system

Abstract

This system provides a platform for companies lagging behind in digitalization and digital transformation to receive proposals for digitalization and digital transformation for their management teams. [Solution] A system comprising: means for a user to input company information; means for a user to input needs and challenges related to digitalization and digital transformation; means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon; means for displaying the proposals generated by the generative artificial intelligence to the user; means for a user to input feedback based on the proposals; means for a user to request a proposal they like; and means for forwarding the proposal request to a business operator and managing the progress of follow-up.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] First, the system provides a means for users to input company information. Next, it provides a means for users to input their needs and challenges regarding digitalization and digital transformation, thereby collecting specific user requirements. Based on this information, it has a means to analyze the user's needs and challenges using generative artificial intelligence and generate proposals based on that analysis. The generated proposals are displayed to the user, and a means is provided for the user to review the proposal content. Furthermore, a means is provided for the user to input feedback based on the proposals and to request proposals they like. In addition, it includes a means to forward proposal requests to service providers (e.g., solution providers) and to manage the progress of follow-up.

[0007] In this way, even with limited resources, it is possible to build a system that allows small and medium-sized enterprises to easily receive expert proposals for digitalization and digital transformation, thereby improving operational efficiency and competitiveness.

[0008] "Digitalization" refers to the process of introducing digital technologies into a company's or organization's business processes, services, and products to achieve automation and efficiency.

[0009] "Digital transformation (DX)" is the process of fundamentally transforming a company's or organization's business model and operational processes by utilizing digital technologies, thereby improving its competitiveness and value creation capabilities.

[0010] "Company information" refers to the basic data of a company, including company name, job title, contact information, etc.

[0011] "Generative artificial intelligence" refers to algorithms and systems that generate new information or suggestions based on specific inputs.

[0012] "Needs" refer to problems that users want to solve or the services and products they are looking for.

[0013] A "challenge" refers to a problem or obstacle that a user is currently facing, and it is something that needs to be solved.

[0014] "Means" refer to the methods or tools used to achieve a specific objective.

[0015] A "suggestion" refers to a solution or recommended action created by a generative artificial intelligence system based on the user's input needs and challenges.

[0016] "Feedback" refers to the opinions and reactions that users provide to suggestions.

[0017] A "Request for Proposal" is the process by which a user formally requests further specific actions or follow-up based on a proposal they have generated.

[0018] A "service provider" is a company or organization that provides services or solutions to users.

[0019] "Follow-up" refers to progress management and additional actions taken after receiving a request for proposal. [Brief explanation of the drawing]

[0020] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] 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 a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of 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 an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0021] 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.

[0022] First, the language used in the following description will be explained.

[0023] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0024] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0025] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0026] 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).

[0027] 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."

[0028] [First Embodiment]

[0029] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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".

[0041] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. The system has a function where the user inputs company information, needs, and challenges, and based on this, a generative artificial intelligence generates proposals, which are then displayed to the user. It also provides a means for the user to input feedback on the proposals and request the preferred proposals from service providers.

[0042] System Configuration

[0043] 1. Terminal: A device on which an application is installed and which the user operates through an interface. The terminal is used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[0044] 2. Server: This server is responsible for analyzing information received from users, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. This also includes receiving requests for suggestions and managing the progress of follow-up.

[0045] Program processing flow

[0046] Initial setup and user registration

[0047] 1. Terminal: The user installs and launches the application. The "New User Registration" option is displayed on the screen.

[0048] 2. User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[0049] 3. Terminal: Sends the entered information to the server.

[0050] 4. Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[0051] Confirming needs and challenges

[0052] 1. Terminal: After the user logs in, a survey screen regarding DX will be displayed. Question items may include, for example, "Current state of digitalization" and "Issues you want to solve."

[0053] 2. User: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[0054] 3. Terminal: Sends the response content to the server.

[0055] 4. Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[0056] Proposal generation using generative artificial intelligence

[0057] 1. Server: Based on the survey results, the server inputs the data into a generative artificial intelligence. The AI ​​then sets specific tasks such as "optimizing inventory management" or "customer data analysis."

[0058] 2. Server: Generative artificial intelligence generates proposals and identifies the optimal solution. For example, specific solutions such as "implementation of an inventory management system" or "proposal of a customer data analysis tool" are generated.

[0059] 3. Server: Sends the generated proposal to the terminal.

[0060] Specific example

[0061] Digitalization of retail stores

[0062] 1. Terminal: Retail store executives install the app and register company information.

[0063] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[0064] 3. Terminal: Sends the response content to the server.

[0065] 4. Server: Generative artificial intelligence generates solutions, including "implementation of a store inventory management system" and "proposal of a customer data analysis tool," and sends them to the terminal.

[0066] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[0067] 6. User: If you like a proposal, press the "Request Proposal" button.

[0068] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[0069] 8. Server: Sends requests for proposals to service providers and records them in the database.

[0070] 9. Server: You will receive follow-up contact from the service provider's representative.

[0071] Thus, this system is configured to effectively support the digitalization and digital transformation of small and medium-sized enterprises.

[0072] The following describes the processing flow.

[0073] Step 1:

[0074] Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[0075] Step 2:

[0076] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[0077] Step 3:

[0078] Terminal: Sends the entered information to the server.

[0079] Step 4:

[0080] Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[0081] Step 5:

[0082] Terminal: After the user logs in, a survey screen regarding DX is displayed. Question items (e.g., "Current state of digitalization," "Issues you want to solve," etc.) are displayed.

[0083] Step 6:

[0084] User: Answer the survey and enter the required information. Press the "Submit" button.

[0085] Step 7:

[0086] Terminal: Sends the response content to the server.

[0087] Step 8:

[0088] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[0089] Step 9:

[0090] Server: Based on the survey results, input data into the generative artificial intelligence. Set specific tasks for the AI, such as "optimizing inventory management" or "customer data analysis."

[0091] Step 10:

[0092] Server: Generative artificial intelligence generates proposals and identifies the optimal solution. For example, it generates specific solutions such as "implementation of an inventory management system" or "proposal of a customer data analysis tool."

[0093] Step 11:

[0094] Server: Sends the generated proposal to the terminal.

[0095] Step 12:

[0096] Terminal: Displays the generated proposal to the user. Displays details of the proposal (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[0097] Step 13:

[0098] User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[0099] Step 14:

[0100] Terminal: Sends feedback to the server.

[0101] Step 15:

[0102] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[0103] Step 16:

[0104] Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[0105] Step 17:

[0106] Terminal: Sends the entered request for proposal details to the server.

[0107] Step 18:

[0108] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[0109] Step 19:

[0110] Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[0111] Step 20:

[0112] Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[0113] (Example 1)

[0114] 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."

[0115] Many companies are lagging behind in digitalization and digital transformation (DX), and management lacks the means to receive appropriate proposals. Furthermore, there are insufficient mechanisms for management to provide quick and efficient feedback on proposals after they are received, as well as for forwarding requests for proposals to service providers and managing their progress. As a result, digitalization and DX initiatives are delayed, potentially leading to a decline in the overall competitiveness of the company.

[0116] 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.

[0117] In this invention, the server includes means for the user to input company information, means for the user to input needs and challenges related to digitalization and digital transformation, means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon, means for displaying the proposals generated by the generative artificial intelligence to the user, means for the user to input feedback based on the proposals, means for the user to request proposals they like, means for forwarding proposal requests to service providers and managing the progress of follow-up, means for sending details regarding the proposal requests to service providers, means for notifying the user of follow-up from service providers, and means for storing user information and proposal request information in a database. As a result, the user can receive comprehensive digitalization and DX proposals, provide feedback on those proposals, request proposals, and follow up on their progress.

[0118] "Company information" refers to information that identifies a company and indicates its basic attributes and characteristics, such as the company name, address, job title, and contact information.

[0119] "Needs and challenges" refer to the problems and demands that companies face regarding digitalization and digital transformation, including areas for improvement and hurdles to overcome.

[0120] "Generative artificial intelligence" refers to artificial intelligence that has the function of automatically generating suggestions and solutions tailored to a specific purpose based on the input data.

[0121] "Proposal" refers to solutions or improvement plans generated by generative artificial intelligence based on a company's needs and challenges.

[0122] "Feedback" refers to users providing evaluations and opinions on suggestions that have been made.

[0123] A "Request for Proposal" refers to a request from a user to take specific actions to implement a proposal they like.

[0124] A "business operator" refers to a provider of services or products for implementing a proposal, and plays a role in realizing the proposal requested by the user.

[0125] "Follow-up" refers to checking the progress and maintaining contact after a request for proposal has been accepted.

[0126] A "database" refers to an electronic record system that organizes and stores user information and requests for proposals, allowing them to be quickly retrieved when needed.

[0127] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. This system utilizes multiple hardware and software components, and has a function to generate proposals using generative artificial intelligence based on company information, needs, and challenges input by the user, and then provide these proposals to the user. It also provides a means for the user to input feedback on the proposals and to request preferred proposals from service providers.

[0128] Components

[0129] 1. Terminal: A device used by users to input company information, needs, and challenges, and to view and review the generated proposals.

[0130] Examples of hardware used: smartphones, tablets, PCs, etc.

[0131] Examples of software used: applications, web browsers, etc.

[0132] 2. Server: This is the central hub of the system, which analyzes information received from users and generates appropriate suggestions using generative artificial intelligence. It also has the function of receiving requests for suggestions and managing the progress of follow-up with businesses.

[0133] Examples of software used: Apache®, NGINX, Python, generative AI models (e.g., GPT-3®, BERT)

[0134] 3. Database: A system for storing user information and request for proposal information.

[0135] Examples of software used: MySQL®, PostgreSQL

[0136] Initial setup and user registration

[0137] First, the user installs the application on their device and enters basic information such as company name, job title, and contact information. This information is sent from the device to the server, which stores it in a database, generates a user ID, and sends it back to the device.

[0138] Confirming needs and challenges

[0139] After the user logs in, the terminal displays a questionnaire about DX (Digital Transformation). The user answers questions such as "Current state of digitalization" and "Challenges to be solved," and sends the answers to the server. The server analyzes the answers, and a generative artificial intelligence prepares the data necessary for generating suggestions.

[0140] Proposal generation using generative artificial intelligence

[0141] The server inputs data into a generative artificial intelligence (AI) system based on the survey results. This AI then sets specific tasks such as "optimizing inventory management" and "customer data analysis" and generates suggestions. The generated suggestions are sent to the terminal and displayed to the user.

[0142] Feedback and Request for Suggestions

[0143] Users can review the generated proposals and provide feedback, including opinions and evaluations. For proposals they like, they can press the "Request Proposal" button, enter details, and send them to the server. The server then forwards this information to the service provider and manages its progress in a database. Follow-up requests from the service provider are notified to the user's device.

[0144] Specific example

[0145] Digitalization of retail stores

[0146] 1. Terminal: Retail store executives install the app and register company information.

[0147] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[0148] 3. Terminal: Sends the response content to the server.

[0149] 4. Server: Generative artificial intelligence generates solutions, including "implementation of a store inventory management system" and "proposal of a customer data analysis tool," and sends them to the terminal.

[0150] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[0151] 6. User: If you like a proposal, press the "Request Proposal" button.

[0152] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[0153] 8. Server: Sends requests for proposals to service providers and records them in the database.

[0154] 9. Server: You will receive follow-up contact from the service provider's representative.

[0155] Example of a prompt

[0156] The following text format is used as an example of a prompt message.

[0157] "Please propose ways to improve the efficiency of inventory management in retail stores."

[0158] "Please tell me how to optimize sales strategies through customer data analysis."

[0159] These prompts enable the generative AI model to generate proposals tailored to the company's needs.

[0160] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0161] Program processing flow

[0162] Initial setup and user registration

[0163] Step 1:

[0164] Subject: terminal

[0165] Process details: The user installs and launches the application.

[0166] Input: Tap the application icon

[0167] Output: Display the app's home screen.

[0168] Specific operation: When the user selects and taps an application from the device's home screen, the application launches and displays the new user registration screen.

[0169] Step 2:

[0170] Subject: User

[0171] Process details: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[0172] Input: Company name, job title, contact information

[0173] Output: Send input information

[0174] Specific operation: The user enters data into each form field and finally clicks the "Register" button.

[0175] Step 3:

[0176] Subject: terminal

[0177] Processing details: The entered information is sent to the server.

[0178] Input: Company information entered by the user

[0179] Output: HTTPS request to the server

[0180] Specific operation: The terminal temporarily stores the input data in memory, creates an HTTPS request, and sends it to the server.

[0181] Step 4:

[0182] Subject: Server

[0183] Processing details: The received user information is saved to the database, a user ID is generated, and it is sent back to the terminal.

[0184] Input: User information

[0185] Output: User ID

[0186] Specific operation: The server inserts the received information into the database, generates a new user ID (such as a UUID), and returns it to the terminal as a response.

[0187] Confirming needs and challenges

[0188] Step 1:

[0189] Subject: terminal

[0190] Processing details: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed.

[0191] Enter: Login information

[0192] Output: Survey screen

[0193] Specific behavior: If user authentication is successful, the survey screen will appear as a pop-up or in a new window.

[0194] Step 2:

[0195] Subject: User

[0196] Process: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[0197] Input: Needs and challenges related to DX

[0198] Output: Submitted response

[0199] Specific actions: The user answers questions using text areas or checkboxes and taps the "Submit" button.

[0200] Step 3:

[0201] Subject: terminal

[0202] Processing details: Send the response content to the server.

[0203] Input: User survey responses

[0204] Output: HTTPS request to the server

[0205] Specific operation: The device temporarily stores the survey data in memory, creates an HTTPS request, and sends it to the server.

[0206] Step 4:

[0207] Subject: Server

[0208] Processing details: The response content is analyzed, and the generative artificial intelligence prepares the data necessary for generating suggestions.

[0209] Input: Survey response data

[0210] Output: Analysis data for proposal generation

[0211] Specific operation: The server uses a natural language processing algorithm to analyze the response and converts the analysis results into a format suitable as input for an AI model.

[0212] Proposal generation using generative artificial intelligence

[0213] Step 1:

[0214] Subject: Server

[0215] Processing details: Based on the survey results, the data is input into a generative artificial intelligence system.

[0216] Input: Analyzed survey results

[0217] Output: Input data for AI

[0218] Specific operation: Convert data into the format required by the AI ​​model (JSON or a specific format) and provide it as input.

[0219] Step 2:

[0220] Subject: Server

[0221] Processing details: Generative artificial intelligence generates proposals and identifies the optimal solution.

[0222] Input: Input data for AI

[0223] Output: Generated proposals

[0224] Specific operation: The AI ​​model executes a proposal generation algorithm and outputs solutions tailored to the company's needs in text format.

[0225] Step 3:

[0226] Subject: Server

[0227] Processing details: Send the generated suggestions to the terminal.

[0228] Input: Generated proposal

[0229] Output: Suggestion data to the terminal

[0230] Specific operation: Format the proposed data in JSON format and send it to the terminal as an HTTPS response.

[0231] Feedback and Request for Suggestions

[0232] Step 1:

[0233] Subject: terminal

[0234] Processing details: The user reviews the proposal and provides feedback such as, "This looks good."

[0235] Input: Generated proposal

[0236] Output: Feedback input screen

[0237] Specific action: The user scrolls to review the suggestions and enters comments in the feedback text area.

[0238] Step 2:

[0239] Subject: User

[0240] Processing steps: Click the "Request Proposal" button for any proposals you like.

[0241] Input: Suggestion

[0242] Output: Request for Proposal Details Input Screen

[0243] Specific operation: The user clicks the "Request a Proposal" button and is redirected to a detailed input form that appears as a pop-up.

[0244] Step 3:

[0245] Subject: terminal

[0246] Processing details: Enter the details of the request for proposal and send them to the server.

[0247] Input: Request for Proposal Details

[0248] Output: Request for Proposal data to the server

[0249] Specific operation: The data from the detailed input form is temporarily stored in memory, and an HTTPS request is created and sent to the server.

[0250] Step 4:

[0251] Subject: Server

[0252] Processing details: Send a request for proposal to a business and record it in the database.

[0253] Input: Request for Proposal Data

[0254] Output: Request for proposal notification to businesses, database record

[0255] Specific operation: Save the proposal request details to the database and simultaneously send notifications to businesses via email or API call.

[0256] Step 5:

[0257] Subject: Server

[0258] Processing details: Notify the user of follow-up from the service provider.

[0259] Input: Follow-up information from the business operator

[0260] Output: Notification to the user

[0261] Specific actions: Receive communications from businesses and send push notifications or emails to users.

[0262] This enables the system to effectively generate digitalization and digital transformation proposals tailored to user needs, and to consistently manage the feedback and request for proposal processes.

[0263] (Application Example 1)

[0264] 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."

[0265] This system aims to solve the problem of companies lagging behind in traditional digitalization and digital transformation finding it difficult to effectively receive proposals for digitalization and digital transformation. It also aims to provide a system that enables logistics centers and field personnel to receive accurate, real-time proposals to address challenges in improving the efficiency of inventory management and shipping operations.

[0266] 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.

[0267] In this invention, the server includes means for a user to input company information, means for a user to input needs and challenges related to digitalization and digital transformation, means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon, means for displaying the proposals generated by the generative artificial intelligence to the user, means for a user to input feedback based on the proposals, means for a user to request proposals they like, means for forwarding proposal requests to businesses and managing the progress of follow-up, means for a user to input on-site conditions and needs via a smart device and check the generated proposals in real time, and means for creating prompt sentences for the generative artificial intelligence to generate proposals regarding the efficiency of the logistics center. This enables companies and logistics centers to efficiently receive proposals for digitalization and digital transformation, and to optimize operations and improve efficiency.

[0268] "Company information" refers to basic company information entered by the user, including company name, job title, contact information, etc.

[0269] "Digitalization" means streamlining analog and manual business processes using digital technology.

[0270] "Digital transformation" refers to a company fundamentally changing its business model and operational processes by utilizing digital technologies.

[0271] "Challenges" refer to specific problems or needs that users wish to solve in the context of digitalization and digital transformation.

[0272] "Generative artificial intelligence" is an artificial intelligence technology that automatically generates optimal suggestions based on input data.

[0273] A "proposal" refers to a solution or solution generated by generative artificial intelligence in response to a company's needs and challenges.

[0274] "Feedback" refers to the evaluations and opinions that users provide regarding the generated suggestions.

[0275] A "Request for Proposal" is an action taken by a user to ask a business to implement a proposal they like.

[0276] A "smart device" refers to a device such as a smartphone or head-mounted display that allows the user to input on-site conditions and needs, and then view the generated suggestions in real time.

[0277] A "prompt statement" is an instruction given to a generative artificial intelligence system to generate specific suggestions.

[0278] "Inventory management" refers to the process of properly managing inventory levels in a logistics center and replenishing or ordering products at the optimal time.

[0279] "Shipping operations" refers to the process of preparing and processing shipments of goods at a logistics center.

[0280] This invention relates to a system that allows field personnel at a logistics center to receive suggestions for efficiency improvements using smart devices. The system is configured so that the user (field personnel) inputs the situation, needs, and challenges at the site through a device such as a smartphone or head-mounted display, and based on that, generative artificial intelligence proposes the optimal solution.

[0281] Hardware environment and software configuration

[0282] 1. Terminal: It is a device such as a smartphone or a head-mounted display that a user uses on-site. With this, corporate information, needs, and issues can be input, and the generated proposals can be confirmed in real time.

[0283] 2. Server: It operates on the cloud and analyzes the information received from the user to generate proposals. Specifically, cloud services such as Amazon Web Services (AWS (registered trademark)) are used.

[0284] 3. Generative AI: Using a generative AI model such as GPT-3 of OpenAI (registered trademark), appropriate proposals are generated based on the user's input. For this, a prompt sentence is generated based on the data input by the user and input into the AI model.

[0285] 4. Application: Installed on the terminal, it provides an interface for the user to input corporate information and on-site issues, receive proposals, and provide feedback. The application is developed using a cross-platform framework such as React Native or Flutter (registered trademark).

[0286] Flow of processing

[0287] 1. User input:

[0288] The user uses the application installed on the smart device to input corporate information, on-site situations, needs, and issues.

[0289] 2. Data transmission:

[0290] The terminal transmits the input information to the server. The data is sent through a secure communication protocol (for example, HTTPS).

[0291] 3. Analysis and prompt sentence generation:

[0292] The server cleans up and normalizes the received data and generates a prompt sentence for input into the generative artificial intelligence.

[0293] 4. Proposal Generation:

[0294] The generative artificial intelligence generates an optimal proposal based on the prompt sentence and returns it to the server in JSON format.

[0295] 5. Proposal Display:

[0296] The server sends the generated proposal to the user's terminal so that the user can view it in real time.

[0297] 6. Feedback and Requests:

[0298] The user inputs feedback on the generated proposal and sends a proposal request to implement the proposals they like.

[0299] Specific Example

[0300] Example of Prompt Sentence

[0301] "Please generate proposals to improve the on-site efficiency of the logistics center. The following are the main issues and requirements from the site.

[0302] The inventory management system is old and inefficient

[0303] There are many mistakes in the shipping operation

[0304] It is difficult to design an efficient delivery route

[0305] Requirements:

[0306] 1. Optimization of inventory management

[0307] 2. Reduction of shipping mistakes

[0308] 3. Efficiency improvement of delivery routes"

[0309] By inputting the above prompts into a generative artificial intelligence system, the AI ​​generates suggestions such as updating inventory management systems, checklist tools to reduce shipping errors, and AI-based delivery route design tools.

[0310] This invention contributes to an efficient solution proposal system that utilizes generative artificial intelligence to solve real-world problems in logistics centers in real time.

[0311] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0312] Step 1:

[0313] The user launches an application installed on their smart device and inputs company information, on-site conditions, needs, and challenges.

[0314] Input: Company name, job title, contact information, on-site situation, challenges / needs

[0315] Output: Input data in JSON format

[0316] Specific operation: The user follows the interface, enters the required information into the form, and presses the "Submit" button.

[0317] Step 2:

[0318] The terminal sends the entered information to the server.

[0319] Input: JSON format data containing company information, on-site conditions, and challenges / needs entered by the user.

[0320] Output: HTTP request to the server

[0321] Specific operation: The terminal uses the HTTPS protocol to send input data to the server's API endpoint.

[0322] Step 3:

[0323] The server cleans and normalizes the data it receives.

[0324] Input: JSON format data sent from the device.

[0325] Output: Cleaned and normalized data

[0326] Specific operation: The server checks the data format and invalid values, and converts them to the correct format.

[0327] Step 4:

[0328] The server generates prompt text to be input to the generative artificial intelligence based on cleaned and normalized data.

[0329] Input: Cleaned and normalized data

[0330] Output: Prompt text to input to the generative artificial intelligence.

[0331] Specific operation: The server generates a prompt message with the input data embedded, based on a template.

[0332] Step 5:

[0333] The generative artificial intelligence generates the optimal suggestion based on the prompt text.

[0334] Input: Prompt message

[0335] Output: Generated proposals (in JSON format)

[0336] Specific operation: The generative artificial intelligence analyzes the prompt text and generates an appropriate solution as a suggestion.

[0337] Step 6:

[0338] The server sends the generated proposal to the user's terminal.

[0339] Input: Generated suggestions (in JSON format)

[0340] Output: Suggestion data sent to the user's terminal.

[0341] Specific operation: The server uses the HTTPS protocol to send the generated proposal to the user's terminal.

[0342] Step 7:

[0343] The device displays suggestions it has received to the user.

[0344] Input: Proposal data sent from the server

[0345] Output: Suggestions displayed to the user

[0346] Specific operation: The terminal analyzes the received suggestion data and displays it through the user interface.

[0347] Step 8:

[0348] Users provide feedback on the generated proposals and press the "Request Proposal" button to implement the proposals they like.

[0349] Input: Feedback, details of the request for proposal

[0350] Output: Feedback and suggestion data sent to the server

[0351] Specific operation: The user reviews the proposal, enters details of feedback or a request for proposal on the interface, and submits it.

[0352] Step 9:

[0353] The server forwards user feedback and requests for suggestions to the service provider and manages the progress of follow-up.

[0354] Input: Feedback, Request for Proposal data

[0355] Output: Data for managing the progress of communication and follow-up with service providers.

[0356] Specific operation: The server forwards the received feedback and requests for suggestions to the relevant service providers and updates the database for progress management.

[0357] 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.

[0358] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. This system has a function where the user inputs company information, needs, and challenges, and based on this, generative artificial intelligence generates proposals and displays them to the user. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, it can provide more personalized proposals.

[0359] System Configuration

[0360] 1. Terminal: A device on which an application is installed and which the user operates through an interface. The terminal is used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[0361] 2. Server: This server is responsible for analyzing information received from the user, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. It also receives requests for suggestions and manages the progress of follow-up. Furthermore, an emotion engine is integrated into the server to analyze the user's emotions.

[0362] 3. Emotion Engine: This engine recognizes and analyzes emotions through user input and actions. This emotional information is provided to the generative artificial intelligence, which adjusts the suggested content and presentation methods based on the user's emotions.

[0363] Program processing flow

[0364] Initial setup and user registration

[0365] 1. Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[0366] 2. User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[0367] 3. Terminal: Sends the entered information to the server.

[0368] 4. Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[0369] Confirming needs and challenges

[0370] 1. Terminal: After the user logs in, a survey screen regarding DX will be displayed. Question items (e.g., "Current state of digitalization," "Issues you want to solve," etc.) will be displayed.

[0371] 2. User: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[0372] 3. Terminal: Sends the response content to the server.

[0373] 4. Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[0374] Proposal generation using generative artificial intelligence and an emotion engine.

[0375] 1. Server: Based on survey results and user input data, the server inputs the data into a generative artificial intelligence. The AI ​​is then given specific tasks such as "optimizing inventory management" or "customer data analysis."

[0376] 2. Server: The emotion engine analyzes user input and actions to understand emotions and provides that emotional information to the generative artificial intelligence.

[0377] 3. Server: Generative artificial intelligence considers the user's emotional information to generate suggestions and identify the optimal solution. For example, specific solutions such as "implementation of an inventory management system" or "suggestion of a customer data analysis tool" are generated.

[0378] 4. Server: Sends the generated proposal to the terminal.

[0379] Display of proposals and feedback

[0380] 1. Terminal: Displays the generated proposal to the user. Displays details of the proposal content (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[0381] 2. User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[0382] 3. Terminal: Sends the feedback content to the server.

[0383] Request for Proposal and Follow-up

[0384] 1. User: If satisfied with the proposal, press the "Request Proposal" button.

[0385] 2. Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[0386] 3. Terminal: Sends the entered proposal request details to the server.

[0387] 4. Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[0388] 5. Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[0389] 6. Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[0390] Specific example

[0391] Digitalization of retail stores and emotion recognition

[0392] 1. Terminal: Retail store executives install the app and register company information.

[0393] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[0394] 3. Terminal: Sends the response content and user input data to the server.

[0395] 4. Server: Consider that the generative AI generates solutions including "implementation of store inventory management systems" and "proposals for customer data analysis tools," and the emotion engine provides user emotion data.

[0396] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[0397] 6. User: If you like a proposal, press the "Request Proposal" button.

[0398] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[0399] 8. Server: Sends requests for proposals to service providers and records them in the database.

[0400] 9. Server: You will receive follow-up contact from the service provider's representative.

[0401] Thus, this system is configured to effectively support the digitalization and digital transformation of small and medium-sized enterprises. Furthermore, by recognizing user emotions and reflecting that information in suggestion generation, it is possible to provide more personalized suggestions.

[0402] The following describes the processing flow.

[0403] Step 1:

[0404] Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[0405] Step 2:

[0406] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[0407] Step 3:

[0408] Terminal: Sends the entered information to the server.

[0409] Step 4:

[0410] Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[0411] Step 5:

[0412] Terminal: After the user logs in, a survey screen regarding DX is displayed. Question items (e.g., "Current state of digitalization," "Issues you want to solve," etc.) are displayed.

[0413] Step 6:

[0414] User: Answer the survey and enter the required information. Press the "Submit" button.

[0415] Step 7:

[0416] Terminal: Sends the response content to the server.

[0417] Step 8:

[0418] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[0419] Step 9:

[0420] Server: Based on the survey results, input data into the generative artificial intelligence. Set specific tasks for the AI, such as "optimizing inventory management" or "customer data analysis."

[0421] Step 10:

[0422] Server: The emotion engine analyzes user emotions from input and actions and provides that emotional information to the generative artificial intelligence.

[0423] Step 11:

[0424] Server: Generative artificial intelligence considers user sentiment information to generate suggestions and identify the optimal solution. For example, it generates specific solutions such as "implementing an inventory management system" or "proposing a customer data analysis tool."

[0425] Step 12:

[0426] Server: Sends the generated proposal to the terminal.

[0427] Step 13:

[0428] Terminal: Displays the generated proposal to the user. Displays details of the proposal (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[0429] Step 14:

[0430] User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[0431] Step 15:

[0432] Terminal: Sends feedback to the server.

[0433] Step 16:

[0434] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[0435] Step 17:

[0436] Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[0437] Step 18:

[0438] Terminal: Sends the entered request for proposal details to the server.

[0439] Step 19:

[0440] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[0441] Step 20:

[0442] Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[0443] Step 21:

[0444] Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[0445] (Example 2)

[0446] 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".

[0447] In modern businesses, digitalization and digital transformation (DX) are essential for improving operational efficiency and maintaining competitiveness. However, especially in small and medium-sized enterprises (SMEs), management often lacks sufficient knowledge and resources for these transformations, frequently delaying the implementation of DX. Furthermore, standard DX proposals alone are insufficient to adequately address the unique challenges and needs of each company, making it difficult to provide optimal solutions. Moreover, conventional proposal systems fail to adequately reflect user emotions and feedback, resulting in insufficient personalization.

[0448] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server has an emotion engine that analyzes emotions from user input and operations, and includes means for providing emotion information to the generative artificial intelligence, means for adjusting the proposed content and presentation method based on the emotion information, and means for forwarding the proposal request to the business operator and managing the progress of follow-up. As a result, not only is the optimal digitalization and DX proposal for the user's specific needs and challenges generated, but personalized proposals and feedback that take the user's emotions into consideration are also possible.

[0449] "Digitalization" refers to managing a company's business processes and information electronically to improve efficiency and automate them.

[0450] "Digital transformation (DX)" refers to fundamentally changing a company's business processes and business models by utilizing digital technologies to improve its competitiveness.

[0451] "Company information" refers to basic information used to identify a company, such as its name, job title, and contact information.

[0452] "Needs and challenges" refer to a company's requirements and problems related to digitalization and digital transformation.

[0453] "Generative artificial intelligence" refers to artificial intelligence that has algorithms for generating optimal digitalization and DX proposals based on data input from users.

[0454] An "emotion engine" refers to a system that analyzes emotions from user input and actions and provides that information to a generative artificial intelligence system.

[0455] "Proposal" refers to a specific solution generated by generative artificial intelligence based on the user's needs and challenges.

[0456] "Feedback" refers to the opinions and evaluations that users provide regarding the proposed content.

[0457] A "Request for Proposal" refers to a request for specific actions based on a proposal that the user likes.

[0458] "Follow-up" refers to managing the progress of the business's implementation of the requested proposal and notifying the user of that progress.

[0459] System Overview

[0460] This invention provides a system that enables management in companies lagging behind in digitalization and digital transformation (DX) to more effectively receive proposals for digitalization and DX. The system includes an interface for users to input company information, needs, and challenges, a generative artificial intelligence, an emotion engine, and follow-up management functions.

[0461] Hardware and software to be used

[0462] This system includes the following components:

[0463] Terminal: A device on which an application is installed and which the user operates through an interface. Terminals are used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[0464] Examples of use: smartphones, tablets, and personal computers.

[0465] Example of software used: Application interface.

[0466] The server is responsible for analyzing information received from the user, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. It also receives requests for suggestions and manages the progress of follow-up. Furthermore, an emotion engine is integrated into the server to analyze the user's emotions.

[0467] Examples of use: cloud servers, on-premises servers.

[0468] Examples of software used: database management systems, artificial intelligence models (generative AI), and sentiment analysis engines.

[0469] Emotion Engine: This engine recognizes and analyzes emotions through user input and actions. This emotional information is provided to a generative artificial intelligence system, which adjusts the suggested content and presentation methods based on the user's emotions.

[0470] Examples of use: machine learning models, sentiment analysis algorithms.

[0471] System Operation Overview

[0472] 1. Initial setup and user registration

[0473] Terminal: The user installs and launches the application, and the new user registration screen is displayed.

[0474] User: Enter company name, job title, contact information, etc., and press the "Register" button.

[0475] Terminal: Sends the entered information to the server.

[0476] Server: Saves user information to the database, generates a new user ID, and sends it back.

[0477] 2. Identifying needs and challenges

[0478] Terminal: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed.

[0479] User: Answer the questionnaire and enter your specific needs and challenges.

[0480] Terminal: Sends the response content to the server.

[0481] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[0482] 3. Proposal generation using generative artificial intelligence and an emotion engine

[0483] Server: Based on survey results and user input data, it inputs data into the generative artificial intelligence.

[0484] Server: The emotion engine analyzes emotional information obtained from user input and actions and provides it to the generative artificial intelligence.

[0485] Server: Generative artificial intelligence generates suggestions while considering the user's emotional information.

[0486] Server: Sends the generated proposal to the terminal.

[0487] 4. Display of proposals and feedback

[0488] Terminal: Displays generated suggestions to the user.

[0489] User: Review the proposal and enter your feedback.

[0490] Terminal: Sends feedback to the server.

[0491] 5. Request for Proposal and Follow-up

[0492] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[0493] Terminal: Displays a form for entering details of the "Request for Proposal," and the user enters the details and submits it.

[0494] Terminal: Sends the entered request for proposal details to the server.

[0495] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[0496] Server: Sends a request for proposal notification to the service provider's representative and follows up.

[0497] Server: Manages the progress of follow-ups and notifies users as needed.

[0498] Specific example

[0499] Examples of use in the retail industry

[0500] 1. Terminal: Retail store executives install the app and register company information.

[0501] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[0502] 3. Terminal: Sends the response content and user input data to the server.

[0503] 4. Server: Consider that the generative AI generates solutions including "implementation of store inventory management systems" and "proposals for customer data analysis tools," and the emotion engine provides user emotion data.

[0504] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[0505] 6. User: If you like a proposal, press the "Request Proposal" button.

[0506] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[0507] 8. Server: Sends requests for proposals to service providers and records them in the database.

[0508] 9. Server: You will receive follow-up contact from the service provider's representative.

[0509] Example of a prompt

[0510] "Our company is struggling with efficient inventory management and has challenges in analyzing customer data. Please provide specific suggestions for solving these problems."

[0511] In this way, this system can address the individual needs of companies and, by taking emotional information into consideration, provide more personalized digitalization and DX proposals.

[0512] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0513] Processing steps

[0514] Initial setup and user registration

[0515] Step 1:

[0516] Terminal: The user installs and launches a system-specific application, and the "New User Registration" button is displayed.

[0517] Input: The user installs and launches the application.

[0518] Output: The "New User Registration" button will appear on the app's initial launch screen.

[0519] Step 2:

[0520] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[0521] Input: User's basic information (company name, job title, contact information).

[0522] Output: Registration information is sent to the terminal.

[0523] Step 3:

[0524] Terminal: Sends the entered information to the server.

[0525] Input: User's basic information.

[0526] Output: User information is sent to the server.

[0527] Step 4:

[0528] Server: Stores the received user information in the database, generates a new user ID, and sends it back.

[0529] Input: User information received from the terminal.

[0530] Output: Information stored in the database and a new user ID.

[0531] Confirming needs and challenges

[0532] Step 1:

[0533] Terminal: After the user logs in, a survey screen about DX (Digital Transformation) will be displayed. Questions will include "Current state of digitalization" and "Challenges you want to solve."

[0534] Input: User login information.

[0535] Output: The survey screen is displayed.

[0536] Step 2:

[0537] User: Answer the questionnaire, enter specific needs and challenges in the text box, and press the "Submit" button.

[0538] Input: Survey responses.

[0539] Output: The answer is entered into the terminal.

[0540] Step 3:

[0541] Terminal: Sends the response content to the server.

[0542] Input: Survey responses.

[0543] Output: The response is sent to the server.

[0544] Step 4:

[0545] Server: Receives the response content, analyzes it, and prepares the data necessary for the generative artificial intelligence to generate proposals.

[0546] Input: Answer content.

[0547] Output: Data is prepared for input into a generative artificial intelligence.

[0548] Proposal generation using generative artificial intelligence and an emotion engine.

[0549] Step 1:

[0550] Server: Inputs data into a generative artificial intelligence system based on survey results and user input data. The AI ​​then sets specific tasks (e.g., "Optimize inventory management," "Analyze customer data").

[0551] Input: Survey results and user input data.

[0552] Output: Data input to a generative artificial intelligence.

[0553] Step 2:

[0554] Server: The emotion engine analyzes emotional information obtained from user input and actions, and provides that information to the generative artificial intelligence.

[0555] Input: User sentiment information.

[0556] Output: Emotional information provided to the generative artificial intelligence.

[0557] Step 3:

[0558] Server: Generative artificial intelligence generates suggestions while considering the user's emotional information. For example, "Implementation of an inventory management system" or "Suggestion of a customer data analysis tool."

[0559] Input: Survey results, user sentiment information.

[0560] Output: Generated proposals.

[0561] Step 4:

[0562] Server: Sends the generated proposal to the terminal.

[0563] Input: Generated suggestions.

[0564] Output: Suggestions sent to the terminal.

[0565] Display of proposals and feedback

[0566] Step 1:

[0567] Terminal: Displays generated proposals to the user. The proposals include detailed information such as "Overview of the inventory management system" and "Benefits of implementation."

[0568] Input: Suggestions sent from the server.

[0569] Output: The suggested content is displayed to the user.

[0570] Step 2:

[0571] User: Review the proposal and check the feedback. Enter comments such as "This looks good" or "I'd like more specific information," and submit.

[0572] Input: User feedback.

[0573] Output: Feedback entered into the terminal.

[0574] Step 3:

[0575] Terminal: Sends feedback to the server.

[0576] Input: Feedback content.

[0577] Output: Feedback sent to the server.

[0578] Request for Proposal and Follow-up

[0579] Step 1:

[0580] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[0581] Input: User action (pressing the "Request Proposal" button).

[0582] Output: The Request for Proposal screen is displayed.

[0583] Step 2:

[0584] Terminal: A form is displayed for the user to enter details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[0585] Input: Details of the Request for Proposal.

[0586] Output: Details of the request for proposal entered into the terminal.

[0587] Step 3:

[0588] Terminal: Sends the entered request for proposal details to the server.

[0589] Input: Details of the Request for Proposal.

[0590] Output: Details of the request for proposal sent to the server.

[0591] Step 4:

[0592] Server: Transfers the details of the Request for Proposal to the service provider and records the relevant data in the database.

[0593] Input: Details of the Request for Proposal.

[0594] Output: Details of the Request for Proposal forwarded to the service provider, and data recorded in the database.

[0595] Step 5:

[0596] Server: Sends a request for proposal notification to the service provider's representative, and the follow-up representative takes specific actions.

[0597] Input: Details of the Request for Proposal.

[0598] Output: Notification to the business representative and follow-up actions.

[0599] Step 6:

[0600] Server: Manages the progress of follow-ups and notifies users as needed. This includes updating statuses such as "An agent will contact you shortly."

[0601] Input: Follow-up progress.

[0602] Output: Notifications to the user and status updates.

[0603] (Application Example 2)

[0604] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0605] In today's world, many companies are lagging behind in digitalization and digital transformation (DX). This lag is particularly pronounced in small and medium-sized enterprises (SMEs), resulting in decreased competitiveness and operational efficiency. Furthermore, management lacks a suitable system for receiving concrete solution proposals, making it difficult to promote digitalization. Moreover, proposals are often uniform and do not align with the feelings and needs of management. A system is needed to solve these problems.

[0606] 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.

[0607] In this invention, the server includes means for the user to input corporate information, means for the user to input needs and challenges related to digitalization and digital transformation, means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon, means incorporating an emotion recognition engine that analyzes the user's input information and emotion information to generate personalized proposals, means for displaying the proposals generated by the generative artificial intelligence to the user, means for the user to input feedback based on the proposals, means for the user to request proposals they like, and means for forwarding proposal requests to service providers and managing the progress of follow-up. This makes it possible for users to receive personalized proposals based on their specific needs and emotions, thereby effectively advancing the digitalization and digital transformation of companies.

[0608] "Means for inputting company information" refers to interfaces or data entry systems for inputting basic company information.

[0609] "Means for inputting needs and challenges" refers to interfaces or database systems that allow users to input their needs and challenges related to digitalization and digital transformation.

[0610] "Generative artificial intelligence" is a type of artificial intelligence that analyzes input data and generates optimal suggestions based on that analysis.

[0611] "Methods for incorporating an emotion recognition engine" refers to methods for integrating an engine into the system that recognizes emotions from user input information and reflects that emotion data in suggestion generation.

[0612] "Means for displaying proposals to users" refers to displays and interfaces that make generated proposals easy for users to understand.

[0613] "Means for inputting feedback" refer to interfaces or data collection systems that allow users to input reactions and opinions on suggestions.

[0614] "Means for requesting proposals" refers to interfaces and notification systems that allow users to actually request proposals they like.

[0615] "Means for forwarding requests for proposals to service providers and managing the progress of follow-up" refers to systems and servers that forward user requests for proposals to service providers and manage and monitor their subsequent progress.

[0616] This invention is a system for management in companies lagging behind in digitalization and digital transformation to receive proposals for digitalization and DX. The system has a function where the user inputs company information, needs, and challenges, and based on this, generative artificial intelligence generates optimal proposals, which are then displayed to the user. Furthermore, by combining this with an emotion recognition engine that recognizes the user's emotions, it can provide more personalized proposals.

[0617] System Configuration

[0618] 1. Terminal

[0619] A terminal is a device on which an application is installed and which the user operates through an interface. This terminal is equipped with means for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[0620] 2. Server

[0621] The server is responsible for analyzing information received from the user, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. It also receives requests for suggestions and manages the progress of follow-up. Furthermore, an emotion recognition engine is integrated into the server to analyze the user's emotions.

[0622] 3. Emotion Recognition Engine

[0623] The emotion recognition engine recognizes and analyzes emotions through user input and actions. This emotion information is provided to a generative artificial intelligence system, which then adjusts the suggested content and presentation methods based on the user's emotions.

[0624] Program processing and hardware / software

[0625] The system utilizes Flask as its framework and OpenAI's GPT-3 for generative artificial intelligence. It incorporates EmotionEngine as its emotion recognition engine to recognize and analyze user emotions.

[0626] Examples of specific cases and prompt statements

[0627] Specific example:

[0628] 1. User: Owner of a physical store. During registration, they entered "Inventory management is not efficient" and "Customer data analysis is difficult."

[0629] 2. Emotions: Emotions such as "anxiety" and "anticipation" are recognized from the user's input.

[0630] 3. Based on this user information, the generative artificial intelligence creates personalized suggestions.

[0631] Example of a prompt:

[0632] User Data: Inventory management is not efficient, customer data analysis is difficult.

[0633] User Emotion: Anxiety, Anticipation

[0634] Generate a personalized DX proposal for the user based on their input and emotion.

[0635] In this way, users can receive personalized suggestions based on their specific needs and emotions, which can effectively advance the company's digitalization and digital transformation.

[0636] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0637] Step 1:

[0638] User Registration

[0639] The user uses a terminal to enter basic information such as company name, job title, and contact information. The terminal receives this information and sends it to the server. The server stores the received information in a database, generates a user ID, and sends it back to the terminal.

[0640] Input: Company name, job title, contact information

[0641] Output: User ID

[0642] Step 2:

[0643] Inputting needs and challenges

[0644] The user uses a terminal to input their needs and challenges regarding digitalization and digital transformation. The terminal sends this information to a server. The server analyzes the received needs and challenges and prepares data for generative artificial intelligence to generate suggestions.

[0645] Input: Needs and challenges related to digitalization and DX

[0646] Output: Data required for proposal generation

[0647] Step 3:

[0648] emotion recognition

[0649] An emotion recognition engine embedded in the server analyzes the user's input information and recognizes the user's emotions. The recognized emotion information is then provided to a generative artificial intelligence system. As a result, suggestions are personalized based on the user's emotions.

[0650] Input: User input information

[0651] Output: User sentiment information

[0652] Step 4:

[0653] Proposal generation using generative artificial intelligence

[0654] The server inputs data into the generative artificial intelligence (AI) based on the user's needs and challenges. The generative AI then generates appropriate suggestions using prompts. For example, it might generate suggestions for optimizing inventory management or analyzing customer data.

[0655] Input: User needs, challenges, and emotional information

[0656] Output: Personalized suggestions

[0657] Step 5:

[0658] Display of proposals and feedback

[0659] The terminal displays the generated suggestions to the user. The user reviews the suggestions and enters feedback. The terminal sends this feedback to the server. The server analyzes the received feedback and updates the suggestions as needed.

[0660] Input: User feedback

[0661] Output: Updated proposal

[0662] Step 6:

[0663] Request for Proposal and Follow-up

[0664] To request a proposal they like, the user enters details using a terminal. The terminal sends this information to the server. The server forwards the request for proposal to the service provider and records it in a database. It also manages the progress of follow-up and notifies the user as needed.

[0665] Input: Details of the Request for Proposal (e.g., desired implementation period, budget, etc.)

[0666] Output: Forwarding of Request for Proposal, follow-up progress notification

[0667] 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.

[0668] 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.

[0669] 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.

[0670] [Second Embodiment]

[0671] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0672] 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.

[0673] 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).

[0674] 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.

[0675] 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.

[0676] 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).

[0677] 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.

[0678] 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.

[0679] 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.

[0680] 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.

[0681] 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.

[0682] 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".

[0683] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. The system has a function where the user inputs company information, needs, and challenges, and based on this, a generative artificial intelligence generates proposals, which are then displayed to the user. It also provides a means for the user to input feedback on the proposals and request the preferred proposals from service providers.

[0684] System Configuration

[0685] 1. Terminal: A device on which an application is installed and which the user operates through an interface. The terminal is used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[0686] 2. Server: This server is responsible for analyzing information received from users, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. This also includes receiving requests for suggestions and managing the progress of follow-up.

[0687] Program processing flow

[0688] Initial setup and user registration

[0689] 1. Terminal: The user installs and launches the application. The "New User Registration" option is displayed on the screen.

[0690] 2. User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[0691] 3. Terminal: Sends the entered information to the server.

[0692] 4. Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[0693] Confirming needs and challenges

[0694] 1. Terminal: After the user logs in, a survey screen regarding DX will be displayed. Question items may include, for example, "Current state of digitalization" and "Issues you want to solve."

[0695] 2. User: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[0696] 3. Terminal: Sends the response content to the server.

[0697] 4. Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[0698] Proposal generation using generative artificial intelligence

[0699] 1. Server: Based on the survey results, the server inputs the data into a generative artificial intelligence. The AI ​​then sets specific tasks such as "optimizing inventory management" or "customer data analysis."

[0700] 2. Server: Generative artificial intelligence generates proposals and identifies the optimal solution. For example, specific solutions such as "implementation of an inventory management system" or "proposal of a customer data analysis tool" are generated.

[0701] 3. Server: Sends the generated proposal to the terminal.

[0702] Specific example

[0703] Digitalization of retail stores

[0704] 1. Terminal: Retail store executives install the app and register company information.

[0705] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[0706] 3. Terminal: Sends the response content to the server.

[0707] 4. Server: Generative artificial intelligence generates solutions, including "implementation of a store inventory management system" and "proposal of a customer data analysis tool," and sends them to the terminal.

[0708] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[0709] 6. User: If you like a proposal, press the "Request Proposal" button.

[0710] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[0711] 8. Server: Sends requests for proposals to service providers and records them in the database.

[0712] 9. Server: You will receive follow-up contact from the service provider's representative.

[0713] Thus, this system is configured to effectively support the digitalization and digital transformation of small and medium-sized enterprises.

[0714] The following describes the processing flow.

[0715] Step 1:

[0716] Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[0717] Step 2:

[0718] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[0719] Step 3:

[0720] Terminal: Sends the entered information to the server.

[0721] Step 4:

[0722] Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[0723] Step 5:

[0724] Terminal: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed. Question items (e.g., "Current digitalization status," "Issues you want to solve," etc.) will be displayed.

[0725] Step 6:

[0726] User: Answer the survey and enter the required information. Press the "Submit" button.

[0727] Step 7:

[0728] Terminal: Sends the response content to the server.

[0729] Step 8:

[0730] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[0731] Step 9:

[0732] Server: Based on the survey results, input data into the generative artificial intelligence. Set specific tasks for the AI, such as "optimizing inventory management" or "customer data analysis."

[0733] Step 10:

[0734] Server: Generative artificial intelligence generates proposals and identifies the optimal solution. For example, it generates specific solutions such as "implementation of an inventory management system" or "proposal of a customer data analysis tool."

[0735] Step 11:

[0736] Server: Sends the generated proposal to the terminal.

[0737] Step 12:

[0738] Terminal: Displays the generated proposal to the user. Displays details of the proposal (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[0739] Step 13:

[0740] User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[0741] Step 14:

[0742] Terminal: Sends feedback to the server.

[0743] Step 15:

[0744] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[0745] Step 16:

[0746] Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[0747] Step 17:

[0748] Terminal: Sends the entered request for proposal details to the server.

[0749] Step 18:

[0750] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[0751] Step 19:

[0752] Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[0753] Step 20:

[0754] Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[0755] (Example 1)

[0756] 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".

[0757] Many companies are lagging behind in digitalization and digital transformation (DX), and management lacks the means to receive appropriate proposals. Furthermore, there are insufficient mechanisms for management to provide quick and efficient feedback on proposals after they are received, as well as for forwarding requests for proposals to service providers and managing their progress. As a result, digitalization and DX initiatives are delayed, potentially leading to a decline in the overall competitiveness of the company.

[0758] 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.

[0759] In this invention, the server includes means for the user to input company information, means for the user to input needs and challenges related to digitalization and digital transformation, means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon, means for displaying the proposals generated by the generative artificial intelligence to the user, means for the user to input feedback based on the proposals, means for the user to request proposals they like, means for forwarding proposal requests to service providers and managing the progress of follow-up, means for sending details regarding the proposal requests to service providers, means for notifying the user of follow-up from service providers, and means for storing user information and proposal request information in a database. As a result, the user can receive comprehensive digitalization and DX proposals, provide feedback on those proposals, request proposals, and follow up on their progress.

[0760] "Company information" refers to information that identifies a company and indicates its basic attributes and characteristics, such as the company name, address, job title, and contact information.

[0761] "Needs and challenges" refer to the problems and demands that companies face regarding digitalization and digital transformation, including areas for improvement and hurdles to overcome.

[0762] "Generative artificial intelligence" refers to artificial intelligence that has the function of automatically generating suggestions and solutions tailored to a specific purpose based on the input data.

[0763] "Proposal" refers to solutions or improvement plans generated by generative artificial intelligence based on a company's needs and challenges.

[0764] "Feedback" refers to users providing evaluations and opinions on suggestions that have been made.

[0765] A "Request for Proposal" refers to a request from a user to take specific actions to implement a proposal they like.

[0766] A "business operator" refers to a provider of services or products for implementing a proposal, and plays a role in realizing the proposal requested by the user.

[0767] "Follow-up" refers to checking the progress and maintaining contact after a request for proposal has been accepted.

[0768] A "database" refers to an electronic record system that organizes and stores user information and requests for proposals, allowing them to be quickly retrieved when needed.

[0769] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. This system utilizes multiple hardware and software components, and has a function to generate proposals using generative artificial intelligence based on company information, needs, and challenges input by the user, and then provide these proposals to the user. It also provides a means for the user to input feedback on the proposals and to request preferred proposals from service providers.

[0770] Components

[0771] 1. Terminal: A device used by users to input company information, needs, and challenges, and to view and review the generated proposals.

[0772] Examples of hardware used: smartphones, tablets, PCs, etc.

[0773] Examples of software used: applications, web browsers, etc.

[0774] 2. Server: This is the central hub of the system, which analyzes information received from users and generates appropriate suggestions using generative artificial intelligence. It also has the function of receiving requests for suggestions and managing the progress of follow-up with businesses.

[0775] Examples of software used: Apache, NGINX, Python, generative AI models (e.g., GPT-3, BERT)

[0776] 3. Database: A system for storing user information and request for proposal information.

[0777] Examples of software used: MySQL, PostgreSQL

[0778] Initial setup and user registration

[0779] First, the user installs the application on their device and enters basic information such as company name, job title, and contact information. This information is sent from the device to the server, which stores it in a database, generates a user ID, and sends it back to the device.

[0780] Confirming needs and challenges

[0781] After the user logs in, the terminal displays a questionnaire about DX (Digital Transformation). The user answers questions such as "Current state of digitalization" and "Challenges to be solved," and sends the answers to the server. The server analyzes the answers, and a generative artificial intelligence prepares the data necessary for generating suggestions.

[0782] Proposal generation using generative artificial intelligence

[0783] The server inputs data into a generative artificial intelligence (AI) system based on the survey results. This AI then sets specific tasks such as "optimizing inventory management" and "customer data analysis" and generates suggestions. The generated suggestions are sent to the terminal and displayed to the user.

[0784] Feedback and Request for Suggestions

[0785] Users can review the generated proposals and provide feedback, including opinions and evaluations. For proposals they like, they can press the "Request Proposal" button, enter details, and send them to the server. The server then forwards this information to the service provider and manages its progress in a database. Follow-up requests from the service provider are notified to the user's device.

[0786] Specific example

[0787] Digitalization of retail stores

[0788] 1. Terminal: Retail store executives install the app and register company information.

[0789] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[0790] 3. Terminal: Sends the response content to the server.

[0791] 4. Server: Generative artificial intelligence generates solutions, including "implementation of a store inventory management system" and "proposal of a customer data analysis tool," and sends them to the terminal.

[0792] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[0793] 6. User: If you like a proposal, press the "Request Proposal" button.

[0794] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[0795] 8. Server: Sends requests for proposals to service providers and records them in the database.

[0796] 9. Server: You will receive follow-up contact from the service provider's representative.

[0797] Example of a prompt

[0798] The following text format is used as an example of a prompt message.

[0799] "Please propose ways to improve the efficiency of inventory management in retail stores."

[0800] "Please tell me how to optimize sales strategies through customer data analysis."

[0801] These prompts enable the generative AI model to generate proposals tailored to the company's needs.

[0802] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0803] Program processing flow

[0804] Initial setup and user registration

[0805] Step 1:

[0806] Subject: terminal

[0807] Process details: The user installs and launches the application.

[0808] Input: Tap the application icon

[0809] Output: Display the app's home screen.

[0810] Specific operation: When the user selects and taps an application from the device's home screen, the application launches and displays the new user registration screen.

[0811] Step 2:

[0812] Subject: User

[0813] Process details: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[0814] Input: Company name, job title, contact information

[0815] Output: Send input information

[0816] Specific operation: The user enters data into each form field and finally clicks the "Register" button.

[0817] Step 3:

[0818] Subject: terminal

[0819] Processing details: The entered information is sent to the server.

[0820] Input: Company information entered by the user

[0821] Output: HTTPS request to the server

[0822] Specific operation: The terminal temporarily stores the input data in memory, creates an HTTPS request, and sends it to the server.

[0823] Step 4:

[0824] Subject: Server

[0825] Processing details: The received user information is saved to the database, a user ID is generated, and it is sent back to the terminal.

[0826] Input: User information

[0827] Output: User ID

[0828] Specific operation: The server inserts the received information into the database, generates a new user ID (such as a UUID), and returns it to the terminal as a response.

[0829] Confirming needs and challenges

[0830] Step 1:

[0831] Subject: terminal

[0832] Processing details: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed.

[0833] Enter: Login information

[0834] Output: Survey screen

[0835] Specific behavior: If user authentication is successful, the survey screen will appear as a pop-up or in a new window.

[0836] Step 2:

[0837] Subject: User

[0838] Process: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[0839] Input: Needs and challenges related to DX

[0840] Output: Submitted response

[0841] Specific actions: The user answers questions using text areas or checkboxes and taps the "Submit" button.

[0842] Step 3:

[0843] Subject: terminal

[0844] Processing details: Send the response content to the server.

[0845] Input: User survey responses

[0846] Output: HTTPS request to the server

[0847] Specific operation: The device temporarily stores the survey data in memory, creates an HTTPS request, and sends it to the server.

[0848] Step 4:

[0849] Subject: Server

[0850] Processing details: The response content is analyzed, and the generative artificial intelligence prepares the data necessary for generating suggestions.

[0851] Input: Survey response data

[0852] Output: Analysis data for proposal generation

[0853] Specific operation: The server uses a natural language processing algorithm to analyze the response and converts the analysis results into a format suitable as input for an AI model.

[0854] Proposal generation using generative artificial intelligence

[0855] Step 1:

[0856] Subject: Server

[0857] Processing details: Based on the survey results, the data is input into a generative artificial intelligence system.

[0858] Input: Analyzed survey results

[0859] Output: Input data for AI

[0860] Specific operation: Convert data into the format required by the AI ​​model (JSON or a specific format) and provide it as input.

[0861] Step 2:

[0862] Subject: Server

[0863] Processing details: Generative artificial intelligence generates proposals and identifies the optimal solution.

[0864] Input: Input data for AI

[0865] Output: Generated proposals

[0866] Specific operation: The AI ​​model executes a proposal generation algorithm and outputs solutions tailored to the company's needs in text format.

[0867] Step 3:

[0868] Subject: Server

[0869] Processing details: Send the generated suggestions to the terminal.

[0870] Input: Generated proposal

[0871] Output: Suggestion data to the terminal

[0872] Specific operation: Format the proposed data in JSON format and send it to the terminal as an HTTPS response.

[0873] Feedback and Request for Suggestions

[0874] Step 1:

[0875] Subject: terminal

[0876] Processing details: The user reviews the proposal and provides feedback such as, "This looks good."

[0877] Input: Generated proposal

[0878] Output: Feedback input screen

[0879] Specific action: The user scrolls to review the suggestions and enters comments in the feedback text area.

[0880] Step 2:

[0881] Subject: User

[0882] Processing steps: Click the "Request Proposal" button for any proposals you like.

[0883] Input: Suggestion

[0884] Output: Request for Proposal Details Input Screen

[0885] Specific operation: The user clicks the "Request a Proposal" button and is redirected to a detailed input form that appears as a pop-up.

[0886] Step 3:

[0887] Subject: terminal

[0888] Processing details: Enter the details of the request for proposal and send them to the server.

[0889] Input: Request for Proposal Details

[0890] Output: Request for Proposal data to the server

[0891] Specific operation: The data from the detailed input form is temporarily stored in memory, and an HTTPS request is created and sent to the server.

[0892] Step 4:

[0893] Subject: Server

[0894] Processing details: Send a request for proposal to a business and record it in the database.

[0895] Input: Request for Proposal Data

[0896] Output: Request for proposal notification to businesses, database record

[0897] Specific operation: Save the proposal request details to the database and simultaneously send notifications to businesses via email or API call.

[0898] Step 5:

[0899] Subject: Server

[0900] Processing details: Notify the user of follow-up from the service provider.

[0901] Input: Follow-up information from the business operator

[0902] Output: Notification to the user

[0903] Specific actions: Receive communications from businesses and send push notifications or emails to users.

[0904] This enables the system to effectively generate digitalization and digital transformation proposals tailored to user needs, and to consistently manage the feedback and request for proposal processes.

[0905] (Application Example 1)

[0906] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0907] This system aims to solve the problem of companies lagging behind in traditional digitalization and digital transformation finding it difficult to effectively receive proposals for digitalization and digital transformation. It also aims to provide a system that enables logistics centers and field personnel to receive accurate, real-time proposals to address challenges in improving the efficiency of inventory management and shipping operations.

[0908] 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.

[0909] In this invention, the server includes means for a user to input company information, means for a user to input needs and challenges related to digitalization and digital transformation, means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon, means for displaying the proposals generated by the generative artificial intelligence to the user, means for a user to input feedback based on the proposals, means for a user to request proposals they like, means for forwarding proposal requests to businesses and managing the progress of follow-up, means for a user to input on-site conditions and needs via a smart device and check the generated proposals in real time, and means for creating prompt sentences for the generative artificial intelligence to generate proposals regarding the efficiency of the logistics center. This enables companies and logistics centers to efficiently receive proposals for digitalization and digital transformation, and to optimize operations and improve efficiency.

[0910] "Company information" refers to basic company information entered by the user, including company name, job title, contact information, etc.

[0911] "Digitalization" means streamlining analog and manual business processes using digital technology.

[0912] "Digital transformation" refers to a company fundamentally changing its business model and operational processes by utilizing digital technologies.

[0913] "Challenges" refer to specific problems or needs that users wish to solve in the context of digitalization and digital transformation.

[0914] "Generative artificial intelligence" is an artificial intelligence technology that automatically generates optimal suggestions based on input data.

[0915] A "proposal" refers to a solution or solution generated by generative artificial intelligence in response to a company's needs and challenges.

[0916] "Feedback" refers to the evaluations and opinions that users provide regarding the generated suggestions.

[0917] A "Request for Proposal" is an action taken by a user to ask a business to implement a proposal they like.

[0918] A "smart device" refers to a device such as a smartphone or head-mounted display that allows the user to input on-site conditions and needs, and then view the generated suggestions in real time.

[0919] A "prompt statement" is an instruction given to a generative artificial intelligence system to generate specific suggestions.

[0920] "Inventory management" refers to the process of properly managing inventory levels in a logistics center and replenishing or ordering products at the optimal time.

[0921] "Shipping operations" refers to the process of preparing and processing shipments of goods at a logistics center.

[0922] This invention relates to a system that allows field personnel at a logistics center to receive suggestions for efficiency improvements using smart devices. The system is configured so that the user (field personnel) inputs the situation, needs, and challenges at the site through a device such as a smartphone or head-mounted display, and based on that, generative artificial intelligence proposes the optimal solution.

[0923] Hardware environment and software configuration

[0924] 1. Terminal: This refers to devices such as smartphones and head-mounted displays used by users in the field. This allows users to input company information, needs, and challenges, and view generated proposals in real time.

[0925] 2. Server: Runs on the cloud and analyzes information received from users to generate suggestions. Specifically, it uses a cloud service such as Amazon Web Services (AWS).

[0926] 3. Generative Artificial Intelligence: Generative AI models such as OpenAI's GPT-3 are used to generate appropriate suggestions based on user input. This involves generating prompt sentences based on the data entered by the user and inputting them into the AI ​​model.

[0927] 4. Application: Installed on the device, it provides an interface for users to input company information and on-site challenges, receive suggestions, and provide feedback. The application is developed using a cross-platform framework such as React Native or Flutter.

[0928] Processing flow

[0929] 1. User input:

[0930] Users input company information, on-site conditions, needs, and challenges using applications installed on their smart devices.

[0931] 2. Data transmission:

[0932] The terminal sends the entered information to the server. The data is sent via a secure communication protocol (e.g., HTTPS).

[0933] 3. Parsing and prompt generation:

[0934] The server cleans and normalizes the received data and generates prompt sentences for input to the generative artificial intelligence.

[0935] 4. Proposal generation:

[0936] Generative artificial intelligence generates optimal suggestions based on the prompt text and returns them to the server in JSON format.

[0937] 5. Display of proposals:

[0938] The server sends the generated suggestions to the user's terminal, allowing the user to review them in real time.

[0939] 6. Feedback and requests:

[0940] Users provide feedback on the generated proposals and submit requests for proposals to implement the ones they like.

[0941] Specific example

[0942] Example of a prompt

[0943] Please generate proposals to improve operational efficiency at the logistics center. Below are the main challenges and requirements from the field.

[0944] The inventory management system is outdated and inefficient.

[0945] There are many mistakes in the shipping process.

[0946] Designing efficient delivery routes is difficult.

[0947] Requirements:

[0948] 1. Optimizing inventory management

[0949] 2. Reducing shipping errors

[0950] 3. Optimizing delivery routes.

[0951] By inputting the above prompts into a generative artificial intelligence system, the AI ​​generates suggestions such as updating inventory management systems, checklist tools to reduce errors in shipping operations, and AI-based delivery route design tools.

[0952] This invention contributes to an efficient solution proposal system that utilizes generative artificial intelligence to solve real-world problems in logistics centers in real time.

[0953] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0954] Step 1:

[0955] The user launches an application installed on their smart device and inputs company information, on-site conditions, needs, and challenges.

[0956] Input: Company name, job title, contact information, on-site situation, challenges / needs

[0957] Output: Input data in JSON format

[0958] Specific operation: The user follows the interface, enters the required information into the form, and presses the "Submit" button.

[0959] Step 2:

[0960] The terminal sends the entered information to the server.

[0961] Input: JSON format data containing company information, on-site conditions, and challenges / needs entered by the user.

[0962] Output: HTTP request to the server

[0963] Specific operation: The terminal uses the HTTPS protocol to send input data to the server's API endpoint.

[0964] Step 3:

[0965] The server cleans and normalizes the data it receives.

[0966] Input: JSON format data sent from the device.

[0967] Output: Cleaned and normalized data

[0968] Specific operation: The server checks the data format and invalid values, and converts them to the correct format.

[0969] Step 4:

[0970] The server generates prompt text to be input to the generative artificial intelligence based on cleaned and normalized data.

[0971] Input: Cleaned and normalized data

[0972] Output: Prompt text to input to the generative artificial intelligence.

[0973] Specific operation: The server generates a prompt message with the input data embedded, based on a template.

[0974] Step 5:

[0975] The generative artificial intelligence generates the optimal suggestion based on the prompt text.

[0976] Input: Prompt message

[0977] Output: Generated proposals (in JSON format)

[0978] Specific operation: The generative artificial intelligence analyzes the prompt text and generates an appropriate solution as a suggestion.

[0979] Step 6:

[0980] The server sends the generated proposal to the user's terminal.

[0981] Input: Generated suggestions (in JSON format)

[0982] Output: Suggestion data sent to the user's terminal.

[0983] Specific operation: The server uses the HTTPS protocol to send the generated proposal to the user's terminal.

[0984] Step 7:

[0985] The device displays suggestions it has received to the user.

[0986] Input: Proposal data sent from the server

[0987] Output: Suggestions displayed to the user

[0988] Specific operation: The terminal analyzes the received suggestion data and displays it through the user interface.

[0989] Step 8:

[0990] Users provide feedback on the generated proposals and press the "Request Proposal" button to implement the proposals they like.

[0991] Input: Feedback, details of the request for proposal

[0992] Output: Feedback and suggestion data sent to the server

[0993] Specific operation: The user reviews the proposal, enters details of feedback or a request for proposal on the interface, and submits it.

[0994] Step 9:

[0995] The server forwards user feedback and requests for suggestions to the service provider and manages the progress of follow-up.

[0996] Input: Feedback, Request for Proposal data

[0997] Output: Data for managing the progress of communication and follow-up with service providers.

[0998] Specific operation: The server forwards the received feedback and requests for suggestions to the relevant service providers and updates the database for progress management.

[0999] 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.

[1000] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. This system has a function where the user inputs company information, needs, and challenges, and based on this, generative artificial intelligence generates proposals and displays them to the user. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, it can provide more personalized proposals.

[1001] System Configuration

[1002] 1. Terminal: A device on which an application is installed and which the user operates through an interface. The terminal is used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[1003] 2. Server: This server is responsible for analyzing information received from the user, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. It also receives requests for suggestions and manages the progress of follow-up. Furthermore, an emotion engine is integrated into the server to analyze the user's emotions.

[1004] 3. Emotion Engine: This engine recognizes and analyzes emotions through user input and actions. This emotional information is provided to the generative artificial intelligence, which adjusts the suggested content and presentation methods based on the user's emotions.

[1005] Program processing flow

[1006] Initial setup and user registration

[1007] 1. Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[1008] 2. User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[1009] 3. Terminal: Sends the entered information to the server.

[1010] 4. Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[1011] Confirming needs and challenges

[1012] 1. Terminal: After the user logs in, a survey screen regarding DX will be displayed. Question items (e.g., "Current state of digitalization," "Issues you want to solve," etc.) will be displayed.

[1013] 2. User: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[1014] 3. Terminal: Sends the response content to the server.

[1015] 4. Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[1016] Proposal generation using generative artificial intelligence and an emotion engine.

[1017] 1. Server: Based on survey results and user input data, the server inputs the data into a generative artificial intelligence. The AI ​​is then given specific tasks such as "optimizing inventory management" or "customer data analysis."

[1018] 2. Server: The emotion engine analyzes user input and actions to understand emotions and provides that emotional information to the generative artificial intelligence.

[1019] 3. Server: Generative artificial intelligence considers the user's emotional information to generate suggestions and identify the optimal solution. For example, specific solutions such as "implementation of an inventory management system" or "suggestion of a customer data analysis tool" are generated.

[1020] 4. Server: Sends the generated proposal to the terminal.

[1021] Display of proposals and feedback

[1022] 1. Terminal: Displays the generated proposal to the user. Displays details of the proposal content (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[1023] 2. User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[1024] 3. Terminal: Sends the feedback content to the server.

[1025] Request for Proposal and Follow-up

[1026] 1. User: If satisfied with the proposal, press the "Request Proposal" button.

[1027] 2. Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[1028] 3. Terminal: Sends the entered proposal request details to the server.

[1029] 4. Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[1030] 5. Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[1031] 6. Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[1032] Specific example

[1033] Digitalization of retail stores and emotion recognition

[1034] 1. Terminal: Retail store executives install the app and register company information.

[1035] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[1036] 3. Terminal: Sends the response content and user input data to the server.

[1037] 4. Server: Consider that the generative AI generates solutions including "implementation of store inventory management systems" and "proposals for customer data analysis tools," and the emotion engine provides user emotion data.

[1038] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[1039] 6. User: If you like a proposal, press the "Request Proposal" button.

[1040] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[1041] 8. Server: Sends requests for proposals to service providers and records them in the database.

[1042] 9. Server: You will receive follow-up contact from the service provider's representative.

[1043] Thus, this system is configured to effectively support the digitalization and digital transformation of small and medium-sized enterprises. Furthermore, by recognizing user emotions and reflecting that information in suggestion generation, it is possible to provide more personalized suggestions.

[1044] The following describes the processing flow.

[1045] Step 1:

[1046] Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[1047] Step 2:

[1048] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[1049] Step 3:

[1050] Terminal: Sends the entered information to the server.

[1051] Step 4:

[1052] Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[1053] Step 5:

[1054] Terminal: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed. Question items (e.g., "Current digitalization status," "Issues you want to solve," etc.) will be displayed.

[1055] Step 6:

[1056] User: Answer the survey and enter the required information. Press the "Submit" button.

[1057] Step 7:

[1058] Terminal: Sends the response content to the server.

[1059] Step 8:

[1060] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[1061] Step 9:

[1062] Server: Based on the survey results, input data into the generative artificial intelligence. Set specific tasks for the AI, such as "optimizing inventory management" or "customer data analysis."

[1063] Step 10:

[1064] Server: The emotion engine analyzes user emotions from input and actions and provides that emotional information to the generative artificial intelligence.

[1065] Step 11:

[1066] Server: Generative artificial intelligence considers user sentiment information to generate suggestions and identify the optimal solution. For example, it generates specific solutions such as "implementing an inventory management system" or "proposing a customer data analysis tool."

[1067] Step 12:

[1068] Server: Sends the generated proposal to the terminal.

[1069] Step 13:

[1070] Terminal: Displays the generated proposal to the user. Displays details of the proposal (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[1071] Step 14:

[1072] User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[1073] Step 15:

[1074] Terminal: Sends feedback to the server.

[1075] Step 16:

[1076] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[1077] Step 17:

[1078] Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[1079] Step 18:

[1080] Terminal: Sends the entered request for proposal details to the server.

[1081] Step 19:

[1082] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[1083] Step 20:

[1084] Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[1085] Step 21:

[1086] Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[1087] (Example 2)

[1088] 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".

[1089] In modern businesses, digitalization and digital transformation (DX) are essential for improving operational efficiency and maintaining competitiveness. However, especially in small and medium-sized enterprises (SMEs), management often lacks sufficient knowledge and resources for these transformations, frequently delaying the implementation of DX. Furthermore, standard DX proposals alone are insufficient to adequately address the unique challenges and needs of each company, making it difficult to provide optimal solutions. Moreover, conventional proposal systems fail to adequately reflect user emotions and feedback, resulting in insufficient personalization.

[1090] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server has an emotion engine that analyzes emotions from user input and operations, and includes means for providing emotion information to the generative artificial intelligence, means for adjusting the proposed content and presentation method based on the emotion information, and means for forwarding the proposal request to the business operator and managing the progress of follow-up. As a result, not only is the optimal digitalization and DX proposal for the user's specific needs and challenges generated, but personalized proposals and feedback that take the user's emotions into consideration are also possible.

[1091] "Digitalization" refers to managing a company's business processes and information electronically to improve efficiency and automate them.

[1092] "Digital transformation (DX)" refers to fundamentally changing a company's business processes and business models by utilizing digital technologies, thereby improving its competitiveness.

[1093] "Company information" refers to basic information used to identify a company, such as its name, job title, and contact information.

[1094] "Needs and challenges" refer to a company's requirements and problems related to digitalization and digital transformation.

[1095] "Generative artificial intelligence" refers to artificial intelligence that has algorithms for generating optimal digitalization and DX proposals based on data input from users.

[1096] An "emotion engine" refers to a system that analyzes emotions from user input and actions and provides that information to a generative artificial intelligence system.

[1097] "Proposal" refers to a specific solution generated by generative artificial intelligence based on the user's needs and challenges.

[1098] "Feedback" refers to the opinions and evaluations that users provide regarding the proposed content.

[1099] A "Request for Proposal" refers to a request for specific actions based on a proposal that the user likes.

[1100] "Follow-up" refers to managing the progress of the business's implementation of the requested proposal and notifying the user of that progress.

[1101] System Overview

[1102] This invention provides a system that enables management in companies lagging behind in digitalization and digital transformation (DX) to more effectively receive proposals for digitalization and DX. The system includes an interface for users to input company information, needs, and challenges, a generative artificial intelligence, an emotion engine, and follow-up management functions.

[1103] Hardware and software to be used

[1104] This system includes the following components:

[1105] Terminal: A device on which an application is installed and which the user operates through an interface. Terminals are used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[1106] Examples of use: smartphones, tablets, and personal computers.

[1107] Example of software used: Application interface.

[1108] The server is responsible for analyzing information received from the user, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. It also receives requests for suggestions and manages the progress of follow-up. Furthermore, an emotion engine is integrated into the server to analyze the user's emotions.

[1109] Examples of use: cloud servers, on-premises servers.

[1110] Examples of software used: database management systems, artificial intelligence models (generative AI), and sentiment analysis engines.

[1111] Emotion Engine: This engine recognizes and analyzes emotions through user input and actions. This emotional information is provided to a generative artificial intelligence system, which adjusts the suggested content and presentation methods based on the user's emotions.

[1112] Examples of use: machine learning models, sentiment analysis algorithms.

[1113] System Operation Overview

[1114] 1. Initial setup and user registration

[1115] Terminal: The user installs and launches the application, and the new user registration screen is displayed.

[1116] User: Enter company name, job title, contact information, etc., and press the "Register" button.

[1117] Terminal: Sends the entered information to the server.

[1118] Server: Saves user information to the database, generates a new user ID, and sends it back.

[1119] 2. Identifying needs and challenges

[1120] Terminal: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed.

[1121] User: Answer the questionnaire and enter your specific needs and challenges.

[1122] Terminal: Sends the response content to the server.

[1123] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[1124] 3. Proposal generation using generative artificial intelligence and an emotion engine

[1125] Server: Based on survey results and user input data, it inputs data into the generative artificial intelligence.

[1126] Server: The emotion engine analyzes emotional information obtained from user input and actions and provides it to the generative artificial intelligence.

[1127] Server: Generative artificial intelligence generates suggestions while considering the user's emotional information.

[1128] Server: Sends the generated proposal to the terminal.

[1129] 4. Display of proposals and feedback

[1130] Terminal: Displays generated suggestions to the user.

[1131] User: Review the proposal and enter your feedback.

[1132] Terminal: Sends feedback to the server.

[1133] 5. Request for Proposal and Follow-up

[1134] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[1135] Terminal: Displays a form for entering details of the "Request for Proposal," and the user enters the details and submits it.

[1136] Terminal: Sends the entered request for proposal details to the server.

[1137] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[1138] Server: Sends a request for proposal notification to the service provider's representative and follows up.

[1139] Server: Manages the progress of follow-ups and notifies users as needed.

[1140] Specific example

[1141] Examples of use in the retail industry

[1142] 1. Terminal: Retail store executives install the app and register company information.

[1143] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[1144] 3. Terminal: Sends the response content and user input data to the server.

[1145] 4. Server: Consider that the generative AI generates solutions including "implementation of store inventory management systems" and "proposals for customer data analysis tools," and the emotion engine provides user emotion data.

[1146] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[1147] 6. User: If you like a proposal, press the "Request Proposal" button.

[1148] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[1149] 8. Server: Sends requests for proposals to service providers and records them in the database.

[1150] 9. Server: You will receive follow-up contact from the service provider's representative.

[1151] Example of a prompt

[1152] "Our company is struggling with efficient inventory management and has challenges in analyzing customer data. Please provide specific suggestions for solving these problems."

[1153] In this way, this system can address the individual needs of companies and, by taking emotional information into consideration, provide more personalized digitalization and DX proposals.

[1154] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1155] Processing steps

[1156] Initial setup and user registration

[1157] Step 1:

[1158] Terminal: The user installs and launches a system-specific application, and the "New User Registration" button is displayed.

[1159] Input: The user installs and launches the application.

[1160] Output: The "New User Registration" button will appear on the app's initial launch screen.

[1161] Step 2:

[1162] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[1163] Input: User's basic information (company name, job title, contact information).

[1164] Output: Registration information is sent to the terminal.

[1165] Step 3:

[1166] Terminal: Sends the entered information to the server.

[1167] Input: User's basic information.

[1168] Output: User information is sent to the server.

[1169] Step 4:

[1170] Server: Stores the received user information in the database, generates a new user ID, and sends it back.

[1171] Input: User information received from the terminal.

[1172] Output: Information stored in the database and a new user ID.

[1173] Confirming needs and challenges

[1174] Step 1:

[1175] Terminal: After the user logs in, a survey screen about DX (Digital Transformation) will be displayed. Questions will include "Current state of digitalization" and "Issues you want to solve."

[1176] Input: User login information.

[1177] Output: The survey screen is displayed.

[1178] Step 2:

[1179] User: Answer the questionnaire, enter specific needs and challenges in the text box, and press the "Submit" button.

[1180] Input: Survey responses.

[1181] Output: The answer is entered into the terminal.

[1182] Step 3:

[1183] Terminal: Sends the response content to the server.

[1184] Input: Survey responses.

[1185] Output: The response is sent to the server.

[1186] Step 4:

[1187] Server: Receives the response content, analyzes it, and prepares the data necessary for the generative artificial intelligence to generate proposals.

[1188] Input: Answer content.

[1189] Output: Data is prepared for input into a generative artificial intelligence.

[1190] Proposal generation using generative artificial intelligence and an emotion engine.

[1191] Step 1:

[1192] Server: Inputs data into a generative artificial intelligence system based on survey results and user input data. The AI ​​then sets specific tasks (e.g., "Optimize inventory management," "Analyze customer data").

[1193] Input: Survey results and user input data.

[1194] Output: Data input to a generative artificial intelligence.

[1195] Step 2:

[1196] Server: The emotion engine analyzes emotional information obtained from user input and actions, and provides that information to the generative artificial intelligence.

[1197] Input: User sentiment information.

[1198] Output: Emotional information provided to the generative artificial intelligence.

[1199] Step 3:

[1200] Server: Generative artificial intelligence generates suggestions while considering the user's emotional information. For example, "Implementation of an inventory management system" or "Suggestion of a customer data analysis tool."

[1201] Input: Survey results, user sentiment information.

[1202] Output: Generated proposals.

[1203] Step 4:

[1204] Server: Sends the generated proposal to the terminal.

[1205] Input: Generated suggestions.

[1206] Output: Suggestions sent to the terminal.

[1207] Display of proposals and feedback

[1208] Step 1:

[1209] Terminal: Displays generated proposals to the user. The proposals include detailed information such as "Overview of the inventory management system" and "Benefits of implementation."

[1210] Input: Suggestions sent from the server.

[1211] Output: The suggested content is displayed to the user.

[1212] Step 2:

[1213] User: Review the proposal and check the feedback. Enter comments such as "This looks good" or "I'd like more specific information," and submit.

[1214] Input: User feedback.

[1215] Output: Feedback entered into the terminal.

[1216] Step 3:

[1217] Terminal: Sends feedback to the server.

[1218] Input: Feedback content.

[1219] Output: Feedback sent to the server.

[1220] Request for Proposal and Follow-up

[1221] Step 1:

[1222] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[1223] Input: User action (pressing the "Request Proposal" button).

[1224] Output: The Request for Proposal screen is displayed.

[1225] Step 2:

[1226] Terminal: A form is displayed for the user to enter details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[1227] Input: Details of the Request for Proposal.

[1228] Output: Details of the request for proposal entered into the terminal.

[1229] Step 3:

[1230] Terminal: Sends the entered request for proposal details to the server.

[1231] Input: Details of the Request for Proposal.

[1232] Output: Details of the request for proposal sent to the server.

[1233] Step 4:

[1234] Server: Transfers the details of the Request for Proposal to the service provider and records the relevant data in the database.

[1235] Input: Details of the Request for Proposal.

[1236] Output: Details of the Request for Proposal forwarded to the service provider, and data recorded in the database.

[1237] Step 5:

[1238] Server: Sends a request for proposal notification to the service provider's representative, and the follow-up representative takes specific actions.

[1239] Input: Details of the Request for Proposal.

[1240] Output: Notification to the business representative and follow-up actions.

[1241] Step 6:

[1242] Server: Manages the progress of follow-ups and notifies users as needed. This includes updating statuses such as "An agent will contact you shortly."

[1243] Input: Follow-up progress.

[1244] Output: Notifications to the user and status updates.

[1245] (Application Example 2)

[1246] 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."

[1247] In today's world, many companies are lagging behind in digitalization and digital transformation (DX). This lag is particularly pronounced in small and medium-sized enterprises (SMEs), resulting in decreased competitiveness and operational efficiency. Furthermore, management lacks a suitable system for receiving concrete solution proposals, making it difficult to promote digitalization. Moreover, proposals are often uniform and do not align with the feelings and needs of management. A system is needed to solve these problems.

[1248] 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.

[1249] In this invention, the server includes means for the user to input corporate information, means for the user to input needs and challenges related to digitalization and digital transformation, means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon, means incorporating an emotion recognition engine that analyzes the user's input information and emotion information to generate personalized proposals, means for displaying the proposals generated by the generative artificial intelligence to the user, means for the user to input feedback based on the proposals, means for the user to request proposals they like, and means for forwarding proposal requests to service providers and managing the progress of follow-up. This makes it possible for users to receive personalized proposals based on their specific needs and emotions, thereby effectively advancing the digitalization and digital transformation of companies.

[1250] "Means for inputting company information" refers to interfaces or data entry systems for inputting basic company information.

[1251] "Means for inputting needs and challenges" refers to interfaces or database systems that allow users to input their needs and challenges related to digitalization and digital transformation.

[1252] "Generative artificial intelligence" is a type of artificial intelligence that analyzes input data and generates optimal suggestions based on that analysis.

[1253] "Methods for incorporating an emotion recognition engine" refers to methods for integrating an engine into the system that recognizes emotions from user input information and reflects that emotion data in suggestion generation.

[1254] "Means for displaying proposals to users" refers to displays and interfaces that make generated proposals easy for users to understand.

[1255] "Means for inputting feedback" refer to interfaces or data collection systems that allow users to input reactions and opinions on suggestions.

[1256] "Means for requesting proposals" refers to interfaces and notification systems that allow users to actually request proposals they like.

[1257] "Means for forwarding requests for proposals to service providers and managing the progress of follow-up" refers to systems and servers that forward user requests for proposals to service providers and manage and monitor their subsequent progress.

[1258] This invention is a system for management in companies lagging behind in digitalization and digital transformation to receive proposals for digitalization and DX. The system has a function where the user inputs company information, needs, and challenges, and based on this, generative artificial intelligence generates optimal proposals, which are then displayed to the user. Furthermore, by combining this with an emotion recognition engine that recognizes the user's emotions, it can provide more personalized proposals.

[1259] System Configuration

[1260] 1. Terminal

[1261] A terminal is a device on which an application is installed and which the user operates through an interface. This terminal is equipped with means for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[1262] 2. Server

[1263] The server is responsible for analyzing information received from the user, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. It also receives requests for suggestions and manages the progress of follow-up. Furthermore, an emotion recognition engine is integrated into the server to analyze the user's emotions.

[1264] 3. Emotion Recognition Engine

[1265] The emotion recognition engine recognizes and analyzes emotions through user input and actions. This emotion information is provided to a generative artificial intelligence system, which then adjusts the suggested content and presentation methods based on the user's emotions.

[1266] Program processing and hardware / software

[1267] The system utilizes Flask as its framework and OpenAI's GPT-3 for generative artificial intelligence. It incorporates EmotionEngine as its emotion recognition engine to recognize and analyze user emotions.

[1268] Examples of specific cases and prompt statements

[1269] Specific example:

[1270] 1. User: Owner of a physical store. During registration, they entered "Inventory management is not efficient" and "Customer data analysis is difficult."

[1271] 2. Emotions: Emotions such as "anxiety" and "anticipation" are recognized from the user's input.

[1272] 3. Based on this user information, the generative artificial intelligence creates personalized suggestions.

[1273] Example of a prompt:

[1274] User Data: Inventory management is not efficient, customer data analysis is difficult.

[1275] User Emotion: Anxiety, Anticipation

[1276] Generate a personalized DX proposal for the user based on their input and emotion.

[1277] In this way, users can receive personalized suggestions based on their specific needs and emotions, which can effectively advance the company's digitalization and digital transformation.

[1278] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1279] Step 1:

[1280] User Registration

[1281] The user uses a terminal to enter basic information such as company name, job title, and contact information. The terminal receives this information and sends it to the server. The server stores the received information in a database, generates a user ID, and sends it back to the terminal.

[1282] Input: Company name, job title, contact information

[1283] Output: User ID

[1284] Step 2:

[1285] Inputting needs and challenges

[1286] The user uses a terminal to input their needs and challenges regarding digitalization and digital transformation. The terminal sends this information to a server. The server analyzes the received needs and challenges and prepares data for generative artificial intelligence to generate suggestions.

[1287] Input: Needs and challenges related to digitalization and DX

[1288] Output: Data required for proposal generation

[1289] Step 3:

[1290] emotion recognition

[1291] An emotion recognition engine embedded in the server analyzes the user's input information and recognizes the user's emotions. The recognized emotion information is provided to a generative artificial intelligence system. As a result, suggestions are personalized based on the user's emotions.

[1292] Input: User input information

[1293] Output: User sentiment information

[1294] Step 4:

[1295] Proposal generation using generative artificial intelligence

[1296] The server inputs data into the generative artificial intelligence (AI) based on the user's needs and challenges. The generative AI then generates appropriate suggestions using prompts. For example, it might generate suggestions for optimizing inventory management or analyzing customer data.

[1297] Input: User needs, challenges, and emotional information

[1298] Output: Personalized suggestions

[1299] Step 5:

[1300] Display of proposals and feedback

[1301] The terminal displays the generated suggestions to the user. The user reviews the suggestions and enters feedback. The terminal sends this feedback to the server. The server analyzes the received feedback and updates the suggestions as needed.

[1302] Input: User feedback

[1303] Output: Updated proposal

[1304] Step 6:

[1305] Request for Proposal and Follow-up

[1306] To request a proposal they like, the user enters details using a terminal. The terminal sends this information to the server. The server forwards the request for proposal to the service provider and records it in a database. It also manages the progress of follow-up and notifies the user as needed.

[1307] Input: Details of the Request for Proposal (e.g., desired implementation period, budget, etc.)

[1308] Output: Forwarding of Request for Proposal, follow-up progress notification

[1309] 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.

[1310] 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.

[1311] 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.

[1312] [Third Embodiment]

[1313] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1314] 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.

[1315] 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).

[1316] 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.

[1317] 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.

[1318] 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).

[1319] 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.

[1320] 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.

[1321] 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.

[1322] 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.

[1323] 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.

[1324] 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".

[1325] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. The system has a function where the user inputs company information, needs, and challenges, and based on this, a generative artificial intelligence generates proposals, which are then displayed to the user. It also provides a means for the user to input feedback on the proposals and request the preferred proposals from service providers.

[1326] System Configuration

[1327] 1. Terminal: A device on which an application is installed and which the user operates through an interface. The terminal is used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[1328] 2. Server: This server is responsible for analyzing information received from users, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. This also includes receiving requests for suggestions and managing the progress of follow-up.

[1329] Program processing flow

[1330] Initial setup and user registration

[1331] 1. Terminal: The user installs and launches the application. The "New User Registration" option is displayed on the screen.

[1332] 2. User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[1333] 3. Terminal: Sends the entered information to the server.

[1334] 4. Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[1335] Confirming needs and challenges

[1336] 1. Terminal: After the user logs in, a survey screen regarding DX will be displayed. Question items may include, for example, "Current state of digitalization" and "Issues you want to solve."

[1337] 2. User: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[1338] 3. Terminal: Sends the response content to the server.

[1339] 4. Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[1340] Proposal generation using generative artificial intelligence

[1341] 1. Server: Based on the survey results, the server inputs the data into a generative artificial intelligence. The AI ​​then sets specific tasks such as "optimizing inventory management" or "customer data analysis."

[1342] 2. Server: Generative artificial intelligence generates proposals and identifies the optimal solution. For example, specific solutions such as "implementation of an inventory management system" or "proposal of a customer data analysis tool" are generated.

[1343] 3. Server: Sends the generated proposal to the terminal.

[1344] Specific example

[1345] Digitalization of retail stores

[1346] 1. Terminal: Retail store executives install the app and register company information.

[1347] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[1348] 3. Terminal: Sends the response content to the server.

[1349] 4. Server: Generative artificial intelligence generates solutions, including "implementation of a store inventory management system" and "proposal of a customer data analysis tool," and sends them to the terminal.

[1350] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[1351] 6. User: If you like a proposal, press the "Request Proposal" button.

[1352] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[1353] 8. Server: Sends requests for proposals to service providers and records them in the database.

[1354] 9. Server: You will receive follow-up contact from the service provider's representative.

[1355] Thus, this system is configured to effectively support the digitalization and digital transformation of small and medium-sized enterprises.

[1356] The following describes the processing flow.

[1357] Step 1:

[1358] Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[1359] Step 2:

[1360] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[1361] Step 3:

[1362] Terminal: Sends the entered information to the server.

[1363] Step 4:

[1364] Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[1365] Step 5:

[1366] Terminal: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed. Question items (e.g., "Current digitalization status," "Issues you want to solve," etc.) will be displayed.

[1367] Step 6:

[1368] User: Answer the survey and enter the required information. Press the "Submit" button.

[1369] Step 7:

[1370] Terminal: Sends the response content to the server.

[1371] Step 8:

[1372] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[1373] Step 9:

[1374] Server: Based on the survey results, input data into the generative artificial intelligence. Set specific tasks for the AI, such as "optimizing inventory management" or "customer data analysis."

[1375] Step 10:

[1376] Server: Generative artificial intelligence generates proposals and identifies the optimal solution. For example, it generates specific solutions such as "implementation of an inventory management system" or "proposal of a customer data analysis tool."

[1377] Step 11:

[1378] Server: Sends the generated proposal to the terminal.

[1379] Step 12:

[1380] Terminal: Displays the generated proposal to the user. Displays details of the proposal (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[1381] Step 13:

[1382] User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[1383] Step 14:

[1384] Terminal: Sends feedback to the server.

[1385] Step 15:

[1386] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[1387] Step 16:

[1388] Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[1389] Step 17:

[1390] Terminal: Sends the entered request for proposal details to the server.

[1391] Step 18:

[1392] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[1393] Step 19:

[1394] Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[1395] Step 20:

[1396] Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[1397] (Example 1)

[1398] 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."

[1399] Many companies are lagging behind in digitalization and digital transformation (DX), and management lacks the means to receive appropriate proposals. Furthermore, there are insufficient mechanisms for management to provide quick and efficient feedback on proposals after they are received, as well as for forwarding requests for proposals to service providers and managing their progress. As a result, digitalization and DX initiatives are delayed, potentially leading to a decline in the overall competitiveness of the company.

[1400] 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.

[1401] In this invention, the server includes means for the user to input company information, means for the user to input needs and challenges related to digitalization and digital transformation, means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon, means for displaying the proposals generated by the generative artificial intelligence to the user, means for the user to input feedback based on the proposals, means for the user to request proposals they like, means for forwarding proposal requests to service providers and managing the progress of follow-up, means for sending details regarding the proposal requests to service providers, means for notifying the user of follow-up from service providers, and means for storing user information and proposal request information in a database. As a result, the user can receive comprehensive digitalization and DX proposals, provide feedback on those proposals, request proposals, and follow up on their progress.

[1402] "Company information" refers to information that identifies a company and indicates its basic attributes and characteristics, such as the company name, address, job title, and contact information.

[1403] "Needs and challenges" refer to the problems and demands that companies face regarding digitalization and digital transformation, including areas for improvement and hurdles to overcome.

[1404] "Generative artificial intelligence" refers to artificial intelligence that has the function of automatically generating suggestions and solutions tailored to a specific purpose based on the input data.

[1405] "Proposal" refers to solutions or improvement plans generated by generative artificial intelligence based on a company's needs and challenges.

[1406] "Feedback" refers to users providing evaluations and opinions on suggestions that have been made.

[1407] A "Request for Proposal" refers to a request from a user to take specific actions to implement a proposal they like.

[1408] A "business operator" refers to a provider of services or products for implementing a proposal, and plays a role in realizing the proposal requested by the user.

[1409] "Follow-up" refers to checking the progress and maintaining contact after a request for proposal has been accepted.

[1410] A "database" refers to an electronic record system that organizes and stores user information and requests for proposals, allowing them to be quickly retrieved when needed.

[1411] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. This system utilizes multiple hardware and software components, and has a function to generate proposals using generative artificial intelligence based on company information, needs, and challenges input by the user, and then provide these proposals to the user. It also provides a means for the user to input feedback on the proposals and to request preferred proposals from service providers.

[1412] Components

[1413] 1. Terminal: A device used by users to input company information, needs, and challenges, and to view and review the generated proposals.

[1414] Examples of hardware used: smartphones, tablets, PCs, etc.

[1415] Examples of software used: applications, web browsers, etc.

[1416] 2. Server: This is the central hub of the system, which analyzes information received from users and generates appropriate suggestions using generative artificial intelligence. It also has the function of receiving requests for suggestions and managing the progress of follow-up with businesses.

[1417] Examples of software used: Apache, NGINX, Python, generative AI models (e.g., GPT-3, BERT)

[1418] 3. Database: A system for storing user information and request for proposal information.

[1419] Examples of software used: MySQL, PostgreSQL

[1420] Initial setup and user registration

[1421] First, the user installs the application on their device and enters basic information such as company name, job title, and contact information. This information is sent from the device to the server, which stores it in a database, generates a user ID, and sends it back to the device.

[1422] Confirming needs and challenges

[1423] After the user logs in, the terminal displays a questionnaire about DX (Digital Transformation). The user answers questions such as "Current state of digitalization" and "Challenges to be solved," and sends the answers to the server. The server analyzes the answers, and a generative artificial intelligence prepares the data necessary for generating suggestions.

[1424] Proposal generation using generative artificial intelligence

[1425] The server inputs data into a generative artificial intelligence (AI) system based on the survey results. This AI then sets specific tasks such as "optimizing inventory management" and "customer data analysis" and generates suggestions. The generated suggestions are sent to the terminal and displayed to the user.

[1426] Feedback and Request for Suggestions

[1427] Users can review the generated proposals and provide feedback, including opinions and evaluations. For proposals they like, they can press the "Request Proposal" button, enter details, and send them to the server. The server then forwards this information to the service provider and manages its progress in a database. Follow-up requests from the service provider are notified to the user's device.

[1428] Specific example

[1429] Digitalization of retail stores

[1430] 1. Terminal: Retail store executives install the app and register company information.

[1431] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[1432] 3. Terminal: Sends the response content to the server.

[1433] 4. Server: Generative artificial intelligence generates solutions, including "implementation of a store inventory management system" and "proposal of a customer data analysis tool," and sends them to the terminal.

[1434] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[1435] 6. User: If you like a proposal, press the "Request Proposal" button.

[1436] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[1437] 8. Server: Sends requests for proposals to service providers and records them in the database.

[1438] 9. Server: You will receive follow-up contact from the service provider's representative.

[1439] Example of a prompt

[1440] The following text format is used as an example of a prompt message.

[1441] "Please propose ways to improve the efficiency of inventory management in retail stores."

[1442] "Please tell me how to optimize sales strategies through customer data analysis."

[1443] These prompts enable the generative AI model to generate proposals tailored to the company's needs.

[1444] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1445] Program processing flow

[1446] Initial setup and user registration

[1447] Step 1:

[1448] Subject: terminal

[1449] Process details: The user installs and launches the application.

[1450] Input: Tap the application icon

[1451] Output: Display the app's home screen.

[1452] Specific operation: When the user selects and taps an application from the device's home screen, the application launches and displays the new user registration screen.

[1453] Step 2:

[1454] Subject: User

[1455] Process details: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[1456] Input: Company name, job title, contact information

[1457] Output: Send input information

[1458] Specific operation: The user enters data into each form field and finally clicks the "Register" button.

[1459] Step 3:

[1460] Subject: terminal

[1461] Processing details: The entered information is sent to the server.

[1462] Input: Company information entered by the user

[1463] Output: HTTPS request to the server

[1464] Specific operation: The terminal temporarily stores the input data in memory, creates an HTTPS request, and sends it to the server.

[1465] Step 4:

[1466] Subject: Server

[1467] Processing details: The received user information is saved to the database, a user ID is generated, and it is sent back to the terminal.

[1468] Input: User information

[1469] Output: User ID

[1470] Specific operation: The server inserts the received information into the database, generates a new user ID (such as a UUID), and returns it to the terminal as a response.

[1471] Confirming needs and challenges

[1472] Step 1:

[1473] Subject: terminal

[1474] Processing details: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed.

[1475] Enter: Login information

[1476] Output: Survey screen

[1477] Specific behavior: If user authentication is successful, the survey screen will appear as a pop-up or in a new window.

[1478] Step 2:

[1479] Subject: User

[1480] Process: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[1481] Input: Needs and challenges related to DX

[1482] Output: Submitted response

[1483] Specific actions: The user answers questions using text areas or checkboxes and taps the "Submit" button.

[1484] Step 3:

[1485] Subject: terminal

[1486] Processing details: Send the response content to the server.

[1487] Input: User survey responses

[1488] Output: HTTPS request to the server

[1489] Specific operation: The device temporarily stores the survey data in memory, creates an HTTPS request, and sends it to the server.

[1490] Step 4:

[1491] Subject: Server

[1492] Processing details: The response content is analyzed, and the generative artificial intelligence prepares the data necessary for generating suggestions.

[1493] Input: Survey response data

[1494] Output: Analysis data for proposal generation

[1495] Specific operation: The server uses a natural language processing algorithm to analyze the response and converts the analysis results into a format suitable as input for an AI model.

[1496] Proposal generation using generative artificial intelligence

[1497] Step 1:

[1498] Subject: Server

[1499] Processing details: Based on the survey results, the data is input into a generative artificial intelligence system.

[1500] Input: Analyzed survey results

[1501] Output: Input data for AI

[1502] Specific operation: Convert data into the format required by the AI ​​model (JSON or a specific format) and provide it as input.

[1503] Step 2:

[1504] Subject: Server

[1505] Processing details: Generative artificial intelligence generates proposals and identifies the optimal solution.

[1506] Input: Input data for AI

[1507] Output: Generated proposals

[1508] Specific operation: The AI ​​model executes a proposal generation algorithm and outputs solutions tailored to the company's needs in text format.

[1509] Step 3:

[1510] Subject: Server

[1511] Processing details: Send the generated suggestions to the terminal.

[1512] Input: Generated proposal

[1513] Output: Suggestion data to the terminal

[1514] Specific operation: Format the proposed data in JSON format and send it to the terminal as an HTTPS response.

[1515] Feedback and Request for Suggestions

[1516] Step 1:

[1517] Subject: terminal

[1518] Processing details: The user reviews the proposal and provides feedback such as, "This looks good."

[1519] Input: Generated proposal

[1520] Output: Feedback input screen

[1521] Specific action: The user scrolls to review the suggestions and enters comments in the feedback text area.

[1522] Step 2:

[1523] Subject: User

[1524] Processing steps: Click the "Request Proposal" button for any proposals you like.

[1525] Input: Suggestion

[1526] Output: Request for Proposal Details Input Screen

[1527] Specific operation: The user clicks the "Request a Proposal" button and is redirected to a detailed input form that appears as a pop-up.

[1528] Step 3:

[1529] Subject: terminal

[1530] Processing details: Enter the details of the request for proposal and send them to the server.

[1531] Input: Request for Proposal Details

[1532] Output: Request for Proposal data to the server

[1533] Specific operation: The data from the detailed input form is temporarily stored in memory, and an HTTPS request is created and sent to the server.

[1534] Step 4:

[1535] Subject: Server

[1536] Processing details: Send a request for proposal to a business and record it in the database.

[1537] Input: Request for Proposal Data

[1538] Output: Request for proposal notification to businesses, database record

[1539] Specific operation: Save the proposal request details to the database and simultaneously send notifications to businesses via email or API call.

[1540] Step 5:

[1541] Subject: Server

[1542] Processing details: Notify the user of follow-up from the service provider.

[1543] Input: Follow-up information from the business operator

[1544] Output: Notification to the user

[1545] Specific actions: Receive communications from businesses and send push notifications or emails to users.

[1546] This enables the system to effectively generate digitalization and digital transformation proposals tailored to user needs, and to consistently manage the feedback and request for proposal processes.

[1547] (Application Example 1)

[1548] 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."

[1549] This system aims to solve the problem of companies lagging behind in traditional digitalization and digital transformation finding it difficult to effectively receive proposals for digitalization and digital transformation. It also aims to provide a system that enables logistics centers and field personnel to receive accurate, real-time proposals to address challenges in improving the efficiency of inventory management and shipping operations.

[1550] 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.

[1551] In this invention, the server includes means for a user to input company information, means for a user to input needs and challenges related to digitalization and digital transformation, means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon, means for displaying the proposals generated by the generative artificial intelligence to the user, means for a user to input feedback based on the proposals, means for a user to request proposals they like, means for forwarding proposal requests to businesses and managing the progress of follow-up, means for a user to input on-site conditions and needs via a smart device and check the generated proposals in real time, and means for creating prompt sentences for the generative artificial intelligence to generate proposals regarding the efficiency of the logistics center. This enables companies and logistics centers to efficiently receive proposals for digitalization and digital transformation, and to optimize operations and improve efficiency.

[1552] "Company information" refers to basic company information entered by the user, including company name, job title, contact information, etc.

[1553] "Digitalization" means streamlining analog and manual business processes using digital technology.

[1554] "Digital transformation" refers to a company fundamentally changing its business model and operational processes by utilizing digital technologies.

[1555] "Challenges" refer to specific problems or needs that users wish to solve in the context of digitalization and digital transformation.

[1556] "Generative artificial intelligence" is an artificial intelligence technology that automatically generates optimal suggestions based on input data.

[1557] A "proposal" refers to a solution or solution generated by generative artificial intelligence in response to a company's needs and challenges.

[1558] "Feedback" refers to the evaluations and opinions that users provide regarding the generated suggestions.

[1559] A "Request for Proposal" is an action taken by a user to ask a business to implement a proposal they like.

[1560] A "smart device" refers to a device such as a smartphone or head-mounted display that allows the user to input on-site conditions and needs, and then view the generated suggestions in real time.

[1561] A "prompt statement" is an instruction given to a generative artificial intelligence system to generate specific suggestions.

[1562] "Inventory management" refers to the process of properly managing inventory levels in a logistics center and replenishing or ordering products at the optimal time.

[1563] "Shipping operations" refers to the process of preparing and processing shipments of goods at a logistics center.

[1564] This invention relates to a system that allows field personnel at a logistics center to receive suggestions for efficiency improvements using smart devices. The system is configured so that the user (field personnel) inputs the situation, needs, and challenges at the site through a device such as a smartphone or head-mounted display, and based on that, generative artificial intelligence proposes the optimal solution.

[1565] Hardware environment and software configuration

[1566] 1. Terminal: This refers to devices such as smartphones and head-mounted displays used by users in the field. This allows users to input company information, needs, and challenges, and view generated proposals in real time.

[1567] 2. Server: Runs on the cloud and analyzes information received from users to generate suggestions. Specifically, it uses a cloud service such as Amazon Web Services (AWS).

[1568] 3. Generative Artificial Intelligence: Generative AI models such as OpenAI's GPT-3 are used to generate appropriate suggestions based on user input. This involves generating prompt sentences based on the data entered by the user and inputting them into the AI ​​model.

[1569] 4. Application: Installed on the device, it provides an interface for users to input company information and on-site challenges, receive suggestions, and provide feedback. The application is developed using a cross-platform framework such as React Native or Flutter.

[1570] Processing flow

[1571] 1. User input:

[1572] Users input company information, on-site conditions, needs, and challenges using applications installed on their smart devices.

[1573] 2. Data transmission:

[1574] The terminal sends the entered information to the server. The data is sent via a secure communication protocol (e.g., HTTPS).

[1575] 3. Parsing and prompt generation:

[1576] The server cleans and normalizes the received data and generates prompt sentences for input to the generative artificial intelligence.

[1577] 4. Proposal generation:

[1578] Generative artificial intelligence generates optimal suggestions based on the prompt text and returns them to the server in JSON format.

[1579] 5. Display of proposals:

[1580] The server sends the generated suggestions to the user's terminal, allowing the user to review them in real time.

[1581] 6. Feedback and requests:

[1582] Users provide feedback on the generated proposals and submit requests for proposals to implement the ones they like.

[1583] Specific example

[1584] Example of a prompt

[1585] Please generate proposals to improve operational efficiency at the logistics center. Below are the main challenges and requirements from the field.

[1586] The inventory management system is outdated and inefficient.

[1587] There are many mistakes in the shipping process.

[1588] Designing efficient delivery routes is difficult.

[1589] Requirements:

[1590] 1. Optimizing inventory management

[1591] 2. Reducing shipping errors

[1592] 3. Optimizing delivery routes.

[1593] By inputting the above prompts into a generative artificial intelligence system, the AI ​​generates suggestions such as updating inventory management systems, checklist tools to reduce errors in shipping operations, and AI-based delivery route design tools.

[1594] This invention contributes to an efficient solution proposal system that utilizes generative artificial intelligence to solve real-world problems in logistics centers in real time.

[1595] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1596] Step 1:

[1597] The user launches an application installed on their smart device and inputs company information, on-site conditions, needs, and challenges.

[1598] Input: Company name, job title, contact information, on-site situation, challenges / needs

[1599] Output: Input data in JSON format

[1600] Specific operation: The user follows the interface, enters the required information into the form, and presses the "Submit" button.

[1601] Step 2:

[1602] The terminal sends the entered information to the server.

[1603] Input: JSON format data containing company information, on-site conditions, and challenges / needs entered by the user.

[1604] Output: HTTP request to the server

[1605] Specific operation: The terminal uses the HTTPS protocol to send input data to the server's API endpoint.

[1606] Step 3:

[1607] The server cleans and normalizes the data it receives.

[1608] Input: JSON format data sent from the device.

[1609] Output: Cleaned and normalized data

[1610] Specific operation: The server checks the data format and invalid values, and converts them to the correct format.

[1611] Step 4:

[1612] The server generates prompt text to be input to the generative artificial intelligence based on cleaned and normalized data.

[1613] Input: Cleaned and normalized data

[1614] Output: Prompt text to input to the generative artificial intelligence.

[1615] Specific operation: The server generates a prompt message with the input data embedded, based on a template.

[1616] Step 5:

[1617] The generative artificial intelligence generates the optimal suggestion based on the prompt text.

[1618] Input: Prompt message

[1619] Output: Generated proposals (in JSON format)

[1620] Specific operation: The generative artificial intelligence analyzes the prompt text and generates an appropriate solution as a suggestion.

[1621] Step 6:

[1622] The server sends the generated proposal to the user's terminal.

[1623] Input: Generated suggestions (in JSON format)

[1624] Output: Suggestion data sent to the user's terminal.

[1625] Specific operation: The server uses the HTTPS protocol to send the generated proposal to the user's terminal.

[1626] Step 7:

[1627] The device displays suggestions it has received to the user.

[1628] Input: Proposal data sent from the server

[1629] Output: Suggestions displayed to the user

[1630] Specific operation: The terminal analyzes the received suggestion data and displays it through the user interface.

[1631] Step 8:

[1632] Users provide feedback on the generated proposals and press the "Request Proposal" button to implement the proposals they like.

[1633] Input: Feedback, details of the request for proposal

[1634] Output: Feedback and suggestion data sent to the server

[1635] Specific operation: The user reviews the proposal, enters details of feedback or a request for proposal on the interface, and submits it.

[1636] Step 9:

[1637] The server forwards user feedback and requests for suggestions to the service provider and manages the progress of follow-up.

[1638] Input: Feedback, Request for Proposal data

[1639] Output: Data for managing the progress of communication and follow-up with service providers.

[1640] Specific operation: The server forwards the received feedback and requests for suggestions to the relevant service providers and updates the database for progress management.

[1641] 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.

[1642] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. This system has a function where the user inputs company information, needs, and challenges, and based on this, generative artificial intelligence generates proposals and displays them to the user. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, it can provide more personalized proposals.

[1643] System Configuration

[1644] 1. Terminal: A device on which an application is installed and which the user operates through an interface. The terminal is used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[1645] 2. Server: This server is responsible for analyzing information received from the user, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. It also receives requests for suggestions and manages the progress of follow-up. Furthermore, an emotion engine is integrated into the server to analyze the user's emotions.

[1646] 3. Emotion Engine: This engine recognizes and analyzes emotions through user input and actions. This emotional information is provided to the generative artificial intelligence, which adjusts the suggested content and presentation methods based on the user's emotions.

[1647] Program processing flow

[1648] Initial setup and user registration

[1649] 1. Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[1650] 2. User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[1651] 3. Terminal: Sends the entered information to the server.

[1652] 4. Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[1653] Confirming needs and challenges

[1654] 1. Terminal: After the user logs in, a survey screen regarding DX will be displayed. Question items (e.g., "Current state of digitalization," "Issues you want to solve," etc.) will be displayed.

[1655] 2. User: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[1656] 3. Terminal: Sends the response content to the server.

[1657] 4. Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[1658] Proposal generation using generative artificial intelligence and an emotion engine.

[1659] 1. Server: Based on survey results and user input data, the server inputs the data into a generative artificial intelligence. The AI ​​is then given specific tasks such as "optimizing inventory management" or "customer data analysis."

[1660] 2. Server: The emotion engine analyzes user input and actions to understand emotions and provides that emotional information to the generative artificial intelligence.

[1661] 3. Server: Generative artificial intelligence considers the user's emotional information to generate suggestions and identify the optimal solution. For example, specific solutions such as "implementation of an inventory management system" or "suggestion of a customer data analysis tool" are generated.

[1662] 4. Server: Sends the generated proposal to the terminal.

[1663] Display of proposals and feedback

[1664] 1. Terminal: Displays the generated proposal to the user. Displays details of the proposal content (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[1665] 2. User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[1666] 3. Terminal: Sends the feedback content to the server.

[1667] Request for Proposal and Follow-up

[1668] 1. User: If satisfied with the proposal, press the "Request Proposal" button.

[1669] 2. Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[1670] 3. Terminal: Sends the entered proposal request details to the server.

[1671] 4. Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[1672] 5. Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[1673] 6. Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[1674] Specific example

[1675] Digitalization of retail stores and emotion recognition

[1676] 1. Terminal: Retail store executives install the app and register company information.

[1677] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[1678] 3. Terminal: Sends the response content and user input data to the server.

[1679] 4. Server: Consider that the generative AI generates solutions including "implementation of store inventory management systems" and "proposals for customer data analysis tools," and the emotion engine provides user emotion data.

[1680] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[1681] 6. User: If you like a proposal, press the "Request Proposal" button.

[1682] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[1683] 8. Server: Sends requests for proposals to service providers and records them in the database.

[1684] 9. Server: You will receive follow-up contact from the service provider's representative.

[1685] Thus, this system is configured to effectively support the digitalization and digital transformation of small and medium-sized enterprises. Furthermore, by recognizing user emotions and reflecting that information in suggestion generation, it is possible to provide more personalized suggestions.

[1686] The following describes the processing flow.

[1687] Step 1:

[1688] Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[1689] Step 2:

[1690] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[1691] Step 3:

[1692] Terminal: Sends the entered information to the server.

[1693] Step 4:

[1694] Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[1695] Step 5:

[1696] Terminal: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed. Question items (e.g., "Current digitalization status," "Issues you want to solve," etc.) will be displayed.

[1697] Step 6:

[1698] User: Answer the survey and enter the required information. Press the "Submit" button.

[1699] Step 7:

[1700] Terminal: Sends the response content to the server.

[1701] Step 8:

[1702] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[1703] Step 9:

[1704] Server: Based on the survey results, input data into the generative artificial intelligence. Set specific tasks for the AI, such as "optimizing inventory management" or "customer data analysis."

[1705] Step 10:

[1706] Server: The emotion engine analyzes user emotions from input and actions and provides that emotional information to the generative artificial intelligence.

[1707] Step 11:

[1708] Server: Generative artificial intelligence considers user sentiment information to generate suggestions and identify the optimal solution. For example, it generates specific solutions such as "implementing an inventory management system" or "proposing a customer data analysis tool."

[1709] Step 12:

[1710] Server: Sends the generated proposal to the terminal.

[1711] Step 13:

[1712] Terminal: Displays the generated proposal to the user. Displays details of the proposal (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[1713] Step 14:

[1714] User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[1715] Step 15:

[1716] Terminal: Sends feedback to the server.

[1717] Step 16:

[1718] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[1719] Step 17:

[1720] Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[1721] Step 18:

[1722] Terminal: Sends the entered request for proposal details to the server.

[1723] Step 19:

[1724] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[1725] Step 20:

[1726] Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[1727] Step 21:

[1728] Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[1729] (Example 2)

[1730] 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."

[1731] In modern businesses, digitalization and digital transformation (DX) are essential for improving operational efficiency and maintaining competitiveness. However, especially in small and medium-sized enterprises (SMEs), management often lacks sufficient knowledge and resources for these transformations, frequently delaying the implementation of DX. Furthermore, standard DX proposals alone are insufficient to adequately address the unique challenges and needs of each company, making it difficult to provide optimal solutions. Moreover, conventional proposal systems fail to adequately reflect user emotions and feedback, resulting in insufficient personalization.

[1732] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server has an emotion engine that analyzes emotions from user input and operations, and includes means for providing emotion information to the generative artificial intelligence, means for adjusting the proposed content and presentation method based on the emotion information, and means for forwarding the proposal request to the business operator and managing the progress of follow-up. As a result, not only is the optimal digitalization and DX proposal for the user's specific needs and challenges generated, but personalized proposals and feedback that take the user's emotions into consideration are also possible.

[1733] "Digitalization" refers to managing a company's business processes and information electronically to improve efficiency and automate them.

[1734] "Digital transformation (DX)" refers to fundamentally changing a company's business processes and business models by utilizing digital technologies, thereby improving its competitiveness.

[1735] "Company information" refers to basic information used to identify a company, such as its name, job title, and contact information.

[1736] "Needs and challenges" refer to a company's requirements and problems related to digitalization and digital transformation.

[1737] "Generative artificial intelligence" refers to artificial intelligence that has algorithms for generating optimal digitalization and DX proposals based on data input from users.

[1738] An "emotion engine" refers to a system that analyzes emotions from user input and actions and provides that information to a generative artificial intelligence system.

[1739] "Proposal" refers to a specific solution generated by generative artificial intelligence based on the user's needs and challenges.

[1740] "Feedback" refers to the opinions and evaluations that users provide regarding the proposed content.

[1741] A "Request for Proposal" refers to a request for specific actions based on a proposal that the user likes.

[1742] "Follow-up" refers to managing the progress of the business's implementation of the requested proposal and notifying the user of that progress.

[1743] System Overview

[1744] This invention provides a system that enables management in companies lagging behind in digitalization and digital transformation (DX) to more effectively receive proposals for digitalization and DX. The system includes an interface for users to input company information, needs, and challenges, a generative artificial intelligence, an emotion engine, and follow-up management functions.

[1745] Hardware and software to be used

[1746] This system includes the following components:

[1747] Terminal: A device on which an application is installed and which the user operates through an interface. Terminals are used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[1748] Examples of use: smartphones, tablets, and personal computers.

[1749] Example of software used: Application interface.

[1750] The server is responsible for analyzing information received from the user, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. It also receives requests for suggestions and manages the progress of follow-up. Furthermore, an emotion engine is integrated into the server to analyze the user's emotions.

[1751] Examples of use: cloud servers, on-premises servers.

[1752] Examples of software used: database management systems, artificial intelligence models (generative AI), and sentiment analysis engines.

[1753] Emotion Engine: This engine recognizes and analyzes emotions through user input and actions. This emotional information is provided to a generative artificial intelligence system, which adjusts the suggested content and presentation methods based on the user's emotions.

[1754] Examples of use: machine learning models, sentiment analysis algorithms.

[1755] System Operation Overview

[1756] 1. Initial setup and user registration

[1757] Terminal: The user installs and launches the application, and the new user registration screen is displayed.

[1758] User: Enter company name, job title, contact information, etc., and press the "Register" button.

[1759] Terminal: Sends the entered information to the server.

[1760] Server: Saves user information to the database, generates a new user ID, and sends it back.

[1761] 2. Identifying needs and challenges

[1762] Terminal: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed.

[1763] User: Answer the questionnaire and enter your specific needs and challenges.

[1764] Terminal: Sends the response content to the server.

[1765] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[1766] 3. Proposal generation using generative artificial intelligence and an emotion engine

[1767] Server: Based on survey results and user input data, it inputs data into the generative artificial intelligence.

[1768] Server: The emotion engine analyzes emotional information obtained from user input and actions and provides it to the generative artificial intelligence.

[1769] Server: Generative artificial intelligence generates suggestions while considering the user's emotional information.

[1770] Server: Sends the generated proposal to the terminal.

[1771] 4. Display of proposals and feedback

[1772] Terminal: Displays generated suggestions to the user.

[1773] User: Review the proposal and enter your feedback.

[1774] Terminal: Sends feedback to the server.

[1775] 5. Request for Proposal and Follow-up

[1776] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[1777] Terminal: Displays a form for entering details of the "Request for Proposal," and the user enters the details and submits it.

[1778] Terminal: Sends the entered request for proposal details to the server.

[1779] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[1780] Server: Sends a request for proposal notification to the service provider's representative and follows up.

[1781] Server: Manages the progress of follow-ups and notifies users as needed.

[1782] Specific example

[1783] Examples of use in the retail industry

[1784] 1. Terminal: Retail store executives install the app and register company information.

[1785] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[1786] 3. Terminal: Sends the response content and user input data to the server.

[1787] 4. Server: Consider that the generative AI generates solutions including "implementation of store inventory management systems" and "proposals for customer data analysis tools," and the emotion engine provides user emotion data.

[1788] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[1789] 6. User: If you like a proposal, press the "Request Proposal" button.

[1790] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[1791] 8. Server: Sends requests for proposals to service providers and records them in the database.

[1792] 9. Server: You will receive follow-up contact from the service provider's representative.

[1793] Example of a prompt

[1794] "Our company is struggling with efficient inventory management and has challenges in analyzing customer data. Please provide specific suggestions for solving these problems."

[1795] In this way, this system can address the individual needs of companies and, by taking emotional information into consideration, provide more personalized digitalization and DX proposals.

[1796] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1797] Processing steps

[1798] Initial setup and user registration

[1799] Step 1:

[1800] Terminal: The user installs and launches a system-specific application, and the "New User Registration" button is displayed.

[1801] Input: The user installs and launches the application.

[1802] Output: The "New User Registration" button will appear on the app's initial launch screen.

[1803] Step 2:

[1804] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[1805] Input: User's basic information (company name, job title, contact information).

[1806] Output: Registration information is sent to the terminal.

[1807] Step 3:

[1808] Terminal: Sends the entered information to the server.

[1809] Input: User's basic information.

[1810] Output: User information is sent to the server.

[1811] Step 4:

[1812] Server: Stores the received user information in the database, generates a new user ID, and sends it back.

[1813] Input: User information received from the terminal.

[1814] Output: Information stored in the database and a new user ID.

[1815] Confirming needs and challenges

[1816] Step 1:

[1817] Terminal: After the user logs in, a survey screen about DX (Digital Transformation) will be displayed. Questions will include "Current state of digitalization" and "Issues you want to solve."

[1818] Input: User login information.

[1819] Output: The survey screen is displayed.

[1820] Step 2:

[1821] User: Answer the questionnaire, enter specific needs and challenges in the text box, and press the "Submit" button.

[1822] Input: Survey responses.

[1823] Output: The answer is entered into the terminal.

[1824] Step 3:

[1825] Terminal: Sends the response content to the server.

[1826] Input: Survey responses.

[1827] Output: The response is sent to the server.

[1828] Step 4:

[1829] Server: Receives the response content, analyzes it, and prepares the data necessary for the generative artificial intelligence to generate proposals.

[1830] Input: Answer content.

[1831] Output: Data is prepared for input into a generative artificial intelligence.

[1832] Proposal generation using generative artificial intelligence and an emotion engine.

[1833] Step 1:

[1834] Server: Inputs data into a generative artificial intelligence system based on survey results and user input data. The AI ​​then sets specific tasks (e.g., "Optimize inventory management," "Analyze customer data").

[1835] Input: Survey results and user input data.

[1836] Output: Data input to a generative artificial intelligence.

[1837] Step 2:

[1838] Server: The emotion engine analyzes emotional information obtained from user input and actions, and provides that information to the generative artificial intelligence.

[1839] Input: User sentiment information.

[1840] Output: Emotional information provided to the generative artificial intelligence.

[1841] Step 3:

[1842] Server: Generative artificial intelligence generates suggestions while considering the user's emotional information. For example, "Implementation of an inventory management system" or "Suggestion of a customer data analysis tool."

[1843] Input: Survey results, user sentiment information.

[1844] Output: Generated proposals.

[1845] Step 4:

[1846] Server: Sends the generated proposal to the terminal.

[1847] Input: Generated suggestions.

[1848] Output: Suggestions sent to the terminal.

[1849] Display of proposals and feedback

[1850] Step 1:

[1851] Terminal: Displays generated proposals to the user. The proposals include detailed information such as "Overview of the inventory management system" and "Benefits of implementation."

[1852] Input: Suggestions sent from the server.

[1853] Output: The suggested content is displayed to the user.

[1854] Step 2:

[1855] User: Review the proposal and check the feedback. Enter comments such as "This looks good" or "I'd like more specific information," and submit.

[1856] Input: User feedback.

[1857] Output: Feedback entered into the terminal.

[1858] Step 3:

[1859] Terminal: Sends feedback to the server.

[1860] Input: Feedback content.

[1861] Output: Feedback sent to the server.

[1862] Request for Proposal and Follow-up

[1863] Step 1:

[1864] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[1865] Input: User action (pressing the "Request Proposal" button).

[1866] Output: The Request for Proposal screen is displayed.

[1867] Step 2:

[1868] Terminal: A form is displayed for the user to enter details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[1869] Input: Details of the Request for Proposal.

[1870] Output: Details of the request for proposal entered into the terminal.

[1871] Step 3:

[1872] Terminal: Sends the entered request for proposal details to the server.

[1873] Input: Details of the Request for Proposal.

[1874] Output: Details of the request for proposal sent to the server.

[1875] Step 4:

[1876] Server: Transfers the details of the Request for Proposal to the service provider and records the relevant data in the database.

[1877] Input: Details of the Request for Proposal.

[1878] Output: Details of the Request for Proposal forwarded to the service provider, and data recorded in the database.

[1879] Step 5:

[1880] Server: Sends a request for proposal notification to the service provider's representative, and the follow-up representative takes specific actions.

[1881] Input: Details of the Request for Proposal.

[1882] Output: Notification to the business representative and follow-up actions.

[1883] Step 6:

[1884] Server: Manages the progress of follow-ups and notifies users as needed. This includes updating statuses such as "An agent will contact you shortly."

[1885] Input: Follow-up progress.

[1886] Output: Notifications to the user and status updates.

[1887] (Application Example 2)

[1888] 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."

[1889] In today's world, many companies are lagging behind in digitalization and digital transformation (DX). This lag is particularly pronounced in small and medium-sized enterprises (SMEs), resulting in decreased competitiveness and operational efficiency. Furthermore, management lacks a suitable system for receiving concrete solution proposals, making it difficult to promote digitalization. Moreover, proposals are often uniform and do not align with the feelings and needs of management. A system is needed to solve these problems.

[1890] 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.

[1891] In this invention, the server includes means for the user to input corporate information, means for the user to input needs and challenges related to digitalization and digital transformation, means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon, means incorporating an emotion recognition engine that analyzes the user's input information and emotion information to generate personalized proposals, means for displaying the proposals generated by the generative artificial intelligence to the user, means for the user to input feedback based on the proposals, means for the user to request proposals they like, and means for forwarding proposal requests to service providers and managing the progress of follow-up. This makes it possible for users to receive personalized proposals based on their specific needs and emotions, thereby effectively advancing the digitalization and digital transformation of companies.

[1892] "Means for inputting company information" refers to interfaces or data entry systems for inputting basic company information.

[1893] "Means for inputting needs and challenges" refers to interfaces or database systems that allow users to input their needs and challenges related to digitalization and digital transformation.

[1894] "Generative artificial intelligence" is a type of artificial intelligence that analyzes input data and generates optimal suggestions based on that analysis.

[1895] "Methods for incorporating an emotion recognition engine" refers to methods for integrating an engine into the system that recognizes emotions from user input information and reflects that emotion data in suggestion generation.

[1896] "Means for displaying proposals to users" refers to displays and interfaces that make generated proposals easy for users to understand.

[1897] "Means for inputting feedback" refer to interfaces or data collection systems that allow users to input reactions and opinions on suggestions.

[1898] "Means for requesting proposals" refers to interfaces and notification systems that allow users to actually request proposals they like.

[1899] "Means for forwarding requests for proposals to service providers and managing the progress of follow-up" refers to systems and servers that forward user requests for proposals to service providers and manage and monitor their subsequent progress.

[1900] This invention is a system for management in companies lagging behind in digitalization and digital transformation to receive proposals for digitalization and DX. The system has a function where the user inputs company information, needs, and challenges, and based on this, generative artificial intelligence generates optimal proposals, which are then displayed to the user. Furthermore, by combining this with an emotion recognition engine that recognizes the user's emotions, it can provide more personalized proposals.

[1901] System Configuration

[1902] 1. Terminal

[1903] A terminal is a device on which an application is installed and which the user operates through an interface. This terminal is equipped with means for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[1904] 2. Server

[1905] The server is responsible for analyzing information received from the user, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. It also receives requests for suggestions and manages the progress of follow-up. Furthermore, an emotion recognition engine is integrated into the server to analyze the user's emotions.

[1906] 3. Emotion Recognition Engine

[1907] The emotion recognition engine recognizes and analyzes emotions through user input and actions. This emotion information is provided to a generative artificial intelligence system, which then adjusts the suggested content and presentation methods based on the user's emotions.

[1908] Program processing and hardware / software

[1909] The system utilizes Flask as its framework and OpenAI's GPT-3 for generative artificial intelligence. It incorporates EmotionEngine as its emotion recognition engine to recognize and analyze user emotions.

[1910] Examples of specific cases and prompt statements

[1911] Specific example:

[1912] 1. User: Owner of a physical store. During registration, they entered "Inventory management is not efficient" and "Customer data analysis is difficult."

[1913] 2. Emotions: Emotions such as "anxiety" and "anticipation" are recognized from the user's input.

[1914] 3. Based on this user information, the generative artificial intelligence creates personalized suggestions.

[1915] Example of a prompt:

[1916] User Data: Inventory management is not efficient, customer data analysis is difficult.

[1917] User Emotion: Anxiety, Anticipation

[1918] Generate a personalized DX proposal for the user based on their input and emotion.

[1919] In this way, users can receive personalized suggestions based on their specific needs and emotions, which can effectively advance the company's digitalization and digital transformation.

[1920] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1921] Step 1:

[1922] User Registration

[1923] The user uses a terminal to enter basic information such as company name, job title, and contact information. The terminal receives this information and sends it to the server. The server stores the received information in a database, generates a user ID, and sends it back to the terminal.

[1924] Input: Company name, job title, contact information

[1925] Output: User ID

[1926] Step 2:

[1927] Inputting needs and challenges

[1928] The user uses a terminal to input their needs and challenges regarding digitalization and digital transformation. The terminal sends this information to a server. The server analyzes the received needs and challenges and prepares data for generative artificial intelligence to generate suggestions.

[1929] Input: Needs and challenges related to digitalization and DX

[1930] Output: Data required for proposal generation

[1931] Step 3:

[1932] emotion recognition

[1933] An emotion recognition engine embedded in the server analyzes the user's input information and recognizes the user's emotions. The recognized emotion information is provided to a generative artificial intelligence system. As a result, suggestions are personalized based on the user's emotions.

[1934] Input: User input information

[1935] Output: User sentiment information

[1936] Step 4:

[1937] Proposal generation using generative artificial intelligence

[1938] The server inputs data into the generative artificial intelligence (AI) based on the user's needs and challenges. The generative AI then generates appropriate suggestions using prompts. For example, it might generate suggestions for optimizing inventory management or analyzing customer data.

[1939] Input: User needs, challenges, and emotional information

[1940] Output: Personalized suggestions

[1941] Step 5:

[1942] Display of proposals and feedback

[1943] The terminal displays the generated suggestions to the user. The user reviews the suggestions and enters feedback. The terminal sends this feedback to the server. The server analyzes the received feedback and updates the suggestions as needed.

[1944] Input: User feedback

[1945] Output: Updated proposal

[1946] Step 6:

[1947] Request for Proposal and Follow-up

[1948] To request a proposal they like, the user enters details using a terminal. The terminal sends this information to the server. The server forwards the request for proposal to the service provider and records it in a database. It also manages the progress of follow-up and notifies the user as needed.

[1949] Input: Details of the Request for Proposal (e.g., desired implementation period, budget, etc.)

[1950] Output: Forwarding of Request for Proposal, follow-up progress notification

[1951] 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.

[1952] 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.

[1953] 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.

[1954] [Fourth Embodiment]

[1955] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1956] 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.

[1957] 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).

[1958] 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.

[1959] 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.

[1960] 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).

[1961] 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.

[1962] 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.

[1963] 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.

[1964] 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.

[1965] 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.

[1966] 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.

[1967] 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".

[1968] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. The system has a function where the user inputs company information, needs, and challenges, and based on this, a generative artificial intelligence generates proposals, which are then displayed to the user. It also provides a means for the user to input feedback on the proposals and request the preferred proposals from service providers.

[1969] System Configuration

[1970] 1. Terminal: A device on which an application is installed and which the user operates through an interface. The terminal is used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[1971] 2. Server: This server is responsible for analyzing information received from users, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. This also includes receiving requests for suggestions and managing the progress of follow-up.

[1972] Program processing flow

[1973] Initial setup and user registration

[1974] 1. Terminal: The user installs and launches the application. The "New User Registration" option is displayed on the screen.

[1975] 2. User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[1976] 3. Terminal: Sends the entered information to the server.

[1977] 4. Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[1978] Confirming needs and challenges

[1979] 1. Terminal: After the user logs in, a survey screen regarding DX will be displayed. Question items may include, for example, "Current state of digitalization" and "Issues you want to solve."

[1980] 2. User: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[1981] 3. Terminal: Sends the response content to the server.

[1982] 4. Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[1983] Proposal generation using generative artificial intelligence

[1984] 1. Server: Based on the survey results, the server inputs the data into a generative artificial intelligence. The AI ​​then sets specific tasks such as "optimizing inventory management" or "customer data analysis."

[1985] 2. Server: Generative artificial intelligence generates proposals and identifies the optimal solution. For example, specific solutions such as "implementation of an inventory management system" or "proposal of a customer data analysis tool" are generated.

[1986] 3. Server: Sends the generated proposal to the terminal.

[1987] Specific example

[1988] Digitalization of retail stores

[1989] 1. Terminal: Retail store executives install the app and register company information.

[1990] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[1991] 3. Terminal: Sends the response content to the server.

[1992] 4. Server: Generative artificial intelligence generates solutions, including "implementation of a store inventory management system" and "proposal of a customer data analysis tool," and sends them to the terminal.

[1993] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[1994] 6. User: If you like a proposal, press the "Request Proposal" button.

[1995] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[1996] 8. Server: Sends requests for proposals to service providers and records them in the database.

[1997] 9. Server: You will receive follow-up contact from the service provider's representative.

[1998] Thus, this system is configured to effectively support the digitalization and digital transformation of small and medium-sized enterprises.

[1999] The following describes the processing flow.

[2000] Step 1:

[2001] Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[2002] Step 2:

[2003] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[2004] Step 3:

[2005] Terminal: Sends the entered information to the server.

[2006] Step 4:

[2007] Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[2008] Step 5:

[2009] Terminal: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed. Question items (e.g., "Current digitalization status," "Issues you want to solve," etc.) will be displayed.

[2010] Step 6:

[2011] User: Answer the survey and enter the required information. Press the "Submit" button.

[2012] Step 7:

[2013] Terminal: Sends the response content to the server.

[2014] Step 8:

[2015] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[2016] Step 9:

[2017] Server: Based on the survey results, input data into the generative artificial intelligence. Set specific tasks for the AI, such as "optimizing inventory management" or "customer data analysis."

[2018] Step 10:

[2019] Server: Generative artificial intelligence generates proposals and identifies the optimal solution. For example, it generates specific solutions such as "implementation of an inventory management system" or "proposal of a customer data analysis tool."

[2020] Step 11:

[2021] Server: Sends the generated proposal to the terminal.

[2022] Step 12:

[2023] Terminal: Displays the generated proposal to the user. Displays details of the proposal (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[2024] Step 13:

[2025] User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[2026] Step 14:

[2027] Terminal: Sends feedback to the server.

[2028] Step 15:

[2029] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[2030] Step 16:

[2031] Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[2032] Step 17:

[2033] Terminal: Sends the entered request for proposal details to the server.

[2034] Step 18:

[2035] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[2036] Step 19:

[2037] Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[2038] Step 20:

[2039] Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[2040] (Example 1)

[2041] 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".

[2042] Many companies are lagging behind in digitalization and digital transformation (DX), and management lacks the means to receive appropriate proposals. Furthermore, there are insufficient mechanisms for management to provide quick and efficient feedback on proposals after they are received, as well as for forwarding requests for proposals to service providers and managing their progress. As a result, digitalization and DX initiatives are delayed, potentially leading to a decline in the overall competitiveness of the company.

[2043] 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.

[2044] In this invention, the server includes means for the user to input company information, means for the user to input needs and challenges related to digitalization and digital transformation, means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon, means for displaying the proposals generated by the generative artificial intelligence to the user, means for the user to input feedback based on the proposals, means for the user to request proposals they like, means for forwarding proposal requests to service providers and managing the progress of follow-up, means for sending details regarding the proposal requests to service providers, means for notifying the user of follow-up from service providers, and means for storing user information and proposal request information in a database. As a result, the user can receive comprehensive digitalization and DX proposals, provide feedback on those proposals, request proposals, and follow up on their progress.

[2045] "Company information" refers to information that identifies a company and indicates its basic attributes and characteristics, such as the company name, address, job title, and contact information.

[2046] "Needs and challenges" refer to the problems and demands that companies face regarding digitalization and digital transformation, including areas for improvement and hurdles to overcome.

[2047] "Generative artificial intelligence" refers to artificial intelligence that has the function of automatically generating suggestions and solutions tailored to a specific purpose based on the input data.

[2048] "Proposal" refers to solutions or improvement plans generated by generative artificial intelligence based on a company's needs and challenges.

[2049] "Feedback" refers to users providing evaluations and opinions on suggestions that have been made.

[2050] A "Request for Proposal" refers to a request from a user to take specific actions to implement a proposal they like.

[2051] A "business operator" refers to a provider of services or products for implementing a proposal, and plays a role in realizing the proposal requested by the user.

[2052] "Follow-up" refers to checking the progress and maintaining contact after a request for proposal has been accepted.

[2053] A "database" refers to an electronic record system that organizes and stores user information and requests for proposals, allowing them to be quickly retrieved when needed.

[2054] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. This system utilizes multiple hardware and software components, and has a function to generate proposals using generative artificial intelligence based on company information, needs, and challenges input by the user, and then provide these proposals to the user. It also provides a means for the user to input feedback on the proposals and to request preferred proposals from service providers.

[2055] Components

[2056] 1. Terminal: A device used by users to input company information, needs, and challenges, and to view and review the generated proposals.

[2057] Examples of hardware used: smartphones, tablets, PCs, etc.

[2058] Examples of software used: applications, web browsers, etc.

[2059] 2. Server: This is the central hub of the system, which analyzes information received from users and generates appropriate suggestions using generative artificial intelligence. It also has the function of receiving requests for suggestions and managing the progress of follow-up with businesses.

[2060] Examples of software used: Apache, NGINX, Python, generative AI models (e.g., GPT-3, BERT)

[2061] 3. Database: A system for storing user information and request for proposal information.

[2062] Examples of software used: MySQL, PostgreSQL

[2063] Initial setup and user registration

[2064] First, the user installs the application on their device and enters basic information such as company name, job title, and contact information. This information is sent from the device to the server, which stores it in a database, generates a user ID, and sends it back to the device.

[2065] Confirming needs and challenges

[2066] After the user logs in, the terminal displays a questionnaire about DX (Digital Transformation). The user answers questions such as "Current state of digitalization" and "Challenges to be solved," and sends the answers to the server. The server analyzes the answers, and a generative artificial intelligence prepares the data necessary for generating suggestions.

[2067] Proposal generation using generative artificial intelligence

[2068] The server inputs data into a generative artificial intelligence (AI) system based on the survey results. This AI then sets specific tasks such as "optimizing inventory management" and "customer data analysis" and generates suggestions. The generated suggestions are sent to the terminal and displayed to the user.

[2069] Feedback and Request for Suggestions

[2070] Users can review the generated proposals and provide feedback, including opinions and evaluations. For proposals they like, they can press the "Request Proposal" button, enter details, and send them to the server. The server then forwards this information to the service provider and manages its progress in a database. Follow-up requests from the service provider are notified to the user's device.

[2071] Specific example

[2072] Digitalization of retail stores

[2073] 1. Terminal: Retail store executives install the app and register company information.

[2074] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[2075] 3. Terminal: Sends the response content to the server.

[2076] 4. Server: Generative artificial intelligence generates solutions, including "implementation of a store inventory management system" and "proposal of a customer data analysis tool," and sends them to the terminal.

[2077] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[2078] 6. User: If you like a proposal, press the "Request Proposal" button.

[2079] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[2080] 8. Server: Sends requests for proposals to service providers and records them in the database.

[2081] 9. Server: You will receive follow-up contact from the service provider's representative.

[2082] Example of a prompt

[2083] The following text format is used as an example of a prompt message.

[2084] "Please propose ways to improve the efficiency of inventory management in retail stores."

[2085] "Please tell me how to optimize sales strategies through customer data analysis."

[2086] These prompts enable the generative AI model to generate proposals tailored to the company's needs.

[2087] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2088] Program processing flow

[2089] Initial setup and user registration

[2090] Step 1:

[2091] Subject: terminal

[2092] Process details: The user installs and launches the application.

[2093] Input: Tap the application icon

[2094] Output: Display the app's home screen.

[2095] Specific operation: When the user selects and taps an application from the device's home screen, the application launches and displays the new user registration screen.

[2096] Step 2:

[2097] Subject: User

[2098] Process details: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[2099] Input: Company name, job title, contact information

[2100] Output: Send input information

[2101] Specific operation: The user enters data into each form field and finally clicks the "Register" button.

[2102] Step 3:

[2103] Subject: terminal

[2104] Processing details: The entered information is sent to the server.

[2105] Input: Company information entered by the user

[2106] Output: HTTPS request to the server

[2107] Specific operation: The terminal temporarily stores the input data in memory, creates an HTTPS request, and sends it to the server.

[2108] Step 4:

[2109] Subject: Server

[2110] Processing details: The received user information is saved to the database, a user ID is generated, and it is sent back to the terminal.

[2111] Input: User information

[2112] Output: User ID

[2113] Specific operation: The server inserts the received information into the database, generates a new user ID (such as a UUID), and returns it to the terminal as a response.

[2114] Confirming needs and challenges

[2115] Step 1:

[2116] Subject: terminal

[2117] Processing details: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed.

[2118] Enter: Login information

[2119] Output: Survey screen

[2120] Specific behavior: If user authentication is successful, the survey screen will appear as a pop-up or in a new window.

[2121] Step 2:

[2122] Subject: User

[2123] Process: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[2124] Input: Needs and challenges related to DX

[2125] Output: Submitted response

[2126] Specific actions: The user answers questions using text areas or checkboxes and taps the "Submit" button.

[2127] Step 3:

[2128] Subject: terminal

[2129] Processing details: Send the response content to the server.

[2130] Input: User survey responses

[2131] Output: HTTPS request to the server

[2132] Specific operation: The device temporarily stores the survey data in memory, creates an HTTPS request, and sends it to the server.

[2133] Step 4:

[2134] Subject: Server

[2135] Processing details: The response content is analyzed, and the generative artificial intelligence prepares the data necessary for generating suggestions.

[2136] Input: Survey response data

[2137] Output: Analysis data for proposal generation

[2138] Specific operation: The server uses a natural language processing algorithm to analyze the response and converts the analysis results into a format suitable as input for an AI model.

[2139] Proposal generation using generative artificial intelligence

[2140] Step 1:

[2141] Subject: Server

[2142] Processing details: Based on the survey results, the data is input into a generative artificial intelligence system.

[2143] Input: Analyzed survey results

[2144] Output: Input data for AI

[2145] Specific operation: Convert data into the format required by the AI ​​model (JSON or a specific format) and provide it as input.

[2146] Step 2:

[2147] Subject: Server

[2148] Processing details: Generative artificial intelligence generates proposals and identifies the optimal solution.

[2149] Input: Input data for AI

[2150] Output: Generated proposals

[2151] Specific operation: The AI ​​model executes a proposal generation algorithm and outputs solutions tailored to the company's needs in text format.

[2152] Step 3:

[2153] Subject: Server

[2154] Processing details: Send the generated suggestions to the terminal.

[2155] Input: Generated proposal

[2156] Output: Suggestion data to the terminal

[2157] Specific operation: Format the proposed data in JSON format and send it to the terminal as an HTTPS response.

[2158] Feedback and Request for Suggestions

[2159] Step 1:

[2160] Subject: terminal

[2161] Processing details: The user reviews the proposal and provides feedback such as, "This looks good."

[2162] Input: Generated proposal

[2163] Output: Feedback input screen

[2164] Specific action: The user scrolls to review the suggestions and enters comments in the feedback text area.

[2165] Step 2:

[2166] Subject: User

[2167] Processing steps: Click the "Request Proposal" button for any proposals you like.

[2168] Input: Suggestion

[2169] Output: Request for Proposal Details Input Screen

[2170] Specific operation: The user clicks the "Request a Proposal" button and is redirected to a detailed input form that appears as a pop-up.

[2171] Step 3:

[2172] Subject: terminal

[2173] Processing details: Enter the details of the request for proposal and send them to the server.

[2174] Input: Request for Proposal Details

[2175] Output: Request for Proposal data to the server

[2176] Specific operation: The data from the detailed input form is temporarily stored in memory, and an HTTPS request is created and sent to the server.

[2177] Step 4:

[2178] Subject: Server

[2179] Processing details: Send a request for proposal to a business and record it in the database.

[2180] Input: Request for Proposal Data

[2181] Output: Request for proposal notification to businesses, database record

[2182] Specific operation: Save the proposal request details to the database and simultaneously send notifications to businesses via email or API call.

[2183] Step 5:

[2184] Subject: Server

[2185] Processing details: Notify the user of follow-up from the service provider.

[2186] Input: Follow-up information from the business operator

[2187] Output: Notification to the user

[2188] Specific actions: Receive communications from businesses and send push notifications or emails to users.

[2189] This enables the system to effectively generate digitalization and digital transformation proposals tailored to user needs, and to consistently manage the feedback and request for proposal processes.

[2190] (Application Example 1)

[2191] 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".

[2192] This system aims to solve the problem of companies lagging behind in traditional digitalization and digital transformation finding it difficult to effectively receive proposals for digitalization and digital transformation. It also aims to provide a system that enables logistics centers and field personnel to receive accurate, real-time proposals to address challenges in improving the efficiency of inventory management and shipping operations.

[2193] 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.

[2194] In this invention, the server includes means for a user to input company information, means for a user to input needs and challenges related to digitalization and digital transformation, means having a generative artificial intelligence that analyzes the needs and challenges and generates proposals based thereon, means for displaying the proposals generated by the generative artificial intelligence to the user, means for a user to input feedback based on the proposals, means for a user to request proposals they like, means for forwarding proposal requests to businesses and managing the progress of follow-up, means for a user to input on-site conditions and needs via a smart device and check the generated proposals in real time, and means for creating prompt sentences for the generative artificial intelligence to generate proposals regarding the efficiency of the logistics center. This enables companies and logistics centers to efficiently receive proposals for digitalization and digital transformation, and to optimize operations and improve efficiency.

[2195] "Company information" refers to basic company information entered by the user, including company name, job title, contact information, etc.

[2196] "Digitalization" means streamlining analog and manual business processes using digital technology.

[2197] "Digital transformation" refers to a company fundamentally changing its business model and operational processes by utilizing digital technologies.

[2198] "Challenges" refer to specific problems or needs that users wish to solve in the context of digitalization and digital transformation.

[2199] "Generative artificial intelligence" is an artificial intelligence technology that automatically generates optimal suggestions based on input data.

[2200] A "proposal" refers to a solution or solution generated by generative artificial intelligence in response to a company's needs and challenges.

[2201] "Feedback" refers to the evaluations and opinions that users provide regarding the generated suggestions.

[2202] A "Request for Proposal" is an action taken by a user to ask a business to implement a proposal they like.

[2203] A "smart device" refers to a device such as a smartphone or head-mounted display that allows the user to input on-site conditions and needs, and then view the generated suggestions in real time.

[2204] A "prompt statement" is an instruction given to a generative artificial intelligence system to generate specific suggestions.

[2205] "Inventory management" refers to the process of properly managing inventory levels in a logistics center and replenishing or ordering products at the optimal time.

[2206] "Shipping operations" refers to the process of preparing and processing shipments of goods at a logistics center.

[2207] This invention relates to a system that allows field personnel at a logistics center to receive suggestions for efficiency improvements using smart devices. The system is configured so that the user (field personnel) inputs the situation, needs, and challenges at the site through a device such as a smartphone or head-mounted display, and based on that, generative artificial intelligence proposes the optimal solution.

[2208] Hardware environment and software configuration

[2209] 1. Terminal: This refers to devices such as smartphones and head-mounted displays used by users in the field. This allows users to input company information, needs, and challenges, and view generated proposals in real time.

[2210] 2. Server: Runs on the cloud and analyzes information received from users to generate suggestions. Specifically, it uses a cloud service such as Amazon Web Services (AWS).

[2211] 3. Generative Artificial Intelligence: Generative AI models such as OpenAI's GPT-3 are used to generate appropriate suggestions based on user input. This involves generating prompt sentences based on the data entered by the user and inputting them into the AI ​​model.

[2212] 4. Application: Installed on the device, it provides an interface for users to input company information and on-site challenges, receive suggestions, and provide feedback. The application is developed using a cross-platform framework such as React Native or Flutter.

[2213] Processing flow

[2214] 1. User input:

[2215] Users input company information, on-site conditions, needs, and challenges using applications installed on their smart devices.

[2216] 2. Data transmission:

[2217] The terminal sends the entered information to the server. The data is sent via a secure communication protocol (e.g., HTTPS).

[2218] 3. Parsing and prompt generation:

[2219] The server cleans and normalizes the received data and generates prompt sentences for input to the generative artificial intelligence.

[2220] 4. Proposal generation:

[2221] Generative artificial intelligence generates optimal suggestions based on the prompt text and returns them to the server in JSON format.

[2222] 5. Display of proposals:

[2223] The server sends the generated suggestions to the user's terminal, allowing the user to review them in real time.

[2224] 6. Feedback and requests:

[2225] Users provide feedback on the generated proposals and submit requests for proposals to implement the ones they like.

[2226] Specific example

[2227] Example of a prompt

[2228] Please generate proposals to improve operational efficiency at the logistics center. Below are the main challenges and requirements from the field.

[2229] The inventory management system is outdated and inefficient.

[2230] There are many mistakes in the shipping process.

[2231] Designing efficient delivery routes is difficult.

[2232] Requirements:

[2233] 1. Optimizing inventory management

[2234] 2. Reducing shipping errors

[2235] 3. Optimizing delivery routes.

[2236] By inputting the above prompts into a generative artificial intelligence system, the AI ​​generates suggestions such as updating inventory management systems, checklist tools to reduce errors in shipping operations, and AI-based delivery route design tools.

[2237] This invention contributes to an efficient solution proposal system that utilizes generative artificial intelligence to solve real-world problems in logistics centers in real time.

[2238] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2239] Step 1:

[2240] The user launches an application installed on their smart device and inputs company information, on-site conditions, needs, and challenges.

[2241] Input: Company name, job title, contact information, on-site situation, challenges / needs

[2242] Output: Input data in JSON format

[2243] Specific operation: The user follows the interface, enters the required information into the form, and presses the "Submit" button.

[2244] Step 2:

[2245] The terminal sends the entered information to the server.

[2246] Input: JSON format data containing company information, on-site conditions, and challenges / needs entered by the user.

[2247] Output: HTTP request to the server

[2248] Specific operation: The terminal uses the HTTPS protocol to send input data to the server's API endpoint.

[2249] Step 3:

[2250] The server cleans and normalizes the data it receives.

[2251] Input: JSON format data sent from the device.

[2252] Output: Cleaned and normalized data

[2253] Specific operation: The server checks the data format and invalid values, and converts them to the correct format.

[2254] Step 4:

[2255] The server generates prompt text to be input to the generative artificial intelligence based on cleaned and normalized data.

[2256] Input: Cleaned and normalized data

[2257] Output: Prompt text to input to the generative artificial intelligence.

[2258] Specific operation: The server generates a prompt message with the input data embedded, based on a template.

[2259] Step 5:

[2260] The generative artificial intelligence generates the optimal suggestion based on the prompt text.

[2261] Input: Prompt message

[2262] Output: Generated proposals (in JSON format)

[2263] Specific operation: The generative artificial intelligence analyzes the prompt text and generates an appropriate solution as a suggestion.

[2264] Step 6:

[2265] The server sends the generated proposal to the user's terminal.

[2266] Input: Generated suggestions (in JSON format)

[2267] Output: Suggestion data sent to the user's terminal.

[2268] Specific operation: The server uses the HTTPS protocol to send the generated proposal to the user's terminal.

[2269] Step 7:

[2270] The device displays suggestions it has received to the user.

[2271] Input: Proposal data sent from the server

[2272] Output: Suggestions displayed to the user

[2273] Specific operation: The terminal analyzes the received suggestion data and displays it through the user interface.

[2274] Step 8:

[2275] Users provide feedback on the generated proposals and press the "Request Proposal" button to implement the proposals they like.

[2276] Input: Feedback, details of the request for proposal

[2277] Output: Feedback and suggestion data sent to the server

[2278] Specific operation: The user reviews the proposal, enters details of feedback or a request for proposal on the interface, and submits it.

[2279] Step 9:

[2280] The server forwards user feedback and requests for suggestions to the service provider and manages the progress of follow-up.

[2281] Input: Feedback, Request for Proposal data

[2282] Output: Data for managing the progress of communication and follow-up with service providers.

[2283] Specific operation: The server forwards the received feedback and requests for suggestions to the relevant service providers and updates the database for progress management.

[2284] 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.

[2285] This invention relates to a system for management in companies lagging behind in digitalization and digital transformation (DX) to receive proposals for digitalization and DX. This system has a function where the user inputs company information, needs, and challenges, and based on this, generative artificial intelligence generates proposals and displays them to the user. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, it can provide more personalized proposals.

[2286] System Configuration

[2287] 1. Terminal: A device on which an application is installed and which the user operates through an interface. The terminal is used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[2288] 2. Server: This server is responsible for analyzing information received from the user, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. It also receives requests for suggestions and manages the progress of follow-up. Furthermore, an emotion engine is integrated into the server to analyze the user's emotions.

[2289] 3. Emotion Engine: This engine recognizes and analyzes emotions through user input and actions. This emotional information is provided to the generative artificial intelligence, which adjusts the suggested content and presentation methods based on the user's emotions.

[2290] Program processing flow

[2291] Initial setup and user registration

[2292] 1. Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[2293] 2. User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[2294] 3. Terminal: Sends the entered information to the server.

[2295] 4. Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[2296] Confirming needs and challenges

[2297] 1. Terminal: After the user logs in, a survey screen regarding DX will be displayed. Question items (e.g., "Current state of digitalization," "Issues you want to solve," etc.) will be displayed.

[2298] 2. User: Answer the questionnaire and enter your specific needs and challenges. After entering the information, press the "Submit" button.

[2299] 3. Terminal: Sends the response content to the server.

[2300] 4. Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[2301] Proposal generation using generative artificial intelligence and an emotion engine.

[2302] 1. Server: Based on survey results and user input data, the server inputs the data into a generative artificial intelligence. The AI ​​is then given specific tasks such as "optimizing inventory management" or "customer data analysis."

[2303] 2. Server: The emotion engine analyzes user input and actions to understand emotions and provides that emotional information to the generative artificial intelligence.

[2304] 3. Server: Generative artificial intelligence considers the user's emotional information to generate suggestions and identify the optimal solution. For example, specific solutions such as "implementation of an inventory management system" or "suggestion of a customer data analysis tool" are generated.

[2305] 4. Server: Sends the generated proposal to the terminal.

[2306] Display of proposals and feedback

[2307] 1. Terminal: Displays the generated proposal to the user. Displays details of the proposal content (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[2308] 2. User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[2309] 3. Terminal: Sends the feedback content to the server.

[2310] Request for Proposal and Follow-up

[2311] 1. User: If satisfied with the proposal, press the "Request Proposal" button.

[2312] 2. Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[2313] 3. Terminal: Sends the entered proposal request details to the server.

[2314] 4. Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[2315] 5. Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[2316] 6. Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[2317] Specific example

[2318] Digitalization of retail stores and emotion recognition

[2319] 1. Terminal: Retail store executives install the app and register company information.

[2320] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[2321] 3. Terminal: Sends the response content and user input data to the server.

[2322] 4. Server: Consider that the generative AI generates solutions including "implementation of store inventory management systems" and "proposals for customer data analysis tools," and the emotion engine provides user emotion data.

[2323] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[2324] 6. User: If you like a proposal, press the "Request Proposal" button.

[2325] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[2326] 8. Server: Sends requests for proposals to service providers and records them in the database.

[2327] 9. Server: You will receive follow-up contact from the service provider's representative.

[2328] Thus, this system is configured to effectively support the digitalization and digital transformation of small and medium-sized enterprises. Furthermore, by recognizing user emotions and reflecting that information in suggestion generation, it is possible to provide more personalized suggestions.

[2329] The following describes the processing flow.

[2330] Step 1:

[2331] Terminal: Install and launch the application. The "New User Registration" button will appear on the screen.

[2332] Step 2:

[2333] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[2334] Step 3:

[2335] Terminal: Sends the entered information to the server.

[2336] Step 4:

[2337] Server: Stores the received user information in the database, generates a user ID, and sends it back to the terminal.

[2338] Step 5:

[2339] Terminal: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed. Question items (e.g., "Current digitalization status," "Issues you want to solve," etc.) will be displayed.

[2340] Step 6:

[2341] User: Answer the survey and enter the required information. Press the "Submit" button.

[2342] Step 7:

[2343] Terminal: Sends the response content to the server.

[2344] Step 8:

[2345] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[2346] Step 9:

[2347] Server: Based on the survey results, input data into the generative artificial intelligence. Set specific tasks for the AI, such as "optimizing inventory management" or "customer data analysis."

[2348] Step 10:

[2349] Server: The emotion engine analyzes user emotions from input and actions and provides that emotional information to the generative artificial intelligence.

[2350] Step 11:

[2351] Server: Generative artificial intelligence considers user sentiment information to generate suggestions and identify the optimal solution. For example, it generates specific solutions such as "implementing an inventory management system" or "proposing a customer data analysis tool."

[2352] Step 12:

[2353] Server: Sends the generated proposal to the terminal.

[2354] Step 13:

[2355] Terminal: Displays the generated proposal to the user. Displays details of the proposal (e.g., "Overview of the inventory management system," "Benefits of implementation," etc.).

[2356] Step 14:

[2357] User: Review the proposal and provide feedback. For example, send feedback such as "This looks good" or "I'd like more specific information."

[2358] Step 15:

[2359] Terminal: Sends feedback to the server.

[2360] Step 16:

[2361] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[2362] Step 17:

[2363] Terminal: Displays a form for entering details of the "Request for Proposal" (e.g., "Desired Implementation Period," "Budget," etc.). The user enters the details and presses the "Submit" button.

[2364] Step 18:

[2365] Terminal: Sends the entered request for proposal details to the server.

[2366] Step 19:

[2367] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[2368] Step 20:

[2369] Server: Sends a notification of the request for proposal to the service provider's representative. The representative then takes specific actions to follow up.

[2370] Step 21:

[2371] Server: Manages the progress of follow-ups and notifies users as needed. For example, it sends status updates such as "A representative will contact you shortly."

[2372] (Example 2)

[2373] 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".

[2374] In modern businesses, digitalization and digital transformation (DX) are essential for improving operational efficiency and maintaining competitiveness. However, especially in small and medium-sized enterprises (SMEs), management often lacks sufficient knowledge and resources for these transformations, frequently delaying the implementation of DX. Furthermore, standard DX proposals alone are insufficient to adequately address the unique challenges and needs of each company, making it difficult to provide optimal solutions. Moreover, conventional proposal systems fail to adequately reflect user emotions and feedback, resulting in insufficient personalization.

[2375] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server has an emotion engine that analyzes emotions from user input and operations, and includes means for providing emotion information to the generative artificial intelligence, means for adjusting the proposed content and presentation method based on the emotion information, and means for forwarding the proposal request to the business operator and managing the progress of follow-up. As a result, not only is the optimal digitalization and DX proposal for the user's specific needs and challenges generated, but personalized proposals and feedback that take the user's emotions into consideration are also possible.

[2376] "Digitalization" refers to managing a company's business processes and information electronically to improve efficiency and automate them.

[2377] "Digital transformation (DX)" refers to fundamentally changing a company's business processes and business models by utilizing digital technologies, thereby improving its competitiveness.

[2378] "Company information" refers to basic information used to identify a company, such as its name, job title, and contact information.

[2379] "Needs and challenges" refer to a company's requirements and problems related to digitalization and digital transformation.

[2380] "Generative artificial intelligence" refers to artificial intelligence that has algorithms for generating optimal digitalization and DX proposals based on data input from users.

[2381] An "emotion engine" refers to a system that analyzes emotions from user input and actions and provides that information to a generative artificial intelligence system.

[2382] "Proposal" refers to a specific solution generated by generative artificial intelligence based on the user's needs and challenges.

[2383] "Feedback" refers to the opinions and evaluations that users provide regarding the proposed content.

[2384] A "Request for Proposal" refers to a request for specific actions based on a proposal that the user likes.

[2385] "Follow-up" refers to managing the progress of the business's implementation of the requested proposal and notifying the user of that progress.

[2386] System Overview

[2387] This invention provides a system that enables management in companies lagging behind in digitalization and digital transformation (DX) to more effectively receive proposals for digitalization and DX. The system includes an interface for users to input company information, needs, and challenges, a generative artificial intelligence, an emotion engine, and follow-up management functions.

[2388] Hardware and software to be used

[2389] This system includes the following components:

[2390] Terminal: A device on which an application is installed and which the user operates through an interface. Terminals are used for inputting company information, needs, and challenges, displaying generated proposals, inputting feedback, and sending requests for proposals.

[2391] Examples of use: smartphones, tablets, and personal computers.

[2392] Example of software used: Application interface.

[2393] The server is responsible for analyzing information received from the user, generating appropriate suggestions using generative artificial intelligence, and sending them back to the terminal. It also receives requests for suggestions and manages the progress of follow-up. Furthermore, an emotion engine is integrated into the server to analyze the user's emotions.

[2394] Examples of use: cloud servers, on-premises servers.

[2395] Examples of software used: database management systems, artificial intelligence models (generative AI), and sentiment analysis engines.

[2396] Emotion Engine: This engine recognizes and analyzes emotions through user input and actions. This emotional information is provided to a generative artificial intelligence system, which adjusts the suggested content and presentation methods based on the user's emotions.

[2397] Examples of use: machine learning models, sentiment analysis algorithms.

[2398] System Operation Overview

[2399] 1. Initial setup and user registration

[2400] Terminal: The user installs and launches the application, and the new user registration screen is displayed.

[2401] User: Enter company name, job title, contact information, etc., and press the "Register" button.

[2402] Terminal: Sends the entered information to the server.

[2403] Server: Saves user information to the database, generates a new user ID, and sends it back.

[2404] 2. Identifying needs and challenges

[2405] Terminal: After the user logs in, a survey screen regarding DX (Digital Transformation) will be displayed.

[2406] User: Answer the questionnaire and enter your specific needs and challenges.

[2407] Terminal: Sends the response content to the server.

[2408] Server: Analyzes the responses and prepares the data necessary for the generative artificial intelligence to generate suggestions.

[2409] 3. Proposal generation using generative artificial intelligence and an emotion engine

[2410] Server: Based on survey results and user input data, it inputs data into the generative artificial intelligence.

[2411] Server: The emotion engine analyzes emotional information obtained from user input and actions and provides it to the generative artificial intelligence.

[2412] Server: Generative artificial intelligence generates suggestions while considering the user's emotional information.

[2413] Server: Sends the generated proposal to the terminal.

[2414] 4. Display of proposals and feedback

[2415] Terminal: Displays generated suggestions to the user.

[2416] User: Review the proposal and enter your feedback.

[2417] Terminal: Sends feedback to the server.

[2418] 5. Request for Proposal and Follow-up

[2419] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[2420] Terminal: Displays a form for entering details of the "Request for Proposal," and the user enters the details and submits it.

[2421] Terminal: Sends the entered request for proposal details to the server.

[2422] Server: Transfers the contents of the Request for Proposal to the service provider and records them in the database.

[2423] Server: Sends a request for proposal notification to the service provider's representative and follows up.

[2424] Server: Manages the progress of follow-ups and notifies users as needed.

[2425] Specific example

[2426] Examples of use in the retail industry

[2427] 1. Terminal: Retail store executives install the app and register company information.

[2428] 2. Users: Respond to the survey with statements such as "Inventory management is not efficient" and "Customer data analysis is difficult."

[2429] 3. Terminal: Sends the response content and user input data to the server.

[2430] 4. Server: Consider that the generative AI generates solutions including "implementation of store inventory management systems" and "proposals for customer data analysis tools," and the emotion engine provides user emotion data.

[2431] 5. Terminal: The user reviews the suggestion and provides feedback such as, "This looks good."

[2432] 6. User: If you like a proposal, press the "Request Proposal" button.

[2433] 7. Terminal: Enter the details of the request for proposal and send it to the server.

[2434] 8. Server: Sends requests for proposals to service providers and records them in the database.

[2435] 9. Server: You will receive follow-up contact from the service provider's representative.

[2436] Example of a prompt

[2437] "Our company is struggling with efficient inventory management and has challenges in analyzing customer data. Please provide specific suggestions for solving these problems."

[2438] In this way, this system can address the individual needs of companies and, by taking emotional information into consideration, provide more personalized digitalization and DX proposals.

[2439] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2440] Processing steps

[2441] Initial setup and user registration

[2442] Step 1:

[2443] Terminal: The user installs and launches a system-specific application, and the "New User Registration" button is displayed.

[2444] Input: The user installs and launches the application.

[2445] Output: The "New User Registration" button will appear on the app's initial launch screen.

[2446] Step 2:

[2447] User: Enter basic information such as company name, job title, and contact information, then press the "Register" button.

[2448] Input: User's basic information (company name, job title, contact information).

[2449] Output: Registration information is sent to the terminal.

[2450] Step 3:

[2451] Terminal: Sends the entered information to the server.

[2452] Input: User's basic information.

[2453] Output: User information is sent to the server.

[2454] Step 4:

[2455] Server: Stores the received user information in the database, generates a new user ID, and sends it back.

[2456] Input: User information received from the terminal.

[2457] Output: Information stored in the database and a new user ID.

[2458] Confirming needs and challenges

[2459] Step 1:

[2460] Terminal: After the user logs in, a survey screen about DX (Digital Transformation) will be displayed. Questions will include "Current state of digitalization" and "Issues you want to solve."

[2461] Input: User login information.

[2462] Output: The survey screen is displayed.

[2463] Step 2:

[2464] User: Answer the questionnaire, enter specific needs and challenges in the text box, and press the "Submit" button.

[2465] Input: Survey responses.

[2466] Output: The answer is entered into the terminal.

[2467] Step 3:

[2468] Terminal: Sends the response content to the server.

[2469] Input: Survey responses.

[2470] Output: The response is sent to the server.

[2471] Step 4:

[2472] Server: Receives the response content, analyzes it, and prepares the data necessary for the generative artificial intelligence to generate proposals.

[2473] Input: Answer content.

[2474] Output: Data is prepared for input into a generative artificial intelligence.

[2475] Proposal generation using generative artificial intelligence and an emotion engine.

[2476] Step 1:

[2477] Server: Inputs data into a generative artificial intelligence system based on survey results and user input data. The AI ​​then sets specific tasks (e.g., "Optimize inventory management," "Analyze customer data").

[2478] Input: Survey results and user input data.

[2479] Output: Data input to a generative artificial intelligence.

[2480] Step 2:

[2481] Server: The emotion engine analyzes emotional information obtained from user input and actions, and provides that information to the generative artificial intelligence.

[2482] Input: User sentiment information.

[2483] Output: Emotional information provided to the generative artificial intelligence.

[2484] Step 3:

[2485] Server: Generative artificial intelligence generates suggestions while considering the user's emotional information. For example, "Implementation of an inventory management system" or "Suggestion of a customer data analysis tool."

[2486] Input: Survey results, user sentiment information.

[2487] Output: Generated proposals.

[2488] Step 4:

[2489] Server: Sends the generated proposal to the terminal.

[2490] Input: Generated suggestions.

[2491] Output: Suggestions sent to the terminal.

[2492] Display of proposals and feedback

[2493] Step 1:

[2494] Terminal: Displays generated proposals to the user. The proposals include detailed information such as "Overview of the inventory management system" and "Benefits of implementation."

[2495] Input: Suggestions sent from the server.

[2496] Output: The suggested content is displayed to the user.

[2497] Step 2:

[2498] User: Review the proposal and check the feedback. Enter comments such as "This looks good" or "I'd like more specific information," and submit.

[2499] Input: User feedback.

[2500] Output: Feedback entered into the terminal.

[2501] Step 3:

[2502] Terminal: Sends feedback to the server.

[2503] Input: Feedback content.

[2504] Output: Feedback sent to the server.

[2505] Request for Proposal and Follow-up

[2506] Step 1:

[2507] User: If you are satisfied with the proposal, press the "Request Proposal" button.

[2508] Input: User action (pressing the "Request Proposal" button).

[2509] Output: The Request for Proposal screen is displayed.

[2510] Step 2:

[2511] Terminal: A form is displayed for the user to enter details of the "R...

Claims

1. A system for companies that are lagging behind in digitalization and digital transformation to receive proposals for digitalization and digital transformation for their management teams. A means for users to input company information, A means for users to input their needs and challenges regarding digitalization and digital transformation, A means having a generative artificial intelligence that analyzes the aforementioned needs and challenges and generates proposals based thereon, A means for displaying to the user the proposals generated by the aforementioned generative artificial intelligence, A means for the user to input feedback based on the above proposal, A means for users to request proposals they like, A means of forwarding the request for proposal to the business operator and managing the progress of the follow-up, A system that includes this.

2. The system according to claim 1, further comprising means for a user to respond to a questionnaire regarding digitalization and digital transformation.

3. The system according to claim 1, wherein the generative artificial intelligence has an algorithm for identifying the optimal solution for digitalization and digital transformation.

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