users to utilize generative artificial intelligence,

[0836] A dialogue means for responding to questions and inquiries that arise from the user based on the above proposal,

[0837] A planning tool for scheduling and conducting regular follow-up sessions,

[0838] Improvement measures to continuously improve security measures based on user feedback,

[0839] A system that includes this.

[0840] (Claim 2)

[0841] The system according to claim 1, characterized in that the information receiving means stores the user's business profile in the data storage means.

[0842] (Claim 3)

[0843] The system according to claim 1, characterized in that the strategy presentation means proposes specific means and procedural guidelines as methods for utilizing generative artificial intelligence, as well as security measures.

[0844] "Example 2 of combining an emotion engine"

[0845] (Claim 1)

[0846] A means for inputting user work information via a terminal and acquiring user emotion data along with said work information,

[0847] A means for analyzing the aforementioned business information and emotional data using location information data and generative AI technology,

[0848] Based on the aforementioned analysis results, a means to propose an optimal method for utilizing generative artificial intelligence that takes into account the user's emotional state,

[0849] A means for generating and providing emotionally sensitive responses to questions and consultations that arise from the user based on the aforementioned proposal,

[0850] A means of scheduling and executing follow-up sessions at the optimal timing, taking into account the user's emotional state,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, characterized in that the input means includes means for storing the user's work-related information and emotional data in a database.

[0854] (Claim 3)

[0855] The proposed means is characterized by providing specific procedures and guides as a method for utilizing generative AI that can be flexibly adjusted according to the user's emotional state, as described in claim 1.

[0856] "Application example 2 when combining with an emotional engine"

[0857] (Claim 1)

[0858] A means of obtaining user business information for input,

[0859] An analysis means for analyzing the business information using location data and computer technology,

[0860] Based on the aforementioned analysis results, a proposal means is provided to suggest the most suitable way for the user to utilize generative artificial intelligence,

[0861] An emotion analysis means for analyzing the user's facial expressions and voice characteristics and generating responses according to their emotional state,

[0862] A means for responding to questions and inquiries arising from the above proposal,

[0863] A scheduling mechanism for planning and conducting regular follow-up sessions,

[0864] A system that includes this.

[0865] (Claim 2)

[0866] The system according to claim 1, characterized in that the acquisition means includes recording means for recording the user's work profile in an information accumulating device.

[0867] (Claim 3)

[0868] The proposed means is characterized by providing specific method recommendations and procedural guidelines as methods for utilizing generative artificial intelligence, as described in claim 1. [Explanation of Symbols]

[0869] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input method for entering user business information, An analysis means for analyzing the aforementioned business information using location data and artificial intelligence technology, Based on the aforementioned analysis results, a proposal means is provided to suggest the most suitable way for the user to utilize generative artificial intelligence, A means for responding to questions and inquiries that arise from the user based on the above proposal, A scheduling mechanism for scheduling and conducting regular follow-up sessions, A system that includes this.

2. The system according to claim 1, characterized in that the input means includes a storage means for storing the user's business profile in a database.

3. The proposed means is characterized by providing specific tool recommendations and procedural guidelines as a method for utilizing generative artificial intelligence, as described in claim 1.

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