System

Abstract

To provide a system for enabling a user to accurately analyze a problem of its own company, find an optimum solution, and support creation of a new business chance by cooperation between different companies.SOLUTION: Means for receiving an input of information from a user, means for storing the input information in a database, means for using an artificial intelligence module that performs initial analysis based on the stored information, means for providing an initial analysis result to the user, means for collecting detailed information based on the initial analysis result and using an artificial intelligence module that performs reanalysis, and means for generating an individual proposal based on the reanalysis result; The system includes a means for providing a service to a user, a means for using an artificial intelligence module to analyze the overall needs and tendency of the user, a means for providing an optimum service or solution based on the analysis result, and a means for searching for other users having similar problems or needs and matching the users with each other.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In recent years, there has been a demand for greater efficiency in corporate activities and the creation of new business ideas, but there is a lack of appropriate support systems to achieve this. Small and medium-sized enterprises and startups, in particular, have limited specialized consulting resources, making it difficult to accurately analyze their own issues and find optimal solutions. There is also a problem of few opportunities for different companies to collaborate and create new business opportunities. To address these issues, this invention provides a comprehensive consulting system using AI, with the aim of supporting the identification and resolution of individual issues and collaboration between companies. [Means for solving the problem]

[0005] The present invention solves the above problems by using the following means.

[0006] By providing a system including means for accepting information input from a user, means for saving the input information in a database, means for using an artificial intelligence module to perform an initial analysis based on the saved information, means for providing the results of the initial analysis to the user, means for using an artificial intelligence module to collect detailed information based on the results of the initial analysis and perform a re-analysis, means for generating individual proposals based on the results of the re-analysis and providing them to the user, means for using the artificial intelligence module to analyze the user's overall needs and trends, means for providing optimal services and solutions based on the results of the analysis, and means for searching for other users with similar issues and needs and matching users together, the system enables users to accurately analyze their own issues and find optimal solutions, and also supports different companies collaborating to create new business opportunities.

[0007] "User" refers to a company or individual who uses the system.

[0008] "Means for accepting information input" refers to the interface and functions for collecting data from users (company information, business details, issues, etc.).

[0009] "Means for storing in a database" refers to a storage system for systematically storing and managing collected user information.

[0010] "Initial analysis" refers to the process of analyzing the current situation and conducting a basic assessment of issues based on the input user information.

[0011] "Artificial intelligence module" refers to the part of the software that uses machine learning and data analysis techniques to analyze information and generate suggestions.

[0012] "Initial analysis results" refer to the results of the analysis of the user's current situation and the basic issue assessment obtained through the initial analysis.

[0013] "Means for collecting detailed information" refers to a function for collecting further data from users regarding additional specific information and detailed issues based on the results of the initial analysis.

[0014] "Reanalysis" refers to the process of conducting deeper analysis and generating specific recommendations based on the detailed information collected.

[0015] "Individual proposals" refer to recommendations that include optimal solutions or measures to address the user's specific needs or challenges.

[0016] "Means for analyzing needs and trends" refers to AI analysis functions that use data from all users to identify common needs and current trends.

[0017] "Means of providing optimal services and solutions" refers to the function of recommending the most appropriate products and services based on the user's needs and analysis results.

[0018] "Means of matching users" refers to the function of finding multiple users with similar challenges and needs and providing connections between those users to create business opportunities. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] 1. User registration and information entry

[0041] The user accesses the system and registers an account. An interface for entering basic company information, job description, and specific tasks is displayed on the terminal. The user then enters the necessary information into the system and submits it.

[0042] The server receives the information entered by the user and stores it in a database. The stored information is used for analysis, so accurate and detailed information is required. After saving, the server sends a verification email to the user and activates the account.

[0043] 2. Initial analysis using AI

[0044] The server sends the saved user information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module compares the information with past databases and makes an initial assessment of the user's current situation and challenges.

[0045] The initial evaluation results are sent to the user's device and displayed on a dashboard. The user can review the results and request further consultation if necessary.

[0046] 3. Individual consulting proposals

[0047] When a user requests detailed consulting, the server provides an interface to initiate the collection of additional details, allowing the user to enter and submit more specific issues and requests.

[0048] The server then uses the details provided by the user to perform further analysis using the AI ​​module, which generates more specific solutions and suggestions and sends them back to the server in text format.

[0049] The generated suggestions are displayed on the user's dashboard, and the server provides detailed explanations and links to documentation for these suggestions, allowing the user to review the suggestions and receive guidance on actionable measures.

[0050] 4. Needs and Trends Analysis

[0051] The server then passes the information collected from users and the proposed data back to the AI ​​module, which analyzes the overall needs and trends. The AI ​​module then analyzes the large amount of data to extract current market trends and common user needs.

[0052] The analysis results are used to provide services and solutions that best suit the user's needs. Based on these results, the server recommends services and products that are suitable for the user and displays them on the dashboard.

[0053] 5. Matching users

[0054] The server searches for other users with similar challenges and needs and matches them with each other, potentially leading to joint projects and partnerships.

[0055] The server notifies users of the matching results and provides contact methods and partnership proposals to create business opportunities. Users can contact other companies and consider joint projects.

[0056] Specific examples

[0057] Example 1: Improving manufacturing efficiency

[0058] User A (a small to medium-sized manufacturing company) inputs the issue of improving the efficiency of its manufacturing process. The server sends this information to the AI ​​module, which performs an initial analysis. The AI ​​module then proposes measures to automate the production line and introduce an inventory management system, which the server provides to User A. User A then creates a specific implementation plan based on these proposals.

[0059] Example 2: Strengthening your marketing strategy

[0060] User B (an IT startup) is looking for a new marketing strategy. The server collects detailed information and reanalyzes it using the AI ​​module. The AI ​​module then suggests ways to expand the target market and strengthen the social media campaign, which the server then provides to User B. User B then takes specific steps to implement the proposed strategy.

[0061] Example 3: New business through user matching

[0062] User C (a logistics company) and User D (an e-commerce company) are both seeking to reduce logistics costs. Based on this information, the server matches the two parties and offers a joint delivery service proposal. User C and User D consider forming a partnership and actually start a joint project.

[0063] This system allows users to solve their own problems and discover new business opportunities. The entire system process is user-friendly and supports the growth and efficiency of companies.

[0064] The processing flow will be explained below.

[0065] Step 1:

[0066] A user accesses the consulting service system and enters detailed information such as company information, business details, and specific issues on the registration screen displayed on the terminal.

[0067] Step 2:

[0068] The server receives the information entered by the user and stores it in a database, after which the server sends a verification email to the user and activates the account.

[0069] Step 3:

[0070] The server sends the saved user information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module compares the information with a past database and makes an initial assessment of the user's current situation and challenges.

[0071] Step 4:

[0072] The AI ​​module generates initial analysis results and sends them back to the server, which receives them and displays them on the user's dashboard. The user can then view the initial analysis results.

[0073] Step 5:

[0074] When a user requests detailed consulting, the server provides the user with an interface for inputting detailed information, and the user inputs and submits additional specific issues and requests.

[0075] Step 6:

[0076] The server then uses the detailed information collected from the user to perform further analysis using the AI ​​module, which then generates specific solutions and suggestions and sends them back to the server.

[0077] Step 7:

[0078] The server displays the generated proposals on the user's dashboard, where the user can review the proposals and receive guidance on specific measures.

[0079] Step 8:

[0080] The server then passes the collected information and proposal data back to the AI ​​module, which analyzes overall needs and trends and extracts market trends and common user needs.

[0081] Step 9:

[0082] The server then recommends optimal services and solutions to the user based on the analysis results, and displays the recommendations on the user's dashboard with detailed explanations.

[0083] Step 10:

[0084] The server searches for other users with similar challenges and needs, matches users with each other, notifies users of the matching results, and provides contact methods and collaboration proposals to create business opportunities.

[0085] Step 11:

[0086] Users can contact other companies to discuss details of joint projects and partnerships, and the server provides functionality to support the necessary information sharing and exchange of materials.

[0087] This allows users to efficiently solve problems and explore new business opportunities.

[0088] Example 1

[0089] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0090] In today's business environment, companies need to respond quickly to diversifying challenges and needs. However, achieving this requires accurate information gathering, appropriate analysis, and specific proposals. Traditional methods make these processes time-consuming and labor-intensive, making it difficult to carry them out efficiently and effectively. Furthermore, it is not easy to find suitable partners for inter-company collaboration and matching. Therefore, an efficient system is needed to help companies solve their own challenges and discover new business opportunities.

[0091] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0092] In this invention, the server includes means for accepting information input from a user, means for saving the input information in a database, means for using an artificial intelligence module to perform an initial analysis based on the saved information, means for providing the initial analysis results to the user, means for using an artificial intelligence module to collect detailed information based on the initial analysis results and perform a re-analysis, means for generating individual proposals based on the re-analysis results and providing them to the user, means for using the artificial intelligence module to analyze the user's overall needs and trends, means for providing optimal services and solutions based on the analysis results, means for searching for other users who have similar issues or needs and matching users with each other, means for sending a verification email to the user and activating the account, means for receiving the user's detailed information, converting it into an appropriate format, and sending it to the artificial intelligence module, means for displaying the results of the re-analysis on the user's dashboard and providing related materials and links, and means for generating information recommended to the user based on the analysis results and displaying it on the dashboard.

[0093] This allows companies to quickly and accurately identify problems and receive solutions based on concrete proposals, while also promoting collaboration between companies and creating new business opportunities.

[0094] "User" refers to the entity that uses the system to input information and receive analysis results and suggestions.

[0095] "Means for accepting input of information" refers to the function of providing an interface that allows users to access the system and input company information and tasks.

[0096] "Database" refers to a storage or management system for structuring and storing received information.

[0097] An "artificial intelligence module" refers to a program with machine learning and data analysis capabilities that analyzes stored information and generates results.

[0098] "Initial analysis" refers to the initial information analysis process based on the basic information and issues provided by the user.

[0099] "Reanalysis" refers to the process of reanalyzing information based on more detailed information.

[0100] "Individual proposals" refer to specific solutions or action plans generated to address the user's specific challenges or requests.

[0101] "Needs and Trend Analysis" refers to the analytical process used to extract common issues and market trends based on data collected from users across the board.

[0102] "Verification Email" means the confirmation email sent to the email address provided by the User to activate the Account.

[0103] "Dashboard" refers to the web application interface that allows users to visually view analysis results and recommendations.

[0104] "Matching" refers to the process of searching for other users with similar challenges and needs and connecting suitable users with each other.

[0105] The present invention is a system for users to solve problems and discover new business opportunities. This system focuses on a series of processes in which users input information and receive analysis results and proposals.

[0106] User registration and information entry

[0107] The user accesses the system's registration page using a web browser on their device. The user enters the required information through an interface that allows them to enter company information, job description, and specific tasks, and then clicks the "Submit" button. The server receives this information as an HTTP request and stores it in a MySQL (registered trademark) or PostgreSQL database. Once the information is saved, the server uses an email sending service such as SendGrid to send a verification email to the user. The user clicks the link in the email to activate their account.

[0108] Initial analysis by AI

[0109] The server sends the saved user information to an AI analysis module such as "TENSORFLOW (registered trademark)" or "PyTorch" in an appropriate format (JSON or CSV). The AI ​​module analyzes this information and compares it with past data to make an initial assessment of the user's current situation and challenges. Once the analysis is complete, the AI ​​module returns the results to the server, which displays them on the user's dashboard (built with React or Angular). The user can check the initial assessment results on the dashboard using their device.

[0110] Individual consulting proposals

[0111] If the user requests detailed consulting, the server provides the user with an interface (such as an HTML form) to collect additional details. The user enters the details and clicks the "Submit" button again. The server receives this information and sends it back to the TensorFlow or PyTorch AI module in the appropriate format. The AI ​​module reanalyzes it and proposes a specific solution. The server displays this proposal on the user's dashboard, providing related materials and links. The user can then plan specific actions based on this.

[0112] Needs and trends analysis

[0113] The server performs large-scale data analysis on the information and proposal data collected from all users using big data processing platforms such as Hadoop and Spark. The AI ​​module uses this data to extract market trends and common user needs. The analysis results are returned to the server, which then uses this information to recommend optimal services and solutions to the user. This information is displayed on the user's dashboard.

[0114] Matching users

[0115] The server searches a database for other users with similar challenges and needs and matches them with suitable users. The matching results are provided to users via a dashboard and email notifications. Users can contact other companies based on the displayed information and consider joint projects. The server provides contact methods and partnership proposals, helping to create business opportunities.

[0116] Specific examples

[0117] (Example 1: Improving efficiency in manufacturing)

[0118] User A inputs the issue of improving the efficiency of the manufacturing process. The server sends this information to the AI ​​module, which performs an initial analysis. The AI ​​module then proposes measures such as automating the production line and introducing an inventory management system, which the server then provides to User A.

[0119] (Example 2: Strengthening marketing strategies)

[0120] User B wants to propose a new marketing strategy. The server collects detailed information and reanalyzes it with the AI ​​module. The AI ​​module then suggests expanding the target market or strengthening the social media campaign, which the server then provides to User B.

[0121] (Example 3: New business through user matching)

[0122] User C (a logistics company) and User D (an e-commerce company) are looking to reduce logistics costs. The server matches the two parties and offers a joint delivery service. User C and User D consider partnering and start a joint project.

[0123] Prompt Sentence Examples

[0124] "Please give us some specific suggestions on how to improve the efficiency of the manufacturing process."

[0125] "We're looking for suggestions for new marketing strategies."

[0126] "Please tell us some specific solutions to reduce logistics costs."

[0127] This system enables companies to quickly identify problems and find solutions, thereby improving operational efficiency and creating new business opportunities.

[0128] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0129] Step 1:

[0130] The user accesses the account registration page. Using a terminal, the user enters the specified URL into a web browser and arrives at the system's registration page. This page displays an interface for entering the required information. The input information includes company information, job description, specific challenges, etc.

[0131] Step 2:

[0132] The user enters information and submits it. The user enters the company name, business details, and the problem they want to solve from the terminal and clicks the "Submit" button. The entered data is sent as an HTTP request to the server.

[0133] Step 3:

[0134] The server receives the information and stores it in a database. The server analyzes the user's input information received as an HTTP request and stores it in a database (for example, MySQL or PostgreSQL). The stored data includes the user's company information, business details, and the problem they want to solve. The input is the information the user enters from their terminal, and the output is structured data stored in the database.

[0135] Step 4:

[0136] The server sends a verification email and the user activates the account. The server uses an email sending service (e.g. SendGrid) to send a verification email to the user's email address. The user checks their mailbox and clicks the verification link contained in the email to activate their account. The input is the user's email address stored by the server, and the output is the status of successful authentication.

[0137] Step 5:

[0138] The server sends user information to the AI ​​analysis module. The server converts the user information stored in the database into an appropriate format (e.g., JSON, CSV) and sends it to the AI ​​analysis module (e.g., TensorFlow or PyTorch) via an HTTP API. The input is the user information retrieved from the database, and the output is the completion status of transmission to the AI ​​analysis module.

[0139] Step 6:

[0140] The AI ​​module analyzes the information and generates results. The AI ​​module analyzes the received user information and compares it with past data to make an initial assessment of the user's current situation and issues. The input is the user information sent from the server, and the output is the analysis results.

[0141] Step 7:

[0142] The server displays the initial evaluation results on the user's dashboard. The server displays the initial evaluation results received from the AI ​​module on the user's dashboard (built with React or Angular). The user uses a terminal to check the initial evaluation results on the dashboard. The input is the initial evaluation result from the AI ​​module, and the output is the evaluation result displayed on the user's dashboard.

[0143] Step 8:

[0144] The user requests detailed consulting. The user clicks the "Request detailed consulting" button on the dashboard and proceeds to the interface for collecting additional information. The input is the user's request action, and the output is the display of the interface for entering detailed information.

[0145] Step 9:

[0146] The server provides an interface for the user to gather additional details. The server displays an interface (HTML form) to the user to gather additional details, including the specific problem in the business flow and the type of solution desired. The input is the server's interface display, and the output is preparation to accept user input.

[0147] Step 10:

[0148] User enters details and submits: The user enters details into a form and clicks the "Submit" button. The input is the details entered by the user at the terminal and the output is an HTTP request to the server.

[0149] Step 11:

[0150] The server uses the detailed information to perform re-analysis using the AI ​​module. The server converts the received detailed information into an appropriate format and sends it back to the AI ​​module. The AI ​​module then performs re-analysis and generates specific suggestions. The input is the detailed information sent by the user, and the output is the analysis result returned by the AI ​​module.

[0151] Step 12:

[0152] The server displays the generated suggestions on the user's dashboard. The server displays the suggestions received from the AI ​​module on the user's dashboard, and also provides related materials and links. The user uses their device to check the suggestions on the dashboard. The input is the analysis result of the AI ​​module, and the output is the suggestions displayed on the user's dashboard.

[0153] Step 13:

[0154] The server analyzes needs and trends based on the collected information and proposal data. The server analyzes all user data using Hadoop or Spark to extract market trends and common needs. The input is collected data from all users, and the output is the market trends and user needs analysis results.

[0155] Step 14:

[0156] The server provides the user with the optimal services and solutions based on the analysis results.The server then displays the optimal products and services on the user's dashboard based on the analysis results.The input is the analysis results, and the output is the recommended services and products that are displayed to the user.

[0157] Step 15:

[0158] The server searches for other users with similar issues and needs and performs matching. The server searches for similar users from the database and notifies the user of the matching results. The input is the user's issue information, and the output is the matching results for similar users.

[0159] Step 16:

[0160] Users contact other companies to consider joint projects. The server provides contact methods and collaboration proposals to help start joint projects. The input is the user's contact action, and the output is the provision of contact methods and collaboration proposals.

[0161] (Application example 1)

[0162] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0163] Modern factory operations require efficient management and optimization of production processes. However, manual information entry and management is time-consuming, making it difficult to make efficient decisions. It is also difficult to select appropriate solutions and services and to build a collaborative system between users. In addition, the lack of real-time feedback often delays productivity improvements.

[0164] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0165] In this invention, the server includes means for accepting information input from a user, means for storing the input information in a database, means for using an artificial intelligence module to perform an initial analysis based on the stored information, means for providing the results of the initial analysis to the user, means for using an artificial intelligence module to collect detailed information based on the results of the initial analysis and perform a reanalysis, means for generating individual proposals based on the results of the reanalysis and providing them to the user, means for using the artificial intelligence module to analyze the overall needs and trends of the user, means for providing optimal services and solutions based on the results of the analysis, means for searching for other users who have similar issues or needs and matching users with each other, means for providing an interface for managing information from multiple users in a unified manner, means for managing and optimizing automated factory equipment based on information input by the user, and means for providing real-time feedback to users to improve productivity. This enables efficient management and optimization of production processes, rapid decision-making, building a cooperative system among users, and improving productivity through real-time feedback.

[0166] "User" refers to an individual company or individual who uses the system.

[0167] "Means for accepting information input" refers to an interface that allows a user to input information into the system.

[0168] "Means for storing in a database" refers to a database system for storing and managing input information for a long period of time.

[0169] "Artificial intelligence module that performs initial analysis" refers to the AI ​​analysis engine that performs initial data analysis.

[0170] "Means for providing initial analysis results to a user" refers to means for displaying the analysis results on a user's dashboard or interface.

[0171] "Artificial intelligence module for reanalysis" refers to an AI analysis engine that reanalyzes data based on detailed information.

[0172] "Means for generating individual proposals and providing them to the user" refers to the part of the system that generates specific proposals based on the analysis results and notifies the user of them.

[0173] "Artificial intelligence module for analyzing overall needs and trends" refers to an AI engine for analyzing overall user data needs and market trends.

[0174] "Means for providing optimal services and solutions" refers to the part of the system that suggests the most suitable services and products to users based on the analysis results.

[0175] "Means for searching for other users with similar challenges and needs and matching users together" refers to the part of the system that connects users with common needs and challenges, providing opportunities for information sharing and collaborative projects.

[0176] "Interface for managing information from multiple users at once" refers to an interface for managing and displaying information obtained from a large number of users in a unified manner.

[0177] "Means for managing and optimizing automated factory equipment" refers to the system part for automating equipment within a factory and optimizing its operation.

[0178] "Means for providing real-time feedback" refers to the part of the system that immediately provides the user with feedback on analysis results and recommended actions.

[0179] MODE FOR CARRYING OUT THE INVENTION

[0180] This invention is a system that aims to improve the efficiency and optimization of production processes within factories. Specifically, it is a system that uses artificial intelligence (AI) to analyze information entered by users and propose appropriate solutions. This system consists of the following main components:

[0181] 1. User registration and information entry

[0182] First, the user accesses the system and registers an account. After registration, an interface is provided for entering basic factory information, current work content, and specific tasks, and the user then enters and submits the information required for the system. The entered information is saved in a database (e.g., MySQL) by the server. After saving, the server sends the user an authentication email and activates the account.

[0183] 2. Initial analysis using AI

[0184] The server sends the saved user information to an AI analysis module (e.g., TensorFlow, PyTorch) and begins initial analysis. The AI ​​module compares the information with past data and performs an initial assessment of the user's current situation and issues. The results of the initial assessment are notified to the user's device and displayed on a dashboard.

[0185] 3. Individual consulting proposals

[0186] When a user requests a detailed consultation, the server provides an interface to begin collecting additional details. The user then enters and submits a more specific challenge or request. The server then performs a re-analysis using the AI ​​module based on the details provided by the user. The generated proposals are displayed on the user's dashboard, and the server provides detailed explanations and links to resources related to these proposals.

[0187] 4. Factory equipment management and optimization

[0188] Based on the information entered by the user, the server manages and optimizes automated factory equipment, identifying bottlenecks on production lines within the factory and suggesting the introduction of automation tools or redistribution of tasks, thereby improving factory efficiency.

[0189] 5. Providing real-time feedback

[0190] Furthermore, the server provides users with real-time feedback to improve productivity. For example, if a decline in efficiency in a specific process is detected, the server immediately notifies the user of the problem and suggests improvement measures. The server also monitors the effectiveness of the implemented improvement measures in real time and provides the results as feedback to the user.

[0191] 6. Needs and Trend Analysis

[0192] The server then passes the information collected from users and the proposed data back to the AI ​​analysis module, which analyzes overall needs and trends. The AI ​​module analyzes large amounts of data to extract current market trends and common user needs. The analysis results are used to provide services and solutions that best suit the user's needs.

[0193] 7. User Matching

[0194] The server searches for other users with similar challenges and needs and matches them with each other, leading to the possibility of joint projects and partnerships. The server notifies users of the results of the matches and provides contact methods and partnership proposals to create business opportunities.

[0195] Specific examples

[0196] Example 1: Streamlining the manufacturing process

[0197] A factory inputs the issue of improving the efficiency of its production line into the system. The server sends this information to the AI ​​analysis module, which performs an initial analysis. As a result of the analysis, it identifies bottlenecks in specific processes and suggests ways to resolve them.

[0198] Example prompt sentence:

[0199] User: We are looking to improve the efficiency of our manufacturing line. Please suggest us what the bottlenecks are in our current production line and how to resolve them.

[0200] AI analysis:

[0201] We analyzed the current production line data and found that the bottleneck mainly occurs between process A and process B. Please try the following improvement suggestions.

[0202] 1. Introduction of automation tools for process A

[0203] 2. Introduction of task distribution and parallel processing in Process B

[0204] 3. Optimizing the overall inventory management system

[0205] By using the system in this way, each user can solve their own problems quickly and efficiently.

[0206] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0207] Application example processing steps

[0208] (Processing Steps)

[0209] Step 1:

[0210] Users access the system using a terminal and register an account. They then enter basic factory information, business operations, and specific tasks through an interface. The input data is sent to the server in JSON format.

[0211] Input: Basic information about the factory, business operations, specific issues

[0212] Output: User information data in JSON format

[0213] Step 2:

[0214] The server stores the received user information in a database, which is managed in a MySQL database and used for future analysis.

[0215] Input: User information data in JSON format

[0216] Output: User information stored in the database

[0217] Step 3:

[0218] The server sends the saved user information to an AI analysis module (TensorFlow, PyTorch) to begin initial analysis. The AI ​​module compares the information with past databases and makes an initial assessment of the user's current situation and challenges.

[0219] Input: User information data, historical database

[0220] Output: Initial analysis results

[0221] Step 4:

[0222] The server notifies the user of the analysis results and displays them on the dashboard, allowing the user to check the initial analysis results.

[0223] Input: Initial analysis results

[0224] Output: Analysis results displayed on a dashboard

[0225] Step 5:

[0226] When a user requests a detailed analysis, the server provides an interface to start collecting additional information. The user can then enter more specific issues or requests and submit them. The submitted data is then sent back to the server in JSON format.

[0227] Input: Additional details, specific issues or requests

[0228] Output: Additional information data in JSON format

[0229] Step 6:

[0230] The server then uses the detailed information provided by the user to perform further analysis using the AI ​​analysis module, which then generates more specific solutions and suggestions and sends them back to the server in text format.

[0231] Input: Additional information data

[0232] Output: Reanalysis results, specific solution proposals

[0233] Step 7:

[0234] The server displays the generated proposals on the user's dashboard, providing detailed explanations and links to related materials. The user can review the proposals and select actionable measures.

[0235] Input: Reanalysis results, specific solution proposals

[0236] Output: Detailed proposal information displayed in a dashboard

[0237] Step 8:

[0238] The server then passes the collected user data and proposal data back to the AI ​​analysis module to analyze overall needs and trends. The AI ​​module then extracts market trends and common needs and sends the results back to the server.

[0239] Input: User data, Proposal data

[0240] Output: Needs and trends analysis

[0241] Step 9:

[0242] Based on the analysis results, the server proposes optimal services and solutions to users, and displays related business solutions and new products on a dashboard.

[0243] Input: Needs and trends analysis results

[0244] Output: Recommended services and solutions

[0245] Step 10:

[0246] The server searches for other users with similar challenges and needs, matches them, notifies users of the matching results, and provides suggestions for collaborative projects.

[0247] Input: User data, analysis results

[0248] Output: Matching results, joint project proposals

[0249] Step 11:

[0250] Based on the information entered by the user, the server manages and optimizes automated factory equipment, identifying bottlenecks on production lines within the factory, deploying automation tools, redistributing tasks, and monitoring data in real time.

[0251] Input: Factory information, analysis results

[0252] Output: Optimized factory equipment management data

[0253] Step 12:

[0254] The server provides users with real-time feedback to improve productivity. For example, if a decrease in efficiency in a particular process is detected, the server immediately notifies the user of the problem and suggests a remedial measure.

[0255] Input: Real-time monitoring data

[0256] Output: Notification and suggestions for improvement

[0257] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0258] 1. User registration and information entry

[0259] A user accesses the system and registers an account. On the registration screen displayed on the terminal, the user enters basic company information, job description, and specific tasks. The emotion engine also monitors the user's input and actions during registration to recognize the user's emotional state. This information is also saved as data.

[0260] The server receives the information entered by the user and the emotional information recognized by the emotion engine and stores it in a database. The stored information is used for analysis, so accurate and detailed information is required. After saving, the server sends a verification email to the user and activates the account.

[0261] 2. Initial analysis using AI

[0262] The server sends the saved user information and emotional information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module takes into account the past database and the user's current emotional information to make an initial assessment of the user's current situation and challenges.

[0263] The initial evaluation results are sent to the user's device and displayed on a dashboard. The user can review the results and request further consultation if necessary.

[0264] 3. Individual consulting proposals

[0265] If the user requests detailed consultation, the server provides an interface for the user to enter detailed information. The user enters and submits additional specific issues or requests. The emotion engine continues to recognize the user's emotional state at this point.

[0266] The server then re-analyzes the AI ​​module based on the detailed information and emotional information collected from the user, and the AI ​​module takes the user's emotional state into account when generating specific solutions and suggestions.

[0267] The generated suggestions are displayed on the user's dashboard, and the server provides detailed explanations and links to resources about these suggestions. Depending on the user's emotional state, the suggestions may be adjusted or followed up. The user can review the suggestions and receive guidance on actionable measures.

[0268] 4. Needs and Trends Analysis

[0269] The server then passes the collected information and suggestion data, as well as emotional information, back to the AI ​​module, which analyzes the overall needs and trends. The AI ​​module then analyzes the large amount of data to extract current market trends, common user needs, and users' emotional responses.

[0270] The analysis results are used to provide services and solutions that best suit the user's needs. Based on these results, the server recommends services and products that are suitable for the user and displays them on a dashboard. Recommendations selected based on emotional information can increase user satisfaction.

[0271] 5. Matching users

[0272] The server searches for other users with similar issues and needs and matches them with each other. The emotion engine also takes the user's emotional state into account when matching, suggesting the best partner for building a better relationship.

[0273] The server notifies users of the matching results and provides contact and partnership suggestions to create business opportunities. Users can contact other companies and consider joint projects. Feedback from the emotion engine promotes better communication, making collaborations smoother.

[0274] Specific examples

[0275] Example 1: Improving manufacturing efficiency

[0276] User A (a small to medium-sized manufacturing company) inputs the issue of improving the efficiency of the manufacturing process. The emotion engine detects User A's stress level at the time of input and sends it to the AI ​​module. The server performs an initial analysis based on this information and proposes automating the production line and introducing an inventory management system. When explaining the proposal, the server uses language that reduces User A's stress. User A accepts the proposal with peace of mind and makes a specific implementation plan.

[0277] Example 2: Strengthening your marketing strategy

[0278] User B (an IT startup) is looking for a new marketing strategy. By providing detailed information along with emotional information, the server makes suggestions with the appropriate tone and content. The AI ​​module suggests expanding the target market or strengthening the social media campaign, and the server communicates this to User B, taking the emotional information into account. User B then takes concrete steps to implement the suggestions, improving the success rate.

[0279] Example 3: New business through user matching

[0280] User C (a logistics company) and User D (an e-commerce company) are both seeking to reduce logistics costs. The emotion engine monitors the emotional state of both parties when they use the system and matches them at the optimal time. Based on this information, the server provides proposals for joint delivery services. With the support of the emotion engine, User C and User D communicate smoothly and build a mutually satisfying cooperative relationship.

[0281] This system allows users to receive services that take their emotional state into consideration, enabling them to solve problems and explore new business opportunities efficiently. The entire system process is user-friendly, supporting the growth and efficiency of companies and increasing user satisfaction.

[0282] The processing flow will be explained below.

[0283] Step 1:

[0284] A user accesses the system and registers an account. On the registration screen displayed on the terminal, the user enters company information, job details, and specific tasks. The emotion engine monitors the user's input and operations and recognizes their emotional state.

[0285] Step 2:

[0286] The server receives the information entered by the user and the emotion information recognized by the emotion engine and stores them in a database. After saving, the server sends a verification email to the user to activate the account. The emotion information is also stored.

[0287] Step 3:

[0288] The server sends the saved user information and emotional information to the AI ​​analysis module, which then compares the user's emotional information with the past database and makes an initial assessment of the user's current situation and challenges.

[0289] Step 4:

[0290] The AI ​​module generates initial analysis results and sends them back to the server, which receives them and displays them on the user's dashboard, where the user can view them.

[0291] Step 5:

[0292] If the user requests detailed consultation, the server provides an interface for the user to enter detailed information. The user enters and submits additional specific issues or requests. The emotion engine continues to recognize the user's emotional state at this point.

[0293] Step 6:

[0294] The server then uses the AI ​​module to reanalyze the details and emotional information collected from the user. The AI ​​module then generates specific solutions and proposals and sends them back to the server. The proposals may be adjusted based on the emotional information.

[0295] Step 7:

[0296] The server displays the generated suggestions on the user's dashboard, providing detailed explanations and links to resources. The suggestions may be adjusted based on the user's emotional state. The user can review the suggestions and take action accordingly.

[0297] Step 8:

[0298] The server then passes the collected information, suggestion data, and emotional information from users back to the AI ​​module to analyze overall needs and trends. The AI ​​module then analyzes market trends, common user needs, and emotional responses.

[0299] Step 9:

[0300] The server then recommends optimal services and solutions to users based on the analysis results. The recommendations are adjusted taking into account the user's emotional information and displayed on the dashboard, thereby increasing user satisfaction.

[0301] Step 10:

[0302] The server searches for other users with similar issues and needs and matches them with each other. The emotion engine also takes the user's emotional state into account when matching and suggests the most suitable partner.

[0303] Step 11:

[0304] The server notifies users of the matching results and provides contact methods and partnership proposals to create business opportunities. Users can contact other companies and discuss details of joint projects. The server provides functions to support the necessary information sharing and document exchange.

[0305] This allows the entire system to provide flexible services that reflect the user's emotional state, supporting the growth and efficiency of companies.

[0306] Example 2

[0307] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0308] Conventional systems have difficulty providing optimal proposals and solutions that take into account the user's specific issues and emotional state. Furthermore, when matching users, the system does not consider their emotional state when selecting the optimal partner, which can lead to problems in communication and building cooperative relationships between users. This results in lower user satisfaction and makes it difficult to effectively solve problems and create business opportunities.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0310] In this invention, the server includes a means for accepting information input from a user, a means for using an artificial intelligence module that performs an initial analysis based on the stored information and emotional information, and a means for using an artificial intelligence module that collects detailed information while recognizing the user's emotional state and performs reanalysis. This enables highly accurate suggestions that take the user's emotional state into consideration. The server also includes a means for searching for other users with similar issues or needs and matching users while taking their emotional state into consideration, enabling smooth communication between users and the establishment of effective cooperative relationships.

[0311] A "user" is someone who accesses the system, inputs information, or uses services.

[0312] The "means for accepting information input" is an interface that accepts input of company information, business details, tasks, etc. from the user.

[0313] "Storage means" is a function that records input information and recognized emotional information in a database.

[0314] "Initial analysis" is the process by which the artificial intelligence module evaluates the user's current situation and challenges based on stored information and emotional information.

[0315] The "artificial intelligence module" is a module that analyzes information collected from users and makes proposals and evaluations for solving problems.

[0316] "Emotional state" refers to the mental and emotional state of a user when entering information or using a system.

[0317] The "emotion engine" is an engine that monitors the user's input and actions, and recognizes and evaluates their emotional state.

[0318] "Detailed information" is information about specific issues or requests that are additionally entered by the user.

[0319] "Reanalysis" is the process in which the artificial intelligence module analyzes again based on detailed information and emotional information after the initial analysis.

[0320] "Individual proposals" are problem-solving proposals or solutions specific to the user that are generated based on the results of the reanalysis.

[0321] "Needs and Trends Analysis" is the process of using all the information collected from users to extract common needs and market trends.

[0322] "Means for providing services and solutions" refers to an interface that suggests optimal services and products to users based on the results of analysis.

[0323] "Matching" is the process of searching for users with similar challenges and needs and selecting the most suitable partner, taking into account their emotional state.

[0324] "Business opportunities" are opportunities for new collaborations and projects that arise from matching users together.

[0325] The "means for providing contact methods and business partnership proposals" is a function that supports users in contacting each other and considering business partnerships.

[0326] The system of the present invention accepts information input from users and analyzes and proposes based on that information. A distinctive feature of this system is that it takes into account the emotional state of the user to make optimal proposals and match users with each other.

[0327] 1. User registration and information entry

[0328] First, users access the system and register an account. A registration screen is displayed on the terminal, allowing them to enter basic company information, job duties, and specific tasks. Specifically, information such as the company name, address, and name of the person in charge is entered. The emotion engine also monitors the user's behavior (e.g., typing speed, mouse movement) while entering data and recognizes their emotional state. All of this information is stored in a database. The server then sends the user a verification email and activates the account.

[0329] 2. Initial analysis using AI

[0330] The server sends the user information and emotional information stored in the database to the AI ​​analysis module, which begins the initial analysis. This AI module takes into account the past database and the user's current emotional information to make an initial assessment of the current situation and issues. The results of this initial assessment are notified to the user's device and displayed on a dashboard. The user can review the results and request detailed consulting if necessary.

[0331] 3. Individual consulting proposals

[0332] When a user requests detailed consulting, the server provides an interface for entering detailed information. The user can then enter additional specific issues or requests and submit them. The emotion engine continues to recognize the user's emotional state. The server then sends the collected details and emotional information to the AI ​​analysis module for further analysis. The AI ​​module generates specific solutions and proposals taking the user's emotional state into account. These proposals are displayed on the user's dashboard, and the server provides detailed explanations and links to materials.

[0333] 4. Needs and Trends Analysis

[0334] The server then passes the collected information, proposal data, and emotional information from users back to the AI ​​analysis module, which analyzes overall needs and trends. This AI module analyzes large amounts of data to extract market trends, common user needs, and emotional responses. Based on the results of this analysis, it proposes optimal services and solutions to users. These results are displayed on the user's dashboard.

[0335] 5. User Matching

[0336] The server searches for other users with similar challenges and needs and matches them with each other. The emotion engine also takes into account the user's emotional state to suggest the best partner for building a better relationship. The server notifies the user of the matching results and offers contact methods and partnership suggestions. The user then contacts other companies and considers joint projects. During this process, feedback from the emotion engine promotes smooth communication.

[0337] Specific examples

[0338] Example 1: Improving manufacturing efficiency

[0339] User A (a small to medium-sized manufacturing company) inputs the issue of improving the efficiency of the manufacturing process. The emotion engine detects User A's stress level at the time of input and sends it to the AI ​​module. The server performs an initial analysis based on this information and proposes automating the production line and introducing an inventory management system. When explaining the proposal, the server uses language that reduces User A's stress. User A accepts the proposal with peace of mind and makes a specific implementation plan.

[0340] Example 2: Strengthening your marketing strategy

[0341] User B (an IT startup) is looking for a new marketing strategy. By providing detailed information along with emotional information, the server makes suggestions with the appropriate tone and content. The AI ​​module suggests expanding the target market or strengthening the social media campaign, and the server communicates this to User B, taking the emotional information into account. User B then takes concrete steps to implement the suggestions, improving the success rate.

[0342] Example 3: New business through user matching

[0343] User C (a logistics company) and User D (an e-commerce company) are both seeking to reduce logistics costs. The emotion engine monitors the emotional state of both parties when they use the system and matches them at the optimal time. Based on this information, the server provides proposals for joint delivery services. With the support of the emotion engine, User C and User D communicate smoothly and build a mutually satisfying cooperative relationship.

[0344] Prompt Sentence Examples

[0345] "Enter your manufacturing process efficiency challenge. The emotion engine will detect your stress level and provide you with appropriate suggestions."

[0346] "Please provide us with detailed information and sentiment information on strengthening your marketing strategy. We will suggest strengthening your social media campaign."

[0347] "Consider a joint project with a user looking to reduce logistics costs. We will support you with our emotion engine to ensure smooth communication."

[0348] As described above, the present invention is a system that takes into account the information and emotional state provided by the user and provides optimal suggestions and matching, thereby efficiently resolving user problems and creating business opportunities, thereby improving user satisfaction.

[0349] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0350] Step 1:

[0351] A user accesses the system and displays the account registration screen.

[0352] Specific operation: The user accesses the system's web page or dedicated application from their own device and opens the account registration screen, where an interface for registering the user's information (e.g., company name, address, contact name) is displayed.

[0353] Input: Basic information entered by the user, such as company information and contact name

[0354] Output: Displaying the registration screen and receiving the entered information

[0355] Step 2:

[0356] The terminal accepts the user's information input, and the emotion engine monitors the input behavior (typing speed, mouse movement).

[0357] Specific actions: As users enter company information, job descriptions, and specific tasks, the emotion engine records their input actions in the background.

[0358] Input: Information entered by the user and behavioral data recorded by the emotion engine

[0359] Output: Collection of input information and operational data

[0360] Step 3:

[0361] The device sends the input information and emotion information to the server, which receives it and stores it in a database.

[0362] Specific operation: The device sends the information entered by the user and the behavioral data collected by the emotion engine to the server in one batch. The server immediately records this data in a database upon receiving it.

[0363] Input: User input and behavior data

[0364] Output: Information and behavioral data recorded in a database

[0365] Step 4:

[0366] The server sends a verification email to the user and activates the account.

[0367] Specific operation: The server generates an authentication email based on the user information stored in the database and sends it to the user's registered email address. The user can activate their account by clicking the link contained in this email.

[0368] Input: User information in the database

[0369] Output: Verification email sent to the user's email address

[0370] Step 5:

[0371] The server sends the saved user information and emotional information to the AI ​​analysis module, which begins the initial analysis.

[0372] Specific operation: The server extracts user information and emotional information stored in the database and sends it to the AI ​​analysis module, which then performs an initial assessment of the user's current situation and challenges based on the data sent.

[0373] Input: User information and emotion information in the database

[0374] Output: Generates initial analysis results

[0375] Step 6:

[0376] The AI ​​analysis module generates the initial analysis results, which the server notifies the user's device.

[0377] How it works: The AI ​​analysis module processes the user's information and emotional data to generate an initial evaluation result, which is then sent to the user's device via the server and displayed on the dashboard.

[0378] Input: Stored user information and emotion information

[0379] Output: Initial analysis results displayed on the user's terminal.

[0380] Step 7:

[0381] If the user requests detailed consultation, the server provides an interface for entering detailed information.

[0382] Specific operation: If the user checks the initial analysis results and requests further consultation, the server will provide a new input interface where the user can enter more specific issues and requests.

[0383] Input: Initial analysis results and requests for further information

[0384] Output: Display detailed information input interface

[0385] Step 8:

[0386] The device collects the user's detailed information, and the emotion engine recognizes the user's emotional state. The server receives this information and sends it to the AI ​​analysis module for further analysis.

[0387] Specific actions: When the user enters detailed issues or requests, the emotion engine continues to monitor the user's actions and record their emotional state. The device then sends these details and emotional state data to the server, which then sends them back to the AI ​​analysis module for re-analysis.

[0388] Input: User details and emotional state data

[0389] Output: Generate reanalysis results

[0390] Step 9:

[0391] The AI ​​analysis module then reanalyzes the data and generates personalized suggestions, which the server displays on the user's device, along with detailed explanations and links to resources.

[0392] How it works: The AI ​​analysis module reanalyzes the detailed information and emotional state data to generate personalized suggestions for the user. The generated suggestions are sent to the user's device via the server and displayed on the dashboard. At the same time, the server also provides detailed explanations of the suggestions and links to related materials.

[0393] Input: User details and emotional state data

[0394] Output: Reanalysis results and suggestions displayed on the user's device

[0395] Step 10:

[0396] The server passes the information collected from the user, suggestion data, and emotional information back to the AI ​​analysis module to analyze overall needs and trends.

[0397] Specific operation: The server sends all collected data to an AI analysis module, which analyzes common needs, market trends, and emotional responses of multiple users.

[0398] Input: All information and sentiment collected from the user

[0399] Output: Analysis of needs and trends

[0400] Step 11:

[0401] Based on the results of an analysis of needs and trends, the server suggests the most suitable services and products for the user and displays them on the dashboard.

[0402] Specific operation: Based on the analysis results obtained from the AI ​​analysis module, the server selects services and products (e.g., the latest inventory management tools, optimal marketing strategies) that are suitable for the user's detailed data and displays them on the user's dashboard.

[0403] Input: Analysis of needs and trends

[0404] Output: Service and product suggestions displayed on the user's dashboard

[0405] Step 12:

[0406] The server searches for other users with similar issues and needs and matches them using an emotion engine.

[0407] How it works: The server searches its database to identify other users with similar challenges and needs, and uses an emotion engine to select the best match and match users together.

[0408] Input: User issues, needs, and emotional information

[0409] Output: Generates matching results

[0410] Step 13:

[0411] The server notifies the user of the matching results and provides contact methods and partnership suggestions.

[0412] Specific operation: After receiving the matching results, the server sends them to the user's device and provides contact methods and specific collaboration proposals, including contact information and proposed joint projects.

[0413] Input: Matching results

[0414] Output: Proposal displayed on the user's device and contact information

[0415] These are the processing steps of this system. This system allows users to receive optimal suggestions that take their emotional state into consideration and match users with each other, leading to problem solving and the creation of new business opportunities.

[0416] (Application example 2)

[0417] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0418] In traditional logistics center operations, optimizing delivery schedules and streamlining business processes are extremely important. However, many logistics centers lack systems that can provide optimal proposals that take into account data analysis and emotional states to resolve these issues. This makes it difficult to operate efficiently and reduce logistics costs. Furthermore, it is difficult to build effective collaborative relationships with other logistics centers that face similar challenges, so a comprehensive solution to improve overall operational efficiency is needed.

[0419] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for accepting information input from a user; means for saving the input information in a database; means for using an artificial intelligence module to perform an initial analysis based on the saved information; means for providing the initial analysis result to the user; means for using an artificial intelligence module to collect detailed information based on the initial analysis result and perform a reanalysis; means for generating an individual proposal based on the reanalysis result and providing it to the user; means including an emotion engine that recognizes the user's emotional state and uses the emotional information for analysis; means for using an artificial intelligence module to analyze the user's overall needs and tendencies; means for providing optimal services and solutions based on the analysis results; and means for searching for other users with similar issues and needs and matching users with each other. This makes it possible to improve the operational efficiency of the logistics center, provide appropriate proposals, and build effective cooperative relationships with other logistics centers with similar issues.

[0420] "User" refers to an individual or company that uses the system to input business issues and receives analysis and proposals based on those issues.

[0421] "Means for accepting input of information" refers to the interface or device that allows users to input business tasks and basic information.

[0422] "Means for storing in a database" refers to a system or device for recording and storing information and emotional information input by a user in a database.

[0423] "Artificial intelligence module that performs initial analysis" refers to the artificial intelligence algorithms and software that analyze the user's current situation and issues based on information stored in the database.

[0424] "Means for providing the user with the results of the initial analysis" refers to a system or device for notifying and displaying the results of the initial analysis to the user.

[0425] "Artificial intelligence module that collects detailed information and performs reanalysis" refers to an artificial intelligence algorithm or software that performs reanalysis based on detailed tasks and additional information entered by the user.

[0426] "Means for generating and providing individual proposals to users" refers to a system or device that generates specific solutions or proposals that can be implemented by users based on the results of the reanalysis, and notifies and displays them to users.

[0427] "Emotion engine that recognizes emotional states and uses emotional information for analysis" refers to an algorithm or wireless communication device that recognizes a user's emotional state in real time and uses that information for analysis.

[0428] "Artificial intelligence module for analyzing overall needs and trends" refers to artificial intelligence algorithms and software that analyze information and emotional information collected from many users to identify common needs and trends.

[0429] "Means for providing optimal services and solutions" refers to systems and devices that propose and provide the most suitable services and solutions to users based on the analysis results.

[0430] "Means for searching for other users and matching users" refers to a system or device that finds other users with similar issues or needs and connects those users with each other.

[0431] This invention is a system for improving the operational efficiency of logistics centers, which uses an emotion engine and an artificial intelligence module to analyze users' business issues and make optimal proposals and matching. This system is composed of user terminals, a server, and various databases.

[0432] First, a user accesses the system using a terminal and registers an account. The user enters basic information about the logistics center and specific business tasks, and the terminal sends and stores this information in a database. At the same time, an emotion engine recognizes the user's input and emotional state during operation, and this information is also stored in the database.

[0433] The server then uses an artificial intelligence module to perform an initial analysis based on the stored information. During the initial analysis, the user's input information and emotional information are integrated and analyzed to generate proposals for optimizing and automating logistics schedules. These proposals are then sent to the user's device and displayed on a dashboard. The user can review these proposals and request further consultation if necessary.

[0434] When a detailed consultation is requested, the server provides the user with an interface for inputting additional information. The user uses this to input and submit additional specific issues or requests. The emotion engine continues to recognize the user's emotional state at this point.

[0435] The server then performs a re-analysis based on the collected detailed information and sentiment data. During the re-analysis, the AI ​​module generates specific solutions and proposals and provides them to the user. This allows the logistics center to develop actionable measures, such as more efficient delivery schedules and the introduction of automated systems.

[0436] Furthermore, the server analyzes the information and proposal data collected from users to extract overall needs and trends. Based on this, the server understands market trends and common needs of users and recommends optimal services and products. These recommendations are displayed on the dashboard, increasing user satisfaction.

[0437] Finally, the server searches for other users with similar issues and needs and matches them with each other. The emotion engine takes the user's emotional state into account when matching and suggests matches at the optimal time. This facilitates smooth cooperation between logistics centers and improves operational efficiency.

[0438] Hardware and software used

[0439] Hardware: User devices (smartphones, tablets, etc.), servers

[0440] Software: Flask (web framework), Pandas (data manipulation library), scikit-learn (machine learning library), emotion engine (Emotion Recognition)

[0441] Adding specific examples

[0442] As an example, suppose logistics center A registers with the system and the emotion engine recognizes that the user is in a high-stress state. An initial analysis generates a proposal to optimize the delivery schedule, and the user requests detailed consulting. A further analysis provides proposals for optimizing delivery routes and automating solutions. In addition, a collaboration with logistics center B, which has similar challenges, is suggested, realizing cost savings through joint deliveries.

[0443] Example prompt for a generative AI model:

[0444] "Generate proposals to optimize delivery schedules, taking into account the stress level of distribution center A."

[0445] In this way, the present invention provides a specific means for improving the operational efficiency of a logistics center.

[0446] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0447] Step 1:

[0448] A user accesses the system using a terminal and registers an account. The information entered is basic information about the logistics center and specific business tasks. The terminal sends this information to the database and stores it. The input data includes the company name, person in charge, contact information, task details, etc., and this information is recorded in the database.

[0449] Step 2:

[0450] The emotion engine recognizes the user's emotional state in real time as they input and stores that information in a database. At this stage, the emotion engine determines the user's stress level and emotional state from their input actions, facial expressions, voice, etc., and adds that information to the database.

[0451] Step 3:

[0452] The server performs an initial analysis based on the stored information. An AI module uses this information to analyze and generate proposals for optimizing logistics schedules and introducing automated systems. The user's input data (basic information, business issues) and emotional information are used as input data, which the AI ​​module analyzes to generate initial proposals. The generated proposals are sent to the terminal and displayed on the dashboard.

[0453] Step 4:

[0454] If the user checks the initial analysis results and requests detailed consulting, the server provides an interface for inputting additional information. The user inputs additional specific issues and requests, and the terminal sends the information to the server. The input data includes specific problems and requests for improvement.

[0455] Step 5:

[0456] The emotion engine recognizes the user's emotional state again and stores that information in the database. The user's emotional state is taken into account when reanalyzing, so the emotional information at the time of input is also added.

[0457] Step 6:

[0458] The server performs reanalysis based on the collected detailed information and emotional information. The artificial intelligence module analyzes the detailed information and emotional information and generates specific solutions and proposals. The input data (detailed information, additional tasks, emotional information) is processed and specific proposals are generated as a result of the reanalysis. The generated proposals are sent to the terminal and notified to the user.

[0459] Step 7:

[0460] The server then re-analyzes the collected information and proposal data to analyze overall needs and trends. An AI module analyzes large amounts of data to extract market trends and common needs. The input data includes past proposal data and user sentiment information, and the analysis outputs market trends and common needs.

[0461] Step 8:

[0462] The server generates proposals based on the analysis results to provide optimal services and solutions to users. It recommends optimal services and products and displays them on a dashboard. The input data includes analysis results and sentiment information, and proposals are generated based on this.

[0463] Step 9:

[0464] The server searches for other users with similar issues and needs and matches them with each other. An emotion engine takes into account the user's emotional state and suggests matching at the optimal time. Input data includes the user's business issues and emotional information, and the optimal match is selected based on this. Users can contact other logistics centers and work together.

[0465] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0466] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0467] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0468] [Second embodiment]

[0469] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0470] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0471] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0472] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0473] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0474] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0475] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0476] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0477] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0478] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0479] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0480] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0481] 1. User registration and information entry

[0482] The user accesses the system and registers an account. An interface for entering basic company information, job description, and specific tasks is displayed on the terminal. The user then enters the necessary information into the system and submits it.

[0483] The server receives the information entered by the user and stores it in a database. The stored information is used for analysis, so accurate and detailed information is required. After saving, the server sends a verification email to the user and activates the account.

[0484] 2. Initial analysis using AI

[0485] The server sends the saved user information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module compares the information with past databases and makes an initial assessment of the user's current situation and challenges.

[0486] The initial evaluation results are sent to the user's device and displayed on a dashboard. The user can review the results and request further consultation if necessary.

[0487] 3. Individual consulting proposals

[0488] When a user requests detailed consulting, the server provides an interface to initiate the collection of additional details, allowing the user to enter and submit more specific issues and requests.

[0489] The server then uses the details provided by the user to perform further analysis using the AI ​​module, which generates more specific solutions and suggestions and sends them back to the server in text format.

[0490] The generated suggestions are displayed on the user's dashboard, and the server provides detailed explanations and links to documentation for these suggestions, allowing the user to review the suggestions and receive guidance on actionable measures.

[0491] 4. Needs and Trends Analysis

[0492] The server then passes the information collected from users and the proposed data back to the AI ​​module, which analyzes the overall needs and trends. The AI ​​module then analyzes the large amount of data to extract current market trends and common user needs.

[0493] The analysis results are used to provide services and solutions that best suit the user's needs. Based on these results, the server recommends services and products that are suitable for the user and displays them on the dashboard.

[0494] 5. Matching users

[0495] The server searches for other users with similar challenges and needs and matches them with each other, potentially leading to joint projects and partnerships.

[0496] The server notifies users of the matching results and provides contact methods and partnership proposals to create business opportunities. Users can contact other companies and consider joint projects.

[0497] Specific examples

[0498] Example 1: Improving manufacturing efficiency

[0499] User A (a small to medium-sized manufacturing company) inputs the issue of improving the efficiency of its manufacturing process. The server sends this information to the AI ​​module, which performs an initial analysis. The AI ​​module then proposes measures to automate the production line and introduce an inventory management system, which the server provides to User A. User A then creates a specific implementation plan based on these proposals.

[0500] Example 2: Strengthening your marketing strategy

[0501] User B (an IT startup) is looking for a new marketing strategy. The server collects detailed information and reanalyzes it using the AI ​​module. The AI ​​module then suggests ways to expand the target market and strengthen the social media campaign, which the server then provides to User B. User B then takes specific steps to implement the proposed strategy.

[0502] Example 3: New business through user matching

[0503] User C (a logistics company) and User D (an e-commerce company) are both seeking to reduce logistics costs. Based on this information, the server matches the two parties and offers a joint delivery service proposal. User C and User D consider forming a partnership and actually start a joint project.

[0504] This system allows users to solve their own problems and discover new business opportunities. The entire system process is user-friendly and supports the growth and efficiency of companies.

[0505] The processing flow will be explained below.

[0506] Step 1:

[0507] A user accesses the consulting service system and enters detailed information such as company information, business details, and specific issues on the registration screen displayed on the terminal.

[0508] Step 2:

[0509] The server receives the information entered by the user and stores it in a database, after which the server sends a verification email to the user and activates the account.

[0510] Step 3:

[0511] The server sends the saved user information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module compares the information with a past database and makes an initial assessment of the user's current situation and challenges.

[0512] Step 4:

[0513] The AI ​​module generates initial analysis results and sends them back to the server, which receives them and displays them on the user's dashboard. The user can then view the initial analysis results.

[0514] Step 5:

[0515] When a user requests detailed consulting, the server provides the user with an interface for inputting detailed information, and the user inputs and submits additional specific issues and requests.

[0516] Step 6:

[0517] The server then uses the detailed information collected from the user to perform further analysis using the AI ​​module, which then generates specific solutions and suggestions and sends them back to the server.

[0518] Step 7:

[0519] The server displays the generated proposals on the user's dashboard, where the user can review the proposals and receive guidance on specific measures.

[0520] Step 8:

[0521] The server then passes the collected information and proposal data back to the AI ​​module, which analyzes overall needs and trends and extracts market trends and common user needs.

[0522] Step 9:

[0523] The server then recommends optimal services and solutions to the user based on the analysis results, and displays the recommendations on the user's dashboard with detailed explanations.

[0524] Step 10:

[0525] The server searches for other users with similar challenges and needs, matches users with each other, notifies users of the matching results, and provides contact methods and collaboration proposals to create business opportunities.

[0526] Step 11:

[0527] Users can contact other companies to discuss details of joint projects and partnerships, and the server provides functionality to support the necessary information sharing and exchange of materials.

[0528] This allows users to efficiently solve problems and explore new business opportunities.

[0529] Example 1

[0530] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0531] In today's business environment, companies need to respond quickly to diversifying challenges and needs. However, achieving this requires accurate information gathering, appropriate analysis, and specific proposals. Traditional methods make these processes time-consuming and labor-intensive, making it difficult to carry them out efficiently and effectively. Furthermore, it is not easy to find suitable partners for inter-company collaboration and matching. Therefore, an efficient system is needed to help companies solve their own challenges and discover new business opportunities.

[0532] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0533] In this invention, the server includes means for accepting information input from a user, means for saving the input information in a database, means for using an artificial intelligence module to perform an initial analysis based on the saved information, means for providing the initial analysis results to the user, means for using an artificial intelligence module to collect detailed information based on the initial analysis results and perform a re-analysis, means for generating individual proposals based on the re-analysis results and providing them to the user, means for using the artificial intelligence module to analyze the user's overall needs and trends, means for providing optimal services and solutions based on the analysis results, means for searching for other users who have similar issues or needs and matching users with each other, means for sending a verification email to the user and activating the account, means for receiving the user's detailed information, converting it into an appropriate format, and sending it to the artificial intelligence module, means for displaying the results of the re-analysis on the user's dashboard and providing related materials and links, and means for generating information recommended to the user based on the analysis results and displaying it on the dashboard.

[0534] This allows companies to quickly and accurately identify problems and receive solutions based on concrete proposals, while also promoting collaboration between companies and creating new business opportunities.

[0535] "User" refers to the entity that uses the system to input information and receive analysis results and suggestions.

[0536] "Means for accepting input of information" refers to the function of providing an interface that allows users to access the system and input company information and tasks.

[0537] "Database" refers to a storage or management system for structuring and storing received information.

[0538] An "artificial intelligence module" refers to a program with machine learning and data analysis capabilities that analyzes stored information and generates results.

[0539] "Initial analysis" refers to the initial information analysis process based on the basic information and issues provided by the user.

[0540] "Reanalysis" refers to the process of reanalyzing information based on more detailed information.

[0541] "Individual proposals" refer to specific solutions or action plans generated to address the user's specific challenges or requests.

[0542] "Needs and Trend Analysis" refers to the analytical process used to extract common issues and market trends based on data collected from users across the board.

[0543] "Verification Email" means the confirmation email sent to the email address provided by the User to activate the Account.

[0544] "Dashboard" refers to the web application interface that allows users to visually view analysis results and recommendations.

[0545] "Matching" refers to the process of searching for other users with similar challenges and needs and connecting suitable users with each other.

[0546] The present invention is a system for users to solve problems and discover new business opportunities. This system focuses on a series of processes in which users input information and receive analysis results and proposals.

[0547] User registration and information entry

[0548] Users access the system's registration page using a web browser on their device. They enter the required information through an interface that asks for company information, job description, and specific tasks, and then click the "Submit" button. The server receives this information as an HTTP request and stores it in a MySQL or PostgreSQL database. Once the information is saved, the server uses an email sending service such as SendGrid to send a verification email to the user. The user then clicks the link in the email to activate their account.

[0549] Initial analysis by AI

[0550] The server sends the saved user information to an AI analysis module such as TensorFlow or PyTorch in an appropriate format (JSON or CSV). The AI ​​module analyzes this information and compares it with past data to make an initial assessment of the user's current situation and challenges. Once the analysis is complete, the AI ​​module returns the results to the server, which displays them on the user's dashboard (built with React or Angular). The user can then view the initial assessment results on the dashboard using their device.

[0551] Individual consulting proposals

[0552] If the user requests detailed consulting, the server provides the user with an interface (such as an HTML form) to collect additional details. The user enters the details and clicks the "Submit" button again. The server receives this information and sends it back to the TensorFlow or PyTorch AI module in the appropriate format. The AI ​​module reanalyzes it and proposes a specific solution. The server displays this proposal on the user's dashboard, providing related materials and links. The user can then plan specific actions based on this.

[0553] Needs and trends analysis

[0554] The server performs large-scale data analysis on the information and proposal data collected from all users using big data processing platforms such as Hadoop and Spark. The AI ​​module uses this data to extract market trends and common user needs. The analysis results are returned to the server, which then uses this information to recommend optimal services and solutions to the user. This information is displayed on the user's dashboard.

[0555] Matching users

[0556] The server searches a database for other users with similar challenges and needs and matches them with suitable users. The matching results are provided to users via a dashboard and email notifications. Users can contact other companies based on the displayed information and consider joint projects. The server provides contact methods and partnership proposals, helping to create business opportunities.

[0557] Specific examples

[0558] (Example 1: Improving efficiency in manufacturing)

[0559] User A inputs the issue of improving the efficiency of the manufacturing process. The server sends this information to the AI ​​module, which performs an initial analysis. The AI ​​module then proposes measures such as automating the production line and introducing an inventory management system, which the server then provides to User A.

[0560] (Example 2: Strengthening marketing strategies)

[0561] User B wants to propose a new marketing strategy. The server collects detailed information and reanalyzes it with the AI ​​module. The AI ​​module then suggests expanding the target market or strengthening the social media campaign, which the server then provides to User B.

[0562] (Example 3: New business through user matching)

[0563] User C (a logistics company) and User D (an e-commerce company) are looking to reduce logistics costs. The server matches the two parties and offers a joint delivery service. User C and User D consider partnering and start a joint project.

[0564] Prompt Sentence Examples

[0565] "Please give us some specific suggestions on how to improve the efficiency of the manufacturing process."

[0566] "We're looking for suggestions for new marketing strategies."

[0567] "Please tell us some specific solutions to reduce logistics costs."

[0568] This system enables companies to quickly identify problems and find solutions, thereby improving operational efficiency and creating new business opportunities.

[0569] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0570] Step 1:

[0571] The user accesses the account registration page. Using a terminal, the user enters the specified URL into a web browser and arrives at the system's registration page. This page displays an interface for entering the required information. The input information includes company information, job description, specific challenges, etc.

[0572] Step 2:

[0573] The user enters information and submits it. The user enters the company name, business details, and the problem they want to solve from the terminal and clicks the "Submit" button. The entered data is sent as an HTTP request to the server.

[0574] Step 3:

[0575] The server receives the information and stores it in a database. The server analyzes the user's input information received as an HTTP request and stores it in a database (for example, MySQL or PostgreSQL). The stored data includes the user's company information, business details, and the problem they want to solve. The input is the information the user enters from their terminal, and the output is structured data stored in the database.

[0576] Step 4:

[0577] The server sends a verification email and the user activates the account. The server uses an email sending service (e.g. SendGrid) to send a verification email to the user's email address. The user checks their mailbox and clicks the verification link contained in the email to activate their account. The input is the user's email address stored by the server, and the output is the status of successful authentication.

[0578] Step 5:

[0579] The server sends user information to the AI ​​analysis module. The server converts the user information stored in the database into an appropriate format (e.g., JSON, CSV) and sends it to the AI ​​analysis module (e.g., TensorFlow or PyTorch) via an HTTP API. The input is the user information retrieved from the database, and the output is the completion status of transmission to the AI ​​analysis module.

[0580] Step 6:

[0581] The AI ​​module analyzes the information and generates results. The AI ​​module analyzes the received user information and compares it with past data to make an initial assessment of the user's current situation and issues. The input is the user information sent from the server, and the output is the analysis results.

[0582] Step 7:

[0583] The server displays the initial evaluation results on the user's dashboard. The server displays the initial evaluation results received from the AI ​​module on the user's dashboard (built with React or Angular). The user uses a terminal to check the initial evaluation results on the dashboard. The input is the initial evaluation result from the AI ​​module, and the output is the evaluation result displayed on the user's dashboard.

[0584] Step 8:

[0585] The user requests detailed consulting. The user clicks the "Request detailed consulting" button on the dashboard and proceeds to the interface for collecting additional information. The input is the user's request action, and the output is the display of the interface for entering detailed information.

[0586] Step 9:

[0587] The server provides an interface for the user to gather additional details. The server displays an interface (HTML form) to the user to gather additional details, including the specific problem in the business flow and the type of solution desired. The input is the server's interface display, and the output is preparation to accept user input.

[0588] Step 10:

[0589] User enters details and submits: The user enters details into a form and clicks the "Submit" button. The input is the details entered by the user at the terminal and the output is an HTTP request to the server.

[0590] Step 11:

[0591] The server uses the detailed information to perform re-analysis using the AI ​​module. The server converts the received detailed information into an appropriate format and sends it back to the AI ​​module. The AI ​​module then performs re-analysis and generates specific suggestions. The input is the detailed information sent by the user, and the output is the analysis result returned by the AI ​​module.

[0592] Step 12:

[0593] The server displays the generated suggestions on the user's dashboard. The server displays the suggestions received from the AI ​​module on the user's dashboard, and also provides related materials and links. The user uses their device to check the suggestions on the dashboard. The input is the analysis result of the AI ​​module, and the output is the suggestions displayed on the user's dashboard.

[0594] Step 13:

[0595] The server analyzes needs and trends based on the collected information and proposal data. The server analyzes all user data using Hadoop or Spark to extract market trends and common needs. The input is collected data from all users, and the output is the market trends and user needs analysis results.

[0596] Step 14:

[0597] The server provides the user with the optimal services and solutions based on the analysis results.The server then displays the optimal products and services on the user's dashboard based on the analysis results.The input is the analysis results, and the output is the recommended services and products that are displayed to the user.

[0598] Step 15:

[0599] The server searches for other users with similar issues and needs and performs matching. The server searches for similar users from the database and notifies the user of the matching results. The input is the user's issue information, and the output is the matching results for similar users.

[0600] Step 16:

[0601] Users contact other companies to consider joint projects. The server provides contact methods and collaboration proposals to help start joint projects. The input is the user's contact action, and the output is the provision of contact methods and collaboration proposals.

[0602] (Application example 1)

[0603] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0604] Modern factory operations require efficient management and optimization of production processes. However, manual information entry and management is time-consuming, making it difficult to make efficient decisions. It is also difficult to select appropriate solutions and services and to build a collaborative system between users. In addition, the lack of real-time feedback often delays productivity improvements.

[0605] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0606] In this invention, the server includes means for accepting information input from a user, means for storing the input information in a database, means for using an artificial intelligence module to perform an initial analysis based on the stored information, means for providing the results of the initial analysis to the user, means for using an artificial intelligence module to collect detailed information based on the results of the initial analysis and perform a reanalysis, means for generating individual proposals based on the results of the reanalysis and providing them to the user, means for using the artificial intelligence module to analyze the overall needs and trends of the user, means for providing optimal services and solutions based on the results of the analysis, means for searching for other users who have similar issues or needs and matching users with each other, means for providing an interface for managing information from multiple users in a unified manner, means for managing and optimizing automated factory equipment based on information input by the user, and means for providing real-time feedback to users to improve productivity. This enables efficient management and optimization of production processes, rapid decision-making, building a cooperative system among users, and improving productivity through real-time feedback.

[0607] "User" refers to an individual company or individual who uses the system.

[0608] "Means for accepting information input" refers to an interface that allows a user to input information into the system.

[0609] "Means for storing in a database" refers to a database system for storing and managing input information for a long period of time.

[0610] "Artificial intelligence module that performs initial analysis" refers to the AI ​​analysis engine that performs initial data analysis.

[0611] "Means for providing initial analysis results to a user" refers to means for displaying the analysis results on a user's dashboard or interface.

[0612] "Artificial intelligence module for reanalysis" refers to an AI analysis engine that reanalyzes data based on detailed information.

[0613] "Means for generating individual proposals and providing them to the user" refers to the part of the system that generates specific proposals based on the analysis results and notifies the user of them.

[0614] "Artificial intelligence module for analyzing overall needs and trends" refers to an AI engine for analyzing overall user data needs and market trends.

[0615] "Means for providing optimal services and solutions" refers to the part of the system that suggests the most suitable services and products to users based on the analysis results.

[0616] "Means for searching for other users with similar challenges and needs and matching users together" refers to the part of the system that connects users with common needs and challenges, providing opportunities for information sharing and collaborative projects.

[0617] "Interface for managing information from multiple users at once" refers to an interface for managing and displaying information obtained from a large number of users in a unified manner.

[0618] "Means for managing and optimizing automated factory equipment" refers to the system part for automating equipment within a factory and optimizing its operation.

[0619] "Means for providing real-time feedback" refers to the part of the system that immediately provides the user with feedback on analysis results and recommended actions.

[0620] MODE FOR CARRYING OUT THE INVENTION

[0621] This invention is a system that aims to improve the efficiency and optimization of production processes within factories. Specifically, it is a system that uses artificial intelligence (AI) to analyze information entered by users and propose appropriate solutions. This system consists of the following main components:

[0622] 1. User registration and information entry

[0623] First, the user accesses the system and registers an account. After registration, an interface is provided for entering basic factory information, current work content, and specific tasks, and the user then enters and submits the information required for the system. The entered information is saved in a database (e.g., MySQL) by the server. After saving, the server sends the user an authentication email and activates the account.

[0624] 2. Initial analysis using AI

[0625] The server sends the saved user information to an AI analysis module (e.g., TensorFlow, PyTorch) and begins initial analysis. The AI ​​module compares the information with past data and performs an initial assessment of the user's current situation and issues. The results of the initial assessment are notified to the user's device and displayed on a dashboard.

[0626] 3. Individual consulting proposals

[0627] When a user requests a detailed consultation, the server provides an interface to begin collecting additional details. The user then enters and submits a more specific challenge or request. The server then performs a re-analysis using the AI ​​module based on the details provided by the user. The generated proposals are displayed on the user's dashboard, and the server provides detailed explanations and links to resources related to these proposals.

[0628] 4. Factory equipment management and optimization

[0629] Based on the information entered by the user, the server manages and optimizes automated factory equipment, identifying bottlenecks on production lines within the factory and suggesting the introduction of automation tools or redistribution of tasks, thereby improving factory efficiency.

[0630] 5. Providing real-time feedback

[0631] Furthermore, the server provides users with real-time feedback to improve productivity. For example, if a decline in efficiency in a specific process is detected, the server immediately notifies the user of the problem and suggests improvement measures. The server also monitors the effectiveness of the implemented improvement measures in real time and provides the results as feedback to the user.

[0632] 6. Needs and Trend Analysis

[0633] The server then passes the information collected from users and the proposed data back to the AI ​​analysis module, which analyzes overall needs and trends. The AI ​​module analyzes large amounts of data to extract current market trends and common user needs. The analysis results are used to provide services and solutions that best suit the user's needs.

[0634] 7. User Matching

[0635] The server searches for other users with similar challenges and needs and matches them with each other, leading to the possibility of joint projects and partnerships. The server notifies users of the results of the matches and provides contact methods and partnership proposals to create business opportunities.

[0636] Specific examples

[0637] Example 1: Streamlining the manufacturing process

[0638] A factory inputs the issue of improving the efficiency of its production line into the system. The server sends this information to the AI ​​analysis module, which performs an initial analysis. As a result of the analysis, it identifies bottlenecks in specific processes and suggests ways to resolve them.

[0639] Example prompt sentence:

[0640] User: We are looking to improve the efficiency of our manufacturing line. Please suggest us what the bottlenecks are in our current production line and how to resolve them.

[0641] AI analysis:

[0642] We analyzed the current production line data and found that the bottleneck mainly occurs between process A and process B. Please try the following improvement suggestions.

[0643] 1. Introduction of automation tools for process A

[0644] 2. Introduction of task distribution and parallel processing in Process B

[0645] 3. Optimizing the overall inventory management system

[0646] By using the system in this way, each user can solve their own problems quickly and efficiently.

[0647] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0648] Application example processing steps

[0649] (Processing Steps)

[0650] Step 1:

[0651] Users access the system using a terminal and register an account. They then enter basic factory information, business operations, and specific tasks through an interface. The input data is sent to the server in JSON format.

[0652] Input: Basic information about the factory, business operations, specific issues

[0653] Output: User information data in JSON format

[0654] Step 2:

[0655] The server stores the received user information in a database, which is managed in a MySQL database and used for future analysis.

[0656] Input: User information data in JSON format

[0657] Output: User information stored in the database

[0658] Step 3:

[0659] The server sends the saved user information to an AI analysis module (TensorFlow, PyTorch) to begin initial analysis. The AI ​​module compares the information with past databases and makes an initial assessment of the user's current situation and challenges.

[0660] Input: User information data, historical database

[0661] Output: Initial analysis results

[0662] Step 4:

[0663] The server notifies the user of the analysis results and displays them on the dashboard, allowing the user to check the initial analysis results.

[0664] Input: Initial analysis results

[0665] Output: Analysis results displayed on a dashboard

[0666] Step 5:

[0667] When a user requests a detailed analysis, the server provides an interface to start collecting additional information. The user can then enter more specific issues or requests and submit them. The submitted data is then sent back to the server in JSON format.

[0668] Input: Additional details, specific issues or requests

[0669] Output: Additional information data in JSON format

[0670] Step 6:

[0671] The server then uses the detailed information provided by the user to perform further analysis using the AI ​​analysis module, which then generates more specific solutions and suggestions and sends them back to the server in text format.

[0672] Input: Additional information data

[0673] Output: Reanalysis results, specific solution proposals

[0674] Step 7:

[0675] The server displays the generated proposals on the user's dashboard, providing detailed explanations and links to related materials. The user can review the proposals and select actionable measures.

[0676] Input: Reanalysis results, specific solution proposals

[0677] Output: Detailed proposal information displayed in a dashboard

[0678] Step 8:

[0679] The server then passes the collected user data and proposal data back to the AI ​​analysis module to analyze overall needs and trends. The AI ​​module then extracts market trends and common needs and sends the results back to the server.

[0680] Input: User data, Proposal data

[0681] Output: Needs and trends analysis

[0682] Step 9:

[0683] Based on the analysis results, the server proposes optimal services and solutions to users, and displays related business solutions and new products on a dashboard.

[0684] Input: Needs and trends analysis results

[0685] Output: Recommended services and solutions

[0686] Step 10:

[0687] The server searches for other users with similar challenges and needs, matches them, notifies users of the matching results, and provides suggestions for collaborative projects.

[0688] Input: User data, analysis results

[0689] Output: Matching results, joint project proposals

[0690] Step 11:

[0691] Based on the information entered by the user, the server manages and optimizes automated factory equipment, identifying bottlenecks on production lines within the factory, deploying automation tools, redistributing tasks, and monitoring data in real time.

[0692] Input: Factory information, analysis results

[0693] Output: Optimized factory equipment management data

[0694] Step 12:

[0695] The server provides users with real-time feedback to improve productivity. For example, if a decrease in efficiency in a particular process is detected, the server immediately notifies the user of the problem and suggests a remedial measure.

[0696] Input: Real-time monitoring data

[0697] Output: Notification and suggestions for improvement

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

[0699] 1. User registration and information entry

[0700] A user accesses the system and registers an account. On the registration screen displayed on the terminal, the user enters basic company information, job description, and specific tasks. The emotion engine also monitors the user's input and actions during registration to recognize the user's emotional state. This information is also saved as data.

[0701] The server receives the information entered by the user and the emotional information recognized by the emotion engine and stores it in a database. The stored information is used for analysis, so accurate and detailed information is required. After saving, the server sends a verification email to the user and activates the account.

[0702] 2. Initial analysis using AI

[0703] The server sends the saved user information and emotional information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module takes into account the past database and the user's current emotional information to make an initial assessment of the user's current situation and challenges.

[0704] The initial evaluation results are sent to the user's device and displayed on a dashboard. The user can review the results and request further consultation if necessary.

[0705] 3. Individual consulting proposals

[0706] If the user requests detailed consultation, the server provides an interface for the user to enter detailed information. The user enters and submits additional specific issues or requests. The emotion engine continues to recognize the user's emotional state at this point.

[0707] The server then re-analyzes the AI ​​module based on the detailed information and emotional information collected from the user, and the AI ​​module takes the user's emotional state into account when generating specific solutions and suggestions.

[0708] The generated suggestions are displayed on the user's dashboard, and the server provides detailed explanations and links to resources about these suggestions. Depending on the user's emotional state, the suggestions may be adjusted or followed up. The user can review the suggestions and receive guidance on actionable measures.

[0709] 4. Needs and Trends Analysis

[0710] The server then passes the collected information and suggestion data, as well as emotional information, back to the AI ​​module, which analyzes the overall needs and trends. The AI ​​module then analyzes the large amount of data to extract current market trends, common user needs, and users' emotional responses.

[0711] The analysis results are used to provide services and solutions that best suit the user's needs. Based on these results, the server recommends services and products that are suitable for the user and displays them on a dashboard. Recommendations selected based on emotional information can increase user satisfaction.

[0712] 5. Matching users

[0713] The server searches for other users with similar issues and needs and matches them with each other. The emotion engine also takes the user's emotional state into account when matching, suggesting the best partner for building a better relationship.

[0714] The server notifies users of the matching results and provides contact and partnership suggestions to create business opportunities. Users can contact other companies and consider joint projects. Feedback from the emotion engine promotes better communication, making collaborations smoother.

[0715] Specific examples

[0716] Example 1: Improving manufacturing efficiency

[0717] User A (a small to medium-sized manufacturing company) inputs the issue of improving the efficiency of the manufacturing process. The emotion engine detects User A's stress level at the time of input and sends it to the AI ​​module. The server performs an initial analysis based on this information and proposes automating the production line and introducing an inventory management system. When explaining the proposal, the server uses language that reduces User A's stress. User A accepts the proposal with peace of mind and makes a specific implementation plan.

[0718] Example 2: Strengthening your marketing strategy

[0719] User B (an IT startup) is looking for a new marketing strategy. By providing detailed information along with emotional information, the server makes suggestions with the appropriate tone and content. The AI ​​module suggests expanding the target market or strengthening the social media campaign, and the server communicates this to User B, taking the emotional information into account. User B then takes concrete steps to implement the suggestions, improving the success rate.

[0720] Example 3: New business through user matching

[0721] User C (a logistics company) and User D (an e-commerce company) are both seeking to reduce logistics costs. The emotion engine monitors the emotional state of both parties when they use the system and matches them at the optimal time. Based on this information, the server provides proposals for joint delivery services. With the support of the emotion engine, User C and User D communicate smoothly and build a mutually satisfying cooperative relationship.

[0722] This system allows users to receive services that take their emotional state into consideration, enabling them to solve problems and explore new business opportunities efficiently. The entire system process is user-friendly, supporting the growth and efficiency of companies and increasing user satisfaction.

[0723] The processing flow will be explained below.

[0724] Step 1:

[0725] A user accesses the system and registers an account. On the registration screen displayed on the terminal, the user enters company information, job details, and specific tasks. The emotion engine monitors the user's input and operations and recognizes their emotional state.

[0726] Step 2:

[0727] The server receives the information entered by the user and the emotion information recognized by the emotion engine and stores them in a database. After saving, the server sends a verification email to the user to activate the account. The emotion information is also stored.

[0728] Step 3:

[0729] The server sends the saved user information and emotional information to the AI ​​analysis module, which then compares the user's emotional information with the past database and makes an initial assessment of the user's current situation and challenges.

[0730] Step 4:

[0731] The AI ​​module generates initial analysis results and sends them back to the server, which receives them and displays them on the user's dashboard, where the user can view them.

[0732] Step 5:

[0733] If the user requests detailed consultation, the server provides an interface for the user to enter detailed information. The user enters and submits additional specific issues or requests. The emotion engine continues to recognize the user's emotional state at this point.

[0734] Step 6:

[0735] The server then uses the AI ​​module to reanalyze the details and emotional information collected from the user. The AI ​​module then generates specific solutions and proposals and sends them back to the server. The proposals may be adjusted based on the emotional information.

[0736] Step 7:

[0737] The server displays the generated suggestions on the user's dashboard, providing detailed explanations and links to resources. The suggestions may be adjusted based on the user's emotional state. The user can review the suggestions and take action accordingly.

[0738] Step 8:

[0739] The server then passes the collected information, suggestion data, and emotional information from users back to the AI ​​module to analyze overall needs and trends. The AI ​​module then analyzes market trends, common user needs, and emotional responses.

[0740] Step 9:

[0741] The server then recommends optimal services and solutions to users based on the analysis results. The recommendations are adjusted taking into account the user's emotional information and displayed on the dashboard, thereby increasing user satisfaction.

[0742] Step 10:

[0743] The server searches for other users with similar issues and needs and matches them with each other. The emotion engine also takes the user's emotional state into account when matching and suggests the most suitable partner.

[0744] Step 11:

[0745] The server notifies users of the matching results and provides contact methods and partnership proposals to create business opportunities. Users can contact other companies and discuss details of joint projects. The server provides functions to support the necessary information sharing and document exchange.

[0746] This allows the entire system to provide flexible services that reflect the user's emotional state, supporting the growth and efficiency of companies.

[0747] Example 2

[0748] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0749] Conventional systems have difficulty providing optimal proposals and solutions that take into account the user's specific issues and emotional state. Furthermore, when matching users, the system does not consider their emotional state when selecting the optimal partner, which can lead to problems in communication and building cooperative relationships between users. This results in lower user satisfaction and makes it difficult to effectively solve problems and create business opportunities.

[0750] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0751] In this invention, the server includes a means for accepting information input from a user, a means for using an artificial intelligence module that performs an initial analysis based on the stored information and emotional information, and a means for using an artificial intelligence module that collects detailed information while recognizing the user's emotional state and performs reanalysis. This enables highly accurate suggestions that take the user's emotional state into consideration. The server also includes a means for searching for other users with similar issues or needs and matching users while taking their emotional state into consideration, enabling smooth communication between users and the establishment of effective cooperative relationships.

[0752] A "user" is someone who accesses the system, inputs information, or uses services.

[0753] The "means for accepting information input" is an interface that accepts input of company information, business details, tasks, etc. from the user.

[0754] "Storage means" is a function that records input information and recognized emotional information in a database.

[0755] "Initial analysis" is the process by which the artificial intelligence module evaluates the user's current situation and challenges based on stored information and emotional information.

[0756] The "artificial intelligence module" is a module that analyzes information collected from users and makes proposals and evaluations for solving problems.

[0757] "Emotional state" refers to the mental and emotional state of a user when entering information or using a system.

[0758] The "emotion engine" is an engine that monitors the user's input and actions, and recognizes and evaluates their emotional state.

[0759] "Detailed information" is information about specific issues or requests that are additionally entered by the user.

[0760] "Reanalysis" is the process in which the artificial intelligence module analyzes again based on detailed information and emotional information after the initial analysis.

[0761] "Individual proposals" are problem-solving proposals or solutions specific to the user that are generated based on the results of the reanalysis.

[0762] "Needs and Trends Analysis" is the process of using all the information collected from users to extract common needs and market trends.

[0763] "Means for providing services and solutions" refers to an interface that suggests optimal services and products to users based on the results of analysis.

[0764] "Matching" is the process of searching for users with similar challenges and needs and selecting the most suitable partner, taking into account their emotional state.

[0765] "Business opportunities" are opportunities for new collaborations and projects that arise from matching users together.

[0766] The "means for providing contact methods and business partnership proposals" is a function that supports users in contacting each other and considering business partnerships.

[0767] The system of the present invention accepts information input from users and analyzes and proposes based on that information. A distinctive feature of this system is that it takes into account the emotional state of the user to make optimal proposals and match users with each other.

[0768] 1. User registration and information entry

[0769] First, users access the system and register an account. A registration screen is displayed on the terminal, allowing them to enter basic company information, job duties, and specific tasks. Specifically, information such as the company name, address, and name of the person in charge is entered. The emotion engine also monitors the user's behavior (e.g., typing speed, mouse movement) while entering data and recognizes their emotional state. All of this information is stored in a database. The server then sends the user a verification email and activates the account.

[0770] 2. Initial analysis using AI

[0771] The server sends the user information and emotional information stored in the database to the AI ​​analysis module, which begins the initial analysis. This AI module takes into account the past database and the user's current emotional information to make an initial assessment of the current situation and issues. The results of this initial assessment are notified to the user's device and displayed on a dashboard. The user can review the results and request detailed consulting if necessary.

[0772] 3. Individual consulting proposals

[0773] When a user requests detailed consulting, the server provides an interface for entering detailed information. The user can then enter additional specific issues or requests and submit them. The emotion engine continues to recognize the user's emotional state. The server then sends the collected details and emotional information to the AI ​​analysis module for further analysis. The AI ​​module generates specific solutions and proposals taking the user's emotional state into account. These proposals are displayed on the user's dashboard, and the server provides detailed explanations and links to materials.

[0774] 4. Needs and Trends Analysis

[0775] The server then passes the collected information, proposal data, and emotional information from users back to the AI ​​analysis module, which analyzes overall needs and trends. This AI module analyzes large amounts of data to extract market trends, common user needs, and emotional responses. Based on the results of this analysis, it proposes optimal services and solutions to users. These results are displayed on the user's dashboard.

[0776] 5. User Matching

[0777] The server searches for other users with similar challenges and needs and matches them with each other. The emotion engine also takes into account the user's emotional state to suggest the best partner for building a better relationship. The server notifies the user of the matching results and offers contact methods and partnership suggestions. The user then contacts other companies and considers joint projects. During this process, feedback from the emotion engine promotes smooth communication.

[0778] Specific examples

[0779] Example 1: Improving manufacturing efficiency

[0780] User A (a small to medium-sized manufacturing company) inputs the issue of improving the efficiency of the manufacturing process. The emotion engine detects User A's stress level at the time of input and sends it to the AI ​​module. The server performs an initial analysis based on this information and proposes automating the production line and introducing an inventory management system. When explaining the proposal, the server uses language that reduces User A's stress. User A accepts the proposal with peace of mind and makes a specific implementation plan.

[0781] Example 2: Strengthening your marketing strategy

[0782] User B (an IT startup) is looking for a new marketing strategy. By providing detailed information along with emotional information, the server makes suggestions with the appropriate tone and content. The AI ​​module suggests expanding the target market or strengthening the social media campaign, and the server communicates this to User B, taking the emotional information into account. User B then takes concrete steps to implement the suggestions, improving the success rate.

[0783] Example 3: New business through user matching

[0784] User C (a logistics company) and User D (an e-commerce company) are both seeking to reduce logistics costs. The emotion engine monitors the emotional state of both parties when they use the system and matches them at the optimal time. Based on this information, the server provides proposals for joint delivery services. With the support of the emotion engine, User C and User D communicate smoothly and build a mutually satisfying cooperative relationship.

[0785] Prompt Sentence Examples

[0786] "Enter your manufacturing process efficiency challenge. The emotion engine will detect your stress level and provide you with appropriate suggestions."

[0787] "Please provide us with detailed information and sentiment information on strengthening your marketing strategy. We will suggest strengthening your social media campaign."

[0788] "Consider a joint project with a user looking to reduce logistics costs. We will support you with our emotion engine to ensure smooth communication."

[0789] As described above, the present invention is a system that takes into account the information and emotional state provided by the user and provides optimal suggestions and matching, thereby efficiently resolving user problems and creating business opportunities, thereby improving user satisfaction.

[0790] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0791] Step 1:

[0792] A user accesses the system and displays the account registration screen.

[0793] Specific operation: The user accesses the system's web page or dedicated application from their own device and opens the account registration screen, where an interface for registering the user's information (e.g., company name, address, contact name) is displayed.

[0794] Input: Basic information entered by the user, such as company information and contact name

[0795] Output: Displaying the registration screen and receiving the entered information

[0796] Step 2:

[0797] The terminal accepts the user's information input, and the emotion engine monitors the input behavior (typing speed, mouse movement).

[0798] Specific actions: As users enter company information, job descriptions, and specific tasks, the emotion engine records their input actions in the background.

[0799] Input: Information entered by the user and behavioral data recorded by the emotion engine

[0800] Output: Collection of input information and operational data

[0801] Step 3:

[0802] The device sends the input information and emotion information to the server, which receives it and stores it in a database.

[0803] Specific operation: The device sends the information entered by the user and the behavioral data collected by the emotion engine to the server in one batch. The server immediately records this data in a database upon receiving it.

[0804] Input: User input and behavior data

[0805] Output: Information and behavioral data recorded in a database

[0806] Step 4:

[0807] The server sends a verification email to the user and activates the account.

[0808] Specific operation: The server generates an authentication email based on the user information stored in the database and sends it to the user's registered email address. The user can activate their account by clicking the link contained in this email.

[0809] Input: User information in the database

[0810] Output: Verification email sent to the user's email address

[0811] Step 5:

[0812] The server sends the saved user information and emotional information to the AI ​​analysis module, which begins the initial analysis.

[0813] Specific operation: The server extracts user information and emotional information stored in the database and sends it to the AI ​​analysis module, which then performs an initial assessment of the user's current situation and challenges based on the data sent.

[0814] Input: User information and emotion information in the database

[0815] Output: Generates initial analysis results

[0816] Step 6:

[0817] The AI ​​analysis module generates the initial analysis results, which the server notifies the user's device.

[0818] How it works: The AI ​​analysis module processes the user's information and emotional data to generate an initial evaluation result, which is then sent to the user's device via the server and displayed on the dashboard.

[0819] Input: Stored user information and emotion information

[0820] Output: Initial analysis results displayed on the user's terminal.

[0821] Step 7:

[0822] If the user requests detailed consultation, the server provides an interface for entering detailed information.

[0823] Specific operation: If the user checks the initial analysis results and requests further consultation, the server will provide a new input interface where the user can enter more specific issues and requests.

[0824] Input: Initial analysis results and requests for further information

[0825] Output: Display detailed information input interface

[0826] Step 8:

[0827] The device collects the user's detailed information, and the emotion engine recognizes the user's emotional state. The server receives this information and sends it to the AI ​​analysis module for further analysis.

[0828] Specific actions: When the user enters detailed issues or requests, the emotion engine continues to monitor the user's actions and record their emotional state. The device then sends these details and emotional state data to the server, which then sends them back to the AI ​​analysis module for re-analysis.

[0829] Input: User details and emotional state data

[0830] Output: Generate reanalysis results

[0831] Step 9:

[0832] The AI ​​analysis module then reanalyzes the data and generates personalized suggestions, which the server displays on the user's device, along with detailed explanations and links to resources.

[0833] How it works: The AI ​​analysis module reanalyzes the detailed information and emotional state data to generate personalized suggestions for the user. The generated suggestions are sent to the user's device via the server and displayed on the dashboard. At the same time, the server also provides detailed explanations of the suggestions and links to related materials.

[0834] Input: User details and emotional state data

[0835] Output: Reanalysis results and suggestions displayed on the user's device

[0836] Step 10:

[0837] The server passes the information collected from the user, suggestion data, and emotional information back to the AI ​​analysis module to analyze overall needs and trends.

[0838] Specific operation: The server sends all collected data to an AI analysis module, which analyzes common needs, market trends, and emotional responses of multiple users.

[0839] Input: All information and sentiment collected from the user

[0840] Output: Analysis of needs and trends

[0841] Step 11:

[0842] Based on the results of an analysis of needs and trends, the server suggests the most suitable services and products for the user and displays them on the dashboard.

[0843] Specific operation: Based on the analysis results obtained from the AI ​​analysis module, the server selects services and products (e.g., the latest inventory management tools, optimal marketing strategies) that are suitable for the user's detailed data and displays them on the user's dashboard.

[0844] Input: Analysis of needs and trends

[0845] Output: Service and product suggestions displayed on the user's dashboard

[0846] Step 12:

[0847] The server searches for other users with similar issues and needs and matches them using an emotion engine.

[0848] How it works: The server searches its database to identify other users with similar challenges and needs, and uses an emotion engine to select the best match and match users together.

[0849] Input: User issues, needs, and emotional information

[0850] Output: Generates matching results

[0851] Step 13:

[0852] The server notifies the user of the matching results and provides contact methods and partnership suggestions.

[0853] Specific operation: After receiving the matching results, the server sends them to the user's device and provides contact methods and specific collaboration proposals, including contact information and proposed joint projects.

[0854] Input: Matching results

[0855] Output: Proposal displayed on the user's device and contact information

[0856] These are the processing steps of this system. This system allows users to receive optimal suggestions that take their emotional state into consideration and match users with each other, leading to problem solving and the creation of new business opportunities.

[0857] (Application example 2)

[0858] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0859] In traditional logistics center operations, optimizing delivery schedules and streamlining business processes are extremely important. However, many logistics centers lack systems that can provide optimal proposals that take into account data analysis and emotional states to resolve these issues. This makes it difficult to operate efficiently and reduce logistics costs. Furthermore, it is difficult to build effective collaborative relationships with other logistics centers that face similar challenges, so a comprehensive solution to improve overall operational efficiency is needed.

[0860] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for accepting information input from a user; means for saving the input information in a database; means for using an artificial intelligence module to perform an initial analysis based on the saved information; means for providing the initial analysis result to the user; means for using an artificial intelligence module to collect detailed information based on the initial analysis result and perform a reanalysis; means for generating an individual proposal based on the reanalysis result and providing it to the user; means including an emotion engine that recognizes the user's emotional state and uses the emotional information for analysis; means for using an artificial intelligence module to analyze the user's overall needs and tendencies; means for providing optimal services and solutions based on the analysis results; and means for searching for other users with similar issues and needs and matching users with each other. This makes it possible to improve the operational efficiency of the logistics center, provide appropriate proposals, and build effective cooperative relationships with other logistics centers with similar issues.

[0861] "User" refers to an individual or company that uses the system to input business issues and receives analysis and proposals based on those issues.

[0862] "Means for accepting input of information" refers to the interface or device that allows users to input business tasks and basic information.

[0863] "Means for storing in a database" refers to a system or device for recording and storing information and emotional information input by a user in a database.

[0864] "Artificial intelligence module that performs initial analysis" refers to the artificial intelligence algorithms and software that analyze the user's current situation and issues based on information stored in the database.

[0865] "Means for providing the user with the results of the initial analysis" refers to a system or device for notifying and displaying the results of the initial analysis to the user.

[0866] "Artificial intelligence module that collects detailed information and performs reanalysis" refers to an artificial intelligence algorithm or software that performs reanalysis based on detailed tasks and additional information entered by the user.

[0867] "Means for generating and providing individual proposals to users" refers to a system or device that generates specific solutions or proposals that can be implemented by users based on the results of the reanalysis, and notifies and displays them to users.

[0868] "Emotion engine that recognizes emotional states and uses emotional information for analysis" refers to an algorithm or wireless communication device that recognizes a user's emotional state in real time and uses that information for analysis.

[0869] "Artificial intelligence module for analyzing overall needs and trends" refers to artificial intelligence algorithms and software that analyze information and emotional information collected from many users to identify common needs and trends.

[0870] "Means for providing optimal services and solutions" refers to systems and devices that propose and provide the most suitable services and solutions to users based on the analysis results.

[0871] "Means for searching for other users and matching users" refers to a system or device that finds other users with similar issues or needs and connects those users with each other.

[0872] This invention is a system for improving the operational efficiency of logistics centers, which uses an emotion engine and an artificial intelligence module to analyze users' business issues and make optimal proposals and matching. This system is composed of user terminals, a server, and various databases.

[0873] First, a user accesses the system using a terminal and registers an account. The user enters basic information about the logistics center and specific business tasks, and the terminal sends and stores this information in a database. At the same time, an emotion engine recognizes the user's input and emotional state during operation, and this information is also stored in the database.

[0874] The server then uses an artificial intelligence module to perform an initial analysis based on the stored information. During the initial analysis, the user's input information and emotional information are integrated and analyzed to generate proposals for optimizing and automating logistics schedules. These proposals are then sent to the user's device and displayed on a dashboard. The user can review these proposals and request further consultation if necessary.

[0875] When a detailed consultation is requested, the server provides the user with an interface for inputting additional information. The user uses this to input and submit additional specific issues or requests. The emotion engine continues to recognize the user's emotional state at this point.

[0876] The server then performs a re-analysis based on the collected detailed information and sentiment data. During the re-analysis, the AI ​​module generates specific solutions and proposals and provides them to the user. This allows the logistics center to develop actionable measures, such as more efficient delivery schedules and the introduction of automated systems.

[0877] Furthermore, the server analyzes the information and proposal data collected from users to extract overall needs and trends. Based on this, the server understands market trends and common needs of users and recommends optimal services and products. These recommendations are displayed on the dashboard, increasing user satisfaction.

[0878] Finally, the server searches for other users with similar issues and needs and matches them with each other. The emotion engine takes the user's emotional state into account when matching and suggests matches at the optimal time. This facilitates smooth cooperation between logistics centers and improves operational efficiency.

[0879] Hardware and software used

[0880] Hardware: User devices (smartphones, tablets, etc.), servers

[0881] Software: Flask (web framework), Pandas (data manipulation library), scikit-learn (machine learning library), emotion engine (Emotion Recognition)

[0882] Adding specific examples

[0883] As an example, suppose logistics center A registers with the system and the emotion engine recognizes that the user is in a high-stress state. An initial analysis generates a proposal to optimize the delivery schedule, and the user requests detailed consulting. A further analysis provides proposals for optimizing delivery routes and automating solutions. In addition, a collaboration with logistics center B, which has similar challenges, is suggested, realizing cost savings through joint deliveries.

[0884] Example prompt for a generative AI model:

[0885] "Generate proposals to optimize delivery schedules, taking into account the stress level of distribution center A."

[0886] In this way, the present invention provides a specific means for improving the operational efficiency of a logistics center.

[0887] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0888] Step 1:

[0889] A user accesses the system using a terminal and registers an account. The information entered is basic information about the logistics center and specific business tasks. The terminal sends this information to the database and stores it. The input data includes the company name, person in charge, contact information, task details, etc., and this information is recorded in the database.

[0890] Step 2:

[0891] The emotion engine recognizes the user's emotional state in real time as they input and stores that information in a database. At this stage, the emotion engine determines the user's stress level and emotional state from their input actions, facial expressions, voice, etc., and adds that information to the database.

[0892] Step 3:

[0893] The server performs an initial analysis based on the stored information. An AI module uses this information to analyze and generate proposals for optimizing logistics schedules and introducing automated systems. The user's input data (basic information, business issues) and emotional information are used as input data, which the AI ​​module analyzes to generate initial proposals. The generated proposals are sent to the terminal and displayed on the dashboard.

[0894] Step 4:

[0895] If the user checks the initial analysis results and requests detailed consulting, the server provides an interface for inputting additional information. The user inputs additional specific issues and requests, and the terminal sends the information to the server. The input data includes specific problems and requests for improvement.

[0896] Step 5:

[0897] The emotion engine recognizes the user's emotional state again and stores that information in the database. The user's emotional state is taken into account when reanalyzing, so the emotional information at the time of input is also added.

[0898] Step 6:

[0899] The server performs reanalysis based on the collected detailed information and emotional information. The artificial intelligence module analyzes the detailed information and emotional information and generates specific solutions and proposals. The input data (detailed information, additional tasks, emotional information) is processed and specific proposals are generated as a result of the reanalysis. The generated proposals are sent to the terminal and notified to the user.

[0900] Step 7:

[0901] The server then re-analyzes the collected information and proposal data to analyze overall needs and trends. An AI module analyzes large amounts of data to extract market trends and common needs. The input data includes past proposal data and user sentiment information, and the analysis outputs market trends and common needs.

[0902] Step 8:

[0903] The server generates proposals based on the analysis results to provide optimal services and solutions to users. It recommends optimal services and products and displays them on a dashboard. The input data includes analysis results and sentiment information, and proposals are generated based on this.

[0904] Step 9:

[0905] The server searches for other users with similar issues and needs and matches them with each other. An emotion engine takes into account the user's emotional state and suggests matching at the optimal time. Input data includes the user's business issues and emotional information, and the optimal match is selected based on this. Users can contact other logistics centers and work together.

[0906] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0907] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0908] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0909] [Third embodiment]

[0910] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0911] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0912] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0913] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0914] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0915] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0916] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0917] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0918] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0919] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0920] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0921] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0922] 1. User registration and information entry

[0923] The user accesses the system and registers an account. An interface for entering basic company information, job description, and specific tasks is displayed on the terminal. The user then enters the necessary information into the system and submits it.

[0924] The server receives the information entered by the user and stores it in a database. The stored information is used for analysis, so accurate and detailed information is required. After saving, the server sends a verification email to the user and activates the account.

[0925] 2. Initial analysis using AI

[0926] The server sends the saved user information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module compares the information with past databases and makes an initial assessment of the user's current situation and challenges.

[0927] The initial evaluation results are sent to the user's device and displayed on a dashboard. The user can review the results and request further consultation if necessary.

[0928] 3. Individual consulting proposals

[0929] When a user requests detailed consulting, the server provides an interface to initiate the collection of additional details, allowing the user to enter and submit more specific issues and requests.

[0930] The server then uses the details provided by the user to perform further analysis using the AI ​​module, which generates more specific solutions and suggestions and sends them back to the server in text format.

[0931] The generated suggestions are displayed on the user's dashboard, and the server provides detailed explanations and links to documentation for these suggestions, allowing the user to review the suggestions and receive guidance on actionable measures.

[0932] 4. Needs and Trends Analysis

[0933] The server then passes the information collected from users and the proposed data back to the AI ​​module, which analyzes the overall needs and trends. The AI ​​module then analyzes the large amount of data to extract current market trends and common user needs.

[0934] The analysis results are used to provide services and solutions that best suit the user's needs. Based on these results, the server recommends services and products that are suitable for the user and displays them on the dashboard.

[0935] 5. Matching users

[0936] The server searches for other users with similar challenges and needs and matches them with each other, potentially leading to joint projects and partnerships.

[0937] The server notifies users of the matching results and provides contact methods and partnership proposals to create business opportunities. Users can contact other companies and consider joint projects.

[0938] Specific examples

[0939] Example 1: Improving manufacturing efficiency

[0940] User A (a small to medium-sized manufacturing company) inputs the issue of improving the efficiency of its manufacturing process. The server sends this information to the AI ​​module, which performs an initial analysis. The AI ​​module then proposes measures to automate the production line and introduce an inventory management system, which the server provides to User A. User A then creates a specific implementation plan based on these proposals.

[0941] Example 2: Strengthening your marketing strategy

[0942] User B (an IT startup) is looking for a new marketing strategy. The server collects detailed information and reanalyzes it using the AI ​​module. The AI ​​module then suggests ways to expand the target market and strengthen the social media campaign, which the server then provides to User B. User B then takes specific steps to implement the proposed strategy.

[0943] Example 3: New business through user matching

[0944] User C (a logistics company) and User D (an e-commerce company) are both seeking to reduce logistics costs. Based on this information, the server matches the two parties and offers a joint delivery service proposal. User C and User D consider forming a partnership and actually start a joint project.

[0945] This system allows users to solve their own problems and discover new business opportunities. The entire system process is user-friendly and supports the growth and efficiency of companies.

[0946] The processing flow will be explained below.

[0947] Step 1:

[0948] A user accesses the consulting service system and enters detailed information such as company information, business details, and specific issues on the registration screen displayed on the terminal.

[0949] Step 2:

[0950] The server receives the information entered by the user and stores it in a database, after which the server sends a verification email to the user and activates the account.

[0951] Step 3:

[0952] The server sends the saved user information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module compares the information with a past database and makes an initial assessment of the user's current situation and challenges.

[0953] Step 4:

[0954] The AI ​​module generates initial analysis results and sends them back to the server, which receives them and displays them on the user's dashboard. The user can then view the initial analysis results.

[0955] Step 5:

[0956] When a user requests detailed consulting, the server provides the user with an interface for inputting detailed information, and the user inputs and submits additional specific issues and requests.

[0957] Step 6:

[0958] The server then uses the detailed information collected from the user to perform further analysis using the AI ​​module, which then generates specific solutions and suggestions and sends them back to the server.

[0959] Step 7:

[0960] The server displays the generated proposals on the user's dashboard, where the user can review the proposals and receive guidance on specific measures.

[0961] Step 8:

[0962] The server then passes the collected information and proposal data back to the AI ​​module, which analyzes overall needs and trends and extracts market trends and common user needs.

[0963] Step 9:

[0964] The server then recommends optimal services and solutions to the user based on the analysis results, and displays the recommendations on the user's dashboard with detailed explanations.

[0965] Step 10:

[0966] The server searches for other users with similar challenges and needs, matches users with each other, notifies users of the matching results, and provides contact methods and collaboration proposals to create business opportunities.

[0967] Step 11:

[0968] Users can contact other companies to discuss details of joint projects and partnerships, and the server provides functionality to support the necessary information sharing and exchange of materials.

[0969] This allows users to efficiently solve problems and explore new business opportunities.

[0970] Example 1

[0971] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0972] In today's business environment, companies need to respond quickly to diversifying challenges and needs. However, achieving this requires accurate information gathering, appropriate analysis, and specific proposals. Traditional methods make these processes time-consuming and labor-intensive, making it difficult to carry them out efficiently and effectively. Furthermore, it is not easy to find suitable partners for inter-company collaboration and matching. Therefore, an efficient system is needed to help companies solve their own challenges and discover new business opportunities.

[0973] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0974] In this invention, the server includes means for accepting information input from a user, means for saving the input information in a database, means for using an artificial intelligence module to perform an initial analysis based on the saved information, means for providing the initial analysis results to the user, means for using an artificial intelligence module to collect detailed information based on the initial analysis results and perform a re-analysis, means for generating individual proposals based on the re-analysis results and providing them to the user, means for using the artificial intelligence module to analyze the user's overall needs and trends, means for providing optimal services and solutions based on the analysis results, means for searching for other users who have similar issues or needs and matching users with each other, means for sending a verification email to the user and activating the account, means for receiving the user's detailed information, converting it into an appropriate format, and sending it to the artificial intelligence module, means for displaying the results of the re-analysis on the user's dashboard and providing related materials and links, and means for generating information recommended to the user based on the analysis results and displaying it on the dashboard.

[0975] This allows companies to quickly and accurately identify problems and receive solutions based on concrete proposals, while also promoting collaboration between companies and creating new business opportunities.

[0976] "User" refers to the entity that uses the system to input information and receive analysis results and suggestions.

[0977] "Means for accepting input of information" refers to the function of providing an interface that allows users to access the system and input company information and tasks.

[0978] "Database" refers to a storage or management system for structuring and storing received information.

[0979] An "artificial intelligence module" refers to a program with machine learning and data analysis capabilities that analyzes stored information and generates results.

[0980] "Initial analysis" refers to the initial information analysis process based on the basic information and issues provided by the user.

[0981] "Reanalysis" refers to the process of reanalyzing information based on more detailed information.

[0982] "Individual proposals" refer to specific solutions or action plans generated to address the user's specific challenges or requests.

[0983] "Needs and Trend Analysis" refers to the analytical process used to extract common issues and market trends based on data collected from users across the board.

[0984] "Verification Email" means the confirmation email sent to the email address provided by the User to activate the Account.

[0985] "Dashboard" refers to the web application interface that allows users to visually view analysis results and recommendations.

[0986] "Matching" refers to the process of searching for other users with similar challenges and needs and connecting suitable users with each other.

[0987] The present invention is a system for users to solve problems and discover new business opportunities. This system focuses on a series of processes in which users input information and receive analysis results and proposals.

[0988] User registration and information entry

[0989] Users access the system's registration page using a web browser on their device. They enter the required information through an interface that asks for company information, job description, and specific tasks, and then click the "Submit" button. The server receives this information as an HTTP request and stores it in a MySQL or PostgreSQL database. Once the information is saved, the server uses an email sending service such as SendGrid to send a verification email to the user. The user then clicks the link in the email to activate their account.

[0990] Initial analysis by AI

[0991] The server sends the saved user information to an AI analysis module such as TensorFlow or PyTorch in an appropriate format (JSON or CSV). The AI ​​module analyzes this information and compares it with past data to make an initial assessment of the user's current situation and challenges. Once the analysis is complete, the AI ​​module returns the results to the server, which displays them on the user's dashboard (built with React or Angular). The user can then view the initial assessment results on the dashboard using their device.

[0992] Individual consulting proposals

[0993] If the user requests detailed consulting, the server provides the user with an interface (such as an HTML form) to collect additional details. The user enters the details and clicks the "Submit" button again. The server receives this information and sends it back to the TensorFlow or PyTorch AI module in the appropriate format. The AI ​​module reanalyzes it and proposes a specific solution. The server displays this proposal on the user's dashboard, providing related materials and links. The user can then plan specific actions based on this.

[0994] Needs and trends analysis

[0995] The server performs large-scale data analysis on the information and proposal data collected from all users using big data processing platforms such as Hadoop and Spark. The AI ​​module uses this data to extract market trends and common user needs. The analysis results are returned to the server, which then uses this information to recommend optimal services and solutions to the user. This information is displayed on the user's dashboard.

[0996] Matching users

[0997] The server searches a database for other users with similar challenges and needs and matches them with suitable users. The matching results are provided to users via a dashboard and email notifications. Users can contact other companies based on the displayed information and consider joint projects. The server provides contact methods and partnership proposals, helping to create business opportunities.

[0998] Specific examples

[0999] (Example 1: Improving efficiency in manufacturing)

[1000] User A inputs the issue of improving the efficiency of the manufacturing process. The server sends this information to the AI ​​module, which performs an initial analysis. The AI ​​module then proposes measures such as automating the production line and introducing an inventory management system, which the server then provides to User A.

[1001] (Example 2: Strengthening marketing strategies)

[1002] User B wants to propose a new marketing strategy. The server collects detailed information and reanalyzes it with the AI ​​module. The AI ​​module then suggests expanding the target market or strengthening the social media campaign, which the server then provides to User B.

[1003] (Example 3: New business through user matching)

[1004] User C (a logistics company) and User D (an e-commerce company) are looking to reduce logistics costs. The server matches the two parties and offers a joint delivery service. User C and User D consider partnering and start a joint project.

[1005] Prompt Sentence Examples

[1006] "Please give us some specific suggestions on how to improve the efficiency of the manufacturing process."

[1007] "We're looking for suggestions for new marketing strategies."

[1008] "Please tell us some specific solutions to reduce logistics costs."

[1009] This system enables companies to quickly identify problems and find solutions, thereby improving operational efficiency and creating new business opportunities.

[1010] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1011] Step 1:

[1012] The user accesses the account registration page. Using a terminal, the user enters the specified URL into a web browser and arrives at the system's registration page. This page displays an interface for entering the required information. The input information includes company information, job description, specific challenges, etc.

[1013] Step 2:

[1014] The user enters information and submits it. The user enters the company name, business details, and the problem they want to solve from the terminal and clicks the "Submit" button. The entered data is sent as an HTTP request to the server.

[1015] Step 3:

[1016] The server receives the information and stores it in a database. The server analyzes the user's input information received as an HTTP request and stores it in a database (for example, MySQL or PostgreSQL). The stored data includes the user's company information, business details, and the problem they want to solve. The input is the information the user enters from their terminal, and the output is structured data stored in the database.

[1017] Step 4:

[1018] The server sends a verification email and the user activates the account. The server uses an email sending service (e.g. SendGrid) to send a verification email to the user's email address. The user checks their mailbox and clicks the verification link contained in the email to activate their account. The input is the user's email address stored by the server, and the output is the status of successful authentication.

[1019] Step 5:

[1020] The server sends user information to the AI ​​analysis module. The server converts the user information stored in the database into an appropriate format (e.g., JSON, CSV) and sends it to the AI ​​analysis module (e.g., TensorFlow or PyTorch) via an HTTP API. The input is the user information retrieved from the database, and the output is the completion status of transmission to the AI ​​analysis module.

[1021] Step 6:

[1022] The AI ​​module analyzes the information and generates results. The AI ​​module analyzes the received user information and compares it with past data to make an initial assessment of the user's current situation and issues. The input is the user information sent from the server, and the output is the analysis results.

[1023] Step 7:

[1024] The server displays the initial evaluation results on the user's dashboard. The server displays the initial evaluation results received from the AI ​​module on the user's dashboard (built with React or Angular). The user uses a terminal to check the initial evaluation results on the dashboard. The input is the initial evaluation result from the AI ​​module, and the output is the evaluation result displayed on the user's dashboard.

[1025] Step 8:

[1026] The user requests detailed consulting. The user clicks the "Request detailed consulting" button on the dashboard and proceeds to the interface for collecting additional information. The input is the user's request action, and the output is the display of the interface for entering detailed information.

[1027] Step 9:

[1028] The server provides an interface for the user to gather additional details. The server displays an interface (HTML form) to the user to gather additional details, including the specific problem in the business flow and the type of solution desired. The input is the server's interface display, and the output is preparation to accept user input.

[1029] Step 10:

[1030] User enters details and submits: The user enters details into a form and clicks the "Submit" button. The input is the details entered by the user at the terminal and the output is an HTTP request to the server.

[1031] Step 11:

[1032] The server uses the detailed information to perform re-analysis using the AI ​​module. The server converts the received detailed information into an appropriate format and sends it back to the AI ​​module. The AI ​​module then performs re-analysis and generates specific suggestions. The input is the detailed information sent by the user, and the output is the analysis result returned by the AI ​​module.

[1033] Step 12:

[1034] The server displays the generated suggestions on the user's dashboard. The server displays the suggestions received from the AI ​​module on the user's dashboard, and also provides related materials and links. The user uses their device to check the suggestions on the dashboard. The input is the analysis result of the AI ​​module, and the output is the suggestions displayed on the user's dashboard.

[1035] Step 13:

[1036] The server analyzes needs and trends based on the collected information and proposal data. The server analyzes all user data using Hadoop or Spark to extract market trends and common needs. The input is collected data from all users, and the output is the market trends and user needs analysis results.

[1037] Step 14:

[1038] The server provides the user with the optimal services and solutions based on the analysis results.The server then displays the optimal products and services on the user's dashboard based on the analysis results.The input is the analysis results, and the output is the recommended services and products that are displayed to the user.

[1039] Step 15:

[1040] The server searches for other users with similar issues and needs and performs matching. The server searches for similar users from the database and notifies the user of the matching results. The input is the user's issue information, and the output is the matching results for similar users.

[1041] Step 16:

[1042] Users contact other companies to consider joint projects. The server provides contact methods and collaboration proposals to help start joint projects. The input is the user's contact action, and the output is the provision of contact methods and collaboration proposals.

[1043] (Application example 1)

[1044] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1045] Modern factory operations require efficient management and optimization of production processes. However, manual information entry and management is time-consuming, making it difficult to make efficient decisions. It is also difficult to select appropriate solutions and services and to build a collaborative system between users. In addition, the lack of real-time feedback often delays productivity improvements.

[1046] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1047] In this invention, the server includes means for accepting information input from a user, means for storing the input information in a database, means for using an artificial intelligence module to perform an initial analysis based on the stored information, means for providing the results of the initial analysis to the user, means for using an artificial intelligence module to collect detailed information based on the results of the initial analysis and perform a reanalysis, means for generating individual proposals based on the results of the reanalysis and providing them to the user, means for using the artificial intelligence module to analyze the overall needs and trends of the user, means for providing optimal services and solutions based on the results of the analysis, means for searching for other users who have similar issues or needs and matching users with each other, means for providing an interface for managing information from multiple users in a unified manner, means for managing and optimizing automated factory equipment based on information input by the user, and means for providing real-time feedback to users to improve productivity. This enables efficient management and optimization of production processes, rapid decision-making, building a cooperative system among users, and improving productivity through real-time feedback.

[1048] "User" refers to an individual company or individual who uses the system.

[1049] "Means for accepting information input" refers to an interface that allows a user to input information into the system.

[1050] "Means for storing in a database" refers to a database system for storing and managing input information for a long period of time.

[1051] "Artificial intelligence module that performs initial analysis" refers to the AI ​​analysis engine that performs initial data analysis.

[1052] "Means for providing initial analysis results to a user" refers to means for displaying the analysis results on a user's dashboard or interface.

[1053] "Artificial intelligence module for reanalysis" refers to an AI analysis engine that reanalyzes data based on detailed information.

[1054] "Means for generating individual proposals and providing them to the user" refers to the part of the system that generates specific proposals based on the analysis results and notifies the user of them.

[1055] "Artificial intelligence module for analyzing overall needs and trends" refers to an AI engine for analyzing overall user data needs and market trends.

[1056] "Means for providing optimal services and solutions" refers to the part of the system that suggests the most suitable services and products to users based on the analysis results.

[1057] "Means for searching for other users with similar challenges and needs and matching users together" refers to the part of the system that connects users with common needs and challenges, providing opportunities for information sharing and collaborative projects.

[1058] "Interface for managing information from multiple users at once" refers to an interface for managing and displaying information obtained from a large number of users in a unified manner.

[1059] "Means for managing and optimizing automated factory equipment" refers to the system part for automating equipment within a factory and optimizing its operation.

[1060] "Means for providing real-time feedback" refers to the part of the system that immediately provides the user with feedback on analysis results and recommended actions.

[1061] MODE FOR CARRYING OUT THE INVENTION

[1062] This invention is a system that aims to improve the efficiency and optimization of production processes within factories. Specifically, it is a system that uses artificial intelligence (AI) to analyze information entered by users and propose appropriate solutions. This system consists of the following main components:

[1063] 1. User registration and information entry

[1064] First, the user accesses the system and registers an account. After registration, an interface is provided for entering basic factory information, current work content, and specific tasks, and the user then enters and submits the information required for the system. The entered information is saved in a database (e.g., MySQL) by the server. After saving, the server sends the user an authentication email and activates the account.

[1065] 2. Initial analysis using AI

[1066] The server sends the saved user information to an AI analysis module (e.g., TensorFlow, PyTorch) and begins initial analysis. The AI ​​module compares the information with past data and performs an initial assessment of the user's current situation and issues. The results of the initial assessment are notified to the user's device and displayed on a dashboard.

[1067] 3. Individual consulting proposals

[1068] When a user requests a detailed consultation, the server provides an interface to begin collecting additional details. The user then enters and submits a more specific challenge or request. The server then performs a re-analysis using the AI ​​module based on the details provided by the user. The generated proposals are displayed on the user's dashboard, and the server provides detailed explanations and links to resources related to these proposals.

[1069] 4. Factory equipment management and optimization

[1070] Based on the information entered by the user, the server manages and optimizes automated factory equipment, identifying bottlenecks on production lines within the factory and suggesting the introduction of automation tools or redistribution of tasks, thereby improving factory efficiency.

[1071] 5. Providing real-time feedback

[1072] Furthermore, the server provides users with real-time feedback to improve productivity. For example, if a decline in efficiency in a specific process is detected, the server immediately notifies the user of the problem and suggests improvement measures. The server also monitors the effectiveness of the implemented improvement measures in real time and provides the results as feedback to the user.

[1073] 6. Needs and Trend Analysis

[1074] The server then passes the information collected from users and the proposed data back to the AI ​​analysis module, which analyzes overall needs and trends. The AI ​​module analyzes large amounts of data to extract current market trends and common user needs. The analysis results are used to provide services and solutions that best suit the user's needs.

[1075] 7. User Matching

[1076] The server searches for other users with similar challenges and needs and matches them with each other, leading to the possibility of joint projects and partnerships. The server notifies users of the results of the matches and provides contact methods and partnership proposals to create business opportunities.

[1077] Specific examples

[1078] Example 1: Streamlining the manufacturing process

[1079] A factory inputs the issue of improving the efficiency of its production line into the system. The server sends this information to the AI ​​analysis module, which performs an initial analysis. As a result of the analysis, it identifies bottlenecks in specific processes and suggests ways to resolve them.

[1080] Example prompt sentence:

[1081] User: We are looking to improve the efficiency of our manufacturing line. Please suggest us what the bottlenecks are in our current production line and how to resolve them.

[1082] AI analysis:

[1083] We analyzed the current production line data and found that the bottleneck mainly occurs between process A and process B. Please try the following improvement suggestions.

[1084] 1. Introduction of automation tools for process A

[1085] 2. Introduction of task distribution and parallel processing in Process B

[1086] 3. Optimizing the overall inventory management system

[1087] By using the system in this way, each user can solve their own problems quickly and efficiently.

[1088] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1089] Application example processing steps

[1090] (Processing Steps)

[1091] Step 1:

[1092] Users access the system using a terminal and register an account. They then enter basic factory information, business operations, and specific tasks through an interface. The input data is sent to the server in JSON format.

[1093] Input: Basic information about the factory, business operations, specific issues

[1094] Output: User information data in JSON format

[1095] Step 2:

[1096] The server stores the received user information in a database, which is managed in a MySQL database and used for future analysis.

[1097] Input: User information data in JSON format

[1098] Output: User information stored in the database

[1099] Step 3:

[1100] The server sends the saved user information to an AI analysis module (TensorFlow, PyTorch) to begin initial analysis. The AI ​​module compares the information with past databases and makes an initial assessment of the user's current situation and challenges.

[1101] Input: User information data, historical database

[1102] Output: Initial analysis results

[1103] Step 4:

[1104] The server notifies the user of the analysis results and displays them on the dashboard, allowing the user to check the initial analysis results.

[1105] Input: Initial analysis results

[1106] Output: Analysis results displayed on a dashboard

[1107] Step 5:

[1108] When a user requests a detailed analysis, the server provides an interface to start collecting additional information. The user can then enter more specific issues or requests and submit them. The submitted data is then sent back to the server in JSON format.

[1109] Input: Additional details, specific issues or requests

[1110] Output: Additional information data in JSON format

[1111] Step 6:

[1112] The server then uses the detailed information provided by the user to perform further analysis using the AI ​​analysis module, which then generates more specific solutions and suggestions and sends them back to the server in text format.

[1113] Input: Additional information data

[1114] Output: Reanalysis results, specific solution proposals

[1115] Step 7:

[1116] The server displays the generated proposals on the user's dashboard, providing detailed explanations and links to related materials. The user can review the proposals and select actionable measures.

[1117] Input: Reanalysis results, specific solution proposals

[1118] Output: Detailed proposal information displayed in a dashboard

[1119] Step 8:

[1120] The server then passes the collected user data and proposal data back to the AI ​​analysis module to analyze overall needs and trends. The AI ​​module then extracts market trends and common needs and sends the results back to the server.

[1121] Input: User data, Proposal data

[1122] Output: Needs and trends analysis

[1123] Step 9:

[1124] Based on the analysis results, the server proposes optimal services and solutions to users, and displays related business solutions and new products on a dashboard.

[1125] Input: Needs and trends analysis results

[1126] Output: Recommended services and solutions

[1127] Step 10:

[1128] The server searches for other users with similar challenges and needs, matches them, notifies users of the matching results, and provides suggestions for collaborative projects.

[1129] Input: User data, analysis results

[1130] Output: Matching results, joint project proposals

[1131] Step 11:

[1132] Based on the information entered by the user, the server manages and optimizes automated factory equipment, identifying bottlenecks on production lines within the factory, deploying automation tools, redistributing tasks, and monitoring data in real time.

[1133] Input: Factory information, analysis results

[1134] Output: Optimized factory equipment management data

[1135] Step 12:

[1136] The server provides users with real-time feedback to improve productivity. For example, if a decrease in efficiency in a particular process is detected, the server immediately notifies the user of the problem and suggests a remedial measure.

[1137] Input: Real-time monitoring data

[1138] Output: Notification and suggestions for improvement

[1139] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1140] 1. User registration and information entry

[1141] A user accesses the system and registers an account. On the registration screen displayed on the terminal, the user enters basic company information, job description, and specific tasks. The emotion engine also monitors the user's input and actions during registration to recognize the user's emotional state. This information is also saved as data.

[1142] The server receives the information entered by the user and the emotional information recognized by the emotion engine and stores it in a database. The stored information is used for analysis, so accurate and detailed information is required. After saving, the server sends a verification email to the user and activates the account.

[1143] 2. Initial analysis using AI

[1144] The server sends the saved user information and emotional information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module takes into account the past database and the user's current emotional information to make an initial assessment of the user's current situation and challenges.

[1145] The initial evaluation results are sent to the user's device and displayed on a dashboard. The user can review the results and request further consultation if necessary.

[1146] 3. Individual consulting proposals

[1147] If the user requests detailed consultation, the server provides an interface for the user to enter detailed information. The user enters and submits additional specific issues or requests. The emotion engine continues to recognize the user's emotional state at this point.

[1148] The server then re-analyzes the AI ​​module based on the detailed information and emotional information collected from the user, and the AI ​​module takes the user's emotional state into account when generating specific solutions and suggestions.

[1149] The generated suggestions are displayed on the user's dashboard, and the server provides detailed explanations and links to resources about these suggestions. Depending on the user's emotional state, the suggestions may be adjusted or followed up. The user can review the suggestions and receive guidance on actionable measures.

[1150] 4. Needs and Trends Analysis

[1151] The server then passes the collected information and suggestion data, as well as emotional information, back to the AI ​​module, which analyzes the overall needs and trends. The AI ​​module then analyzes the large amount of data to extract current market trends, common user needs, and users' emotional responses.

[1152] The analysis results are used to provide services and solutions that best suit the user's needs. Based on these results, the server recommends services and products that are suitable for the user and displays them on a dashboard. Recommendations selected based on emotional information can increase user satisfaction.

[1153] 5. Matching users

[1154] The server searches for other users with similar issues and needs and matches them with each other. The emotion engine also takes the user's emotional state into account when matching, suggesting the best partner for building a better relationship.

[1155] The server notifies users of the matching results and provides contact and partnership suggestions to create business opportunities. Users can contact other companies and consider joint projects. Feedback from the emotion engine promotes better communication, making collaborations smoother.

[1156] Specific examples

[1157] Example 1: Improving manufacturing efficiency

[1158] User A (a small to medium-sized manufacturing company) inputs the issue of improving the efficiency of the manufacturing process. The emotion engine detects User A's stress level at the time of input and sends it to the AI ​​module. The server performs an initial analysis based on this information and proposes automating the production line and introducing an inventory management system. When explaining the proposal, the server uses language that reduces User A's stress. User A accepts the proposal with peace of mind and makes a specific implementation plan.

[1159] Example 2: Strengthening your marketing strategy

[1160] User B (an IT startup) is looking for a new marketing strategy. By providing detailed information along with emotional information, the server makes suggestions with the appropriate tone and content. The AI ​​module suggests expanding the target market or strengthening the social media campaign, and the server communicates this to User B, taking the emotional information into account. User B then takes concrete steps to implement the suggestions, improving the success rate.

[1161] Example 3: New business through user matching

[1162] User C (a logistics company) and User D (an e-commerce company) are both seeking to reduce logistics costs. The emotion engine monitors the emotional state of both parties when they use the system and matches them at the optimal time. Based on this information, the server provides proposals for joint delivery services. With the support of the emotion engine, User C and User D communicate smoothly and build a mutually satisfying cooperative relationship.

[1163] This system allows users to receive services that take their emotional state into consideration, enabling them to solve problems and explore new business opportunities efficiently. The entire system process is user-friendly, supporting the growth and efficiency of companies and increasing user satisfaction.

[1164] The processing flow will be explained below.

[1165] Step 1:

[1166] A user accesses the system and registers an account. On the registration screen displayed on the terminal, the user enters company information, job details, and specific tasks. The emotion engine monitors the user's input and operations and recognizes their emotional state.

[1167] Step 2:

[1168] The server receives the information entered by the user and the emotion information recognized by the emotion engine and stores them in a database. After saving, the server sends a verification email to the user to activate the account. The emotion information is also stored.

[1169] Step 3:

[1170] The server sends the saved user information and emotional information to the AI ​​analysis module, which then compares the user's emotional information with the past database and makes an initial assessment of the user's current situation and challenges.

[1171] Step 4:

[1172] The AI ​​module generates initial analysis results and sends them back to the server, which receives them and displays them on the user's dashboard, where the user can view them.

[1173] Step 5:

[1174] If the user requests detailed consultation, the server provides an interface for the user to enter detailed information. The user enters and submits additional specific issues or requests. The emotion engine continues to recognize the user's emotional state at this point.

[1175] Step 6:

[1176] The server then uses the AI ​​module to reanalyze the details and emotional information collected from the user. The AI ​​module then generates specific solutions and proposals and sends them back to the server. The proposals may be adjusted based on the emotional information.

[1177] Step 7:

[1178] The server displays the generated suggestions on the user's dashboard, providing detailed explanations and links to resources. The suggestions may be adjusted based on the user's emotional state. The user can review the suggestions and take action accordingly.

[1179] Step 8:

[1180] The server then passes the collected information, suggestion data, and emotional information from users back to the AI ​​module to analyze overall needs and trends. The AI ​​module then analyzes market trends, common user needs, and emotional responses.

[1181] Step 9:

[1182] The server then recommends optimal services and solutions to users based on the analysis results. The recommendations are adjusted taking into account the user's emotional information and displayed on the dashboard, thereby increasing user satisfaction.

[1183] Step 10:

[1184] The server searches for other users with similar issues and needs and matches them with each other. The emotion engine also takes the user's emotional state into account when matching and suggests the most suitable partner.

[1185] Step 11:

[1186] The server notifies users of the matching results and provides contact methods and partnership proposals to create business opportunities. Users can contact other companies and discuss details of joint projects. The server provides functions to support the necessary information sharing and document exchange.

[1187] This allows the entire system to provide flexible services that reflect the user's emotional state, supporting the growth and efficiency of companies.

[1188] Example 2

[1189] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1190] Conventional systems have difficulty providing optimal proposals and solutions that take into account the user's specific issues and emotional state. Furthermore, when matching users, the system does not consider their emotional state when selecting the optimal partner, which can lead to problems in communication and building cooperative relationships between users. This results in lower user satisfaction and makes it difficult to effectively solve problems and create business opportunities.

[1191] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1192] In this invention, the server includes a means for accepting information input from a user, a means for using an artificial intelligence module that performs an initial analysis based on the stored information and emotional information, and a means for using an artificial intelligence module that collects detailed information while recognizing the user's emotional state and performs reanalysis. This enables highly accurate suggestions that take the user's emotional state into consideration. The server also includes a means for searching for other users with similar issues or needs and matching users while taking their emotional state into consideration, enabling smooth communication between users and the establishment of effective cooperative relationships.

[1193] A "user" is someone who accesses the system, inputs information, or uses services.

[1194] The "means for accepting information input" is an interface that accepts input of company information, business details, tasks, etc. from the user.

[1195] "Storage means" is a function that records input information and recognized emotional information in a database.

[1196] "Initial analysis" is the process by which the artificial intelligence module evaluates the user's current situation and challenges based on stored information and emotional information.

[1197] The "artificial intelligence module" is a module that analyzes information collected from users and makes proposals and evaluations for solving problems.

[1198] "Emotional state" refers to the mental and emotional state of a user when entering information or using a system.

[1199] The "emotion engine" is an engine that monitors the user's input and actions, and recognizes and evaluates their emotional state.

[1200] "Detailed information" is information about specific issues or requests that are additionally entered by the user.

[1201] "Reanalysis" is the process in which the artificial intelligence module analyzes again based on detailed information and emotional information after the initial analysis.

[1202] "Individual proposals" are problem-solving proposals or solutions specific to the user that are generated based on the results of the reanalysis.

[1203] "Needs and Trends Analysis" is the process of using all the information collected from users to extract common needs and market trends.

[1204] "Means for providing services and solutions" refers to an interface that suggests optimal services and products to users based on the results of analysis.

[1205] "Matching" is the process of searching for users with similar challenges and needs and selecting the most suitable partner, taking into account their emotional state.

[1206] "Business opportunities" are opportunities for new collaborations and projects that arise from matching users together.

[1207] The "means for providing contact methods and business partnership proposals" is a function that supports users in contacting each other and considering business partnerships.

[1208] The system of the present invention accepts information input from users and analyzes and proposes based on that information. A distinctive feature of this system is that it takes into account the emotional state of the user to make optimal proposals and match users with each other.

[1209] 1. User registration and information entry

[1210] First, users access the system and register an account. A registration screen is displayed on the terminal, allowing them to enter basic company information, job duties, and specific tasks. Specifically, information such as the company name, address, and name of the person in charge is entered. The emotion engine also monitors the user's behavior (e.g., typing speed, mouse movement) while entering data and recognizes their emotional state. All of this information is stored in a database. The server then sends the user a verification email and activates the account.

[1211] 2. Initial analysis using AI

[1212] The server sends the user information and emotional information stored in the database to the AI ​​analysis module, which begins the initial analysis. This AI module takes into account the past database and the user's current emotional information to make an initial assessment of the current situation and issues. The results of this initial assessment are notified to the user's device and displayed on a dashboard. The user can review the results and request detailed consulting if necessary.

[1213] 3. Individual consulting proposals

[1214] When a user requests detailed consulting, the server provides an interface for entering detailed information. The user can then enter additional specific issues or requests and submit them. The emotion engine continues to recognize the user's emotional state. The server then sends the collected details and emotional information to the AI ​​analysis module for further analysis. The AI ​​module generates specific solutions and proposals taking the user's emotional state into account. These proposals are displayed on the user's dashboard, and the server provides detailed explanations and links to materials.

[1215] 4. Needs and Trends Analysis

[1216] The server then passes the collected information, proposal data, and emotional information from users back to the AI ​​analysis module, which analyzes overall needs and trends. This AI module analyzes large amounts of data to extract market trends, common user needs, and emotional responses. Based on the results of this analysis, it proposes optimal services and solutions to users. These results are displayed on the user's dashboard.

[1217] 5. User Matching

[1218] The server searches for other users with similar challenges and needs and matches them with each other. The emotion engine also takes into account the user's emotional state to suggest the best partner for building a better relationship. The server notifies the user of the matching results and offers contact methods and partnership suggestions. The user then contacts other companies and considers joint projects. During this process, feedback from the emotion engine promotes smooth communication.

[1219] Specific examples

[1220] Example 1: Improving manufacturing efficiency

[1221] User A (a small to medium-sized manufacturing company) inputs the issue of improving the efficiency of the manufacturing process. The emotion engine detects User A's stress level at the time of input and sends it to the AI ​​module. The server performs an initial analysis based on this information and proposes automating the production line and introducing an inventory management system. When explaining the proposal, the server uses language that reduces User A's stress. User A accepts the proposal with peace of mind and makes a specific implementation plan.

[1222] Example 2: Strengthening your marketing strategy

[1223] User B (an IT startup) is looking for a new marketing strategy. By providing detailed information along with emotional information, the server makes suggestions with the appropriate tone and content. The AI ​​module suggests expanding the target market or strengthening the social media campaign, and the server communicates this to User B, taking the emotional information into account. User B then takes concrete steps to implement the suggestions, improving the success rate.

[1224] Example 3: New business through user matching

[1225] User C (a logistics company) and User D (an e-commerce company) are both seeking to reduce logistics costs. The emotion engine monitors the emotional state of both parties when they use the system and matches them at the optimal time. Based on this information, the server provides proposals for joint delivery services. With the support of the emotion engine, User C and User D communicate smoothly and build a mutually satisfying cooperative relationship.

[1226] Prompt Sentence Examples

[1227] "Enter your manufacturing process efficiency challenge. The emotion engine will detect your stress level and provide you with appropriate suggestions."

[1228] "Please provide us with detailed information and sentiment information on strengthening your marketing strategy. We will suggest strengthening your social media campaign."

[1229] "Consider a joint project with a user looking to reduce logistics costs. We will support you with our emotion engine to ensure smooth communication."

[1230] As described above, the present invention is a system that takes into account the information and emotional state provided by the user and provides optimal suggestions and matching, thereby efficiently resolving user problems and creating business opportunities, thereby improving user satisfaction.

[1231] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1232] Step 1:

[1233] A user accesses the system and displays the account registration screen.

[1234] Specific operation: The user accesses the system's web page or dedicated application from their own device and opens the account registration screen, where an interface for registering the user's information (e.g., company name, address, contact name) is displayed.

[1235] Input: Basic information entered by the user, such as company information and contact name

[1236] Output: Displaying the registration screen and receiving the entered information

[1237] Step 2:

[1238] The terminal accepts the user's information input, and the emotion engine monitors the input behavior (typing speed, mouse movement).

[1239] Specific actions: As users enter company information, job descriptions, and specific tasks, the emotion engine records their input actions in the background.

[1240] Input: Information entered by the user and behavioral data recorded by the emotion engine

[1241] Output: Collection of input information and operational data

[1242] Step 3:

[1243] The device sends the input information and emotion information to the server, which receives it and stores it in a database.

[1244] Specific operation: The device sends the information entered by the user and the behavioral data collected by the emotion engine to the server in one batch. The server immediately records this data in a database upon receiving it.

[1245] Input: User input and behavior data

[1246] Output: Information and behavioral data recorded in a database

[1247] Step 4:

[1248] The server sends a verification email to the user and activates the account.

[1249] Specific operation: The server generates an authentication email based on the user information stored in the database and sends it to the user's registered email address. The user can activate their account by clicking the link contained in this email.

[1250] Input: User information in the database

[1251] Output: Verification email sent to the user's email address

[1252] Step 5:

[1253] The server sends the saved user information and emotional information to the AI ​​analysis module, which begins the initial analysis.

[1254] Specific operation: The server extracts user information and emotional information stored in the database and sends it to the AI ​​analysis module, which then performs an initial assessment of the user's current situation and challenges based on the data sent.

[1255] Input: User information and emotion information in the database

[1256] Output: Generates initial analysis results

[1257] Step 6:

[1258] The AI ​​analysis module generates the initial analysis results, which the server notifies the user's device.

[1259] How it works: The AI ​​analysis module processes the user's information and emotional data to generate an initial evaluation result, which is then sent to the user's device via the server and displayed on the dashboard.

[1260] Input: Stored user information and emotion information

[1261] Output: Initial analysis results displayed on the user's terminal.

[1262] Step 7:

[1263] If the user requests detailed consultation, the server provides an interface for entering detailed information.

[1264] Specific operation: If the user checks the initial analysis results and requests further consultation, the server will provide a new input interface where the user can enter more specific issues and requests.

[1265] Input: Initial analysis results and requests for further information

[1266] Output: Display detailed information input interface

[1267] Step 8:

[1268] The device collects the user's detailed information, and the emotion engine recognizes the user's emotional state. The server receives this information and sends it to the AI ​​analysis module for further analysis.

[1269] Specific actions: When the user enters detailed issues or requests, the emotion engine continues to monitor the user's actions and record their emotional state. The device then sends these details and emotional state data to the server, which then sends them back to the AI ​​analysis module for re-analysis.

[1270] Input: User details and emotional state data

[1271] Output: Generate reanalysis results

[1272] Step 9:

[1273] The AI ​​analysis module then reanalyzes the data and generates personalized suggestions, which the server displays on the user's device, along with detailed explanations and links to resources.

[1274] How it works: The AI ​​analysis module reanalyzes the detailed information and emotional state data to generate personalized suggestions for the user. The generated suggestions are sent to the user's device via the server and displayed on the dashboard. At the same time, the server also provides detailed explanations of the suggestions and links to related materials.

[1275] Input: User details and emotional state data

[1276] Output: Reanalysis results and suggestions displayed on the user's device

[1277] Step 10:

[1278] The server passes the information collected from the user, suggestion data, and emotional information back to the AI ​​analysis module to analyze overall needs and trends.

[1279] Specific operation: The server sends all collected data to an AI analysis module, which analyzes common needs, market trends, and emotional responses of multiple users.

[1280] Input: All information and sentiment collected from the user

[1281] Output: Analysis of needs and trends

[1282] Step 11:

[1283] Based on the results of an analysis of needs and trends, the server suggests the most suitable services and products for the user and displays them on the dashboard.

[1284] Specific operation: Based on the analysis results obtained from the AI ​​analysis module, the server selects services and products (e.g., the latest inventory management tools, optimal marketing strategies) that are suitable for the user's detailed data and displays them on the user's dashboard.

[1285] Input: Analysis of needs and trends

[1286] Output: Service and product suggestions displayed on the user's dashboard

[1287] Step 12:

[1288] The server searches for other users with similar issues and needs and matches them using an emotion engine.

[1289] How it works: The server searches its database to identify other users with similar challenges and needs, and uses an emotion engine to select the best match and match users together.

[1290] Input: User issues, needs, and emotional information

[1291] Output: Generates matching results

[1292] Step 13:

[1293] The server notifies the user of the matching results and provides contact methods and partnership suggestions.

[1294] Specific operation: After receiving the matching results, the server sends them to the user's device and provides contact methods and specific collaboration proposals, including contact information and proposed joint projects.

[1295] Input: Matching results

[1296] Output: Proposal displayed on the user's device and contact information

[1297] These are the processing steps of this system. This system allows users to receive optimal suggestions that take their emotional state into consideration and match users with each other, leading to problem solving and the creation of new business opportunities.

[1298] (Application example 2)

[1299] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1300] In traditional logistics center operations, optimizing delivery schedules and streamlining business processes are extremely important. However, many logistics centers lack systems that can provide optimal proposals that take into account data analysis and emotional states to resolve these issues. This makes it difficult to operate efficiently and reduce logistics costs. Furthermore, it is difficult to build effective collaborative relationships with other logistics centers that face similar challenges, so a comprehensive solution to improve overall operational efficiency is needed.

[1301] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for accepting information input from a user; means for saving the input information in a database; means for using an artificial intelligence module to perform an initial analysis based on the saved information; means for providing the initial analysis result to the user; means for using an artificial intelligence module to collect detailed information based on the initial analysis result and perform a reanalysis; means for generating an individual proposal based on the reanalysis result and providing it to the user; means including an emotion engine that recognizes the user's emotional state and uses the emotional information for analysis; means for using an artificial intelligence module to analyze the user's overall needs and tendencies; means for providing optimal services and solutions based on the analysis results; and means for searching for other users with similar issues and needs and matching users with each other. This makes it possible to improve the operational efficiency of the logistics center, provide appropriate proposals, and build effective cooperative relationships with other logistics centers with similar issues.

[1302] "User" refers to an individual or company that uses the system to input business issues and receives analysis and proposals based on those issues.

[1303] "Means for accepting input of information" refers to the interface or device that allows users to input business tasks and basic information.

[1304] "Means for storing in a database" refers to a system or device for recording and storing information and emotional information input by a user in a database.

[1305] "Artificial intelligence module that performs initial analysis" refers to the artificial intelligence algorithms and software that analyze the user's current situation and issues based on information stored in the database.

[1306] "Means for providing the user with the results of the initial analysis" refers to a system or device for notifying and displaying the results of the initial analysis to the user.

[1307] "Artificial intelligence module that collects detailed information and performs reanalysis" refers to an artificial intelligence algorithm or software that performs reanalysis based on detailed tasks and additional information entered by the user.

[1308] "Means for generating and providing individual proposals to users" refers to a system or device that generates specific solutions or proposals that can be implemented by users based on the results of the reanalysis, and notifies and displays them to users.

[1309] "Emotion engine that recognizes emotional states and uses emotional information for analysis" refers to an algorithm or wireless communication device that recognizes a user's emotional state in real time and uses that information for analysis.

[1310] "Artificial intelligence module for analyzing overall needs and trends" refers to artificial intelligence algorithms and software that analyze information and emotional information collected from many users to identify common needs and trends.

[1311] "Means for providing optimal services and solutions" refers to systems and devices that propose and provide the most suitable services and solutions to users based on the analysis results.

[1312] "Means for searching for other users and matching users" refers to a system or device that finds other users with similar issues or needs and connects those users with each other.

[1313] This invention is a system for improving the operational efficiency of logistics centers, which uses an emotion engine and an artificial intelligence module to analyze users' business issues and make optimal proposals and matching. This system is composed of user terminals, a server, and various databases.

[1314] First, a user accesses the system using a terminal and registers an account. The user enters basic information about the logistics center and specific business tasks, and the terminal sends and stores this information in a database. At the same time, an emotion engine recognizes the user's input and emotional state during operation, and this information is also stored in the database.

[1315] The server then uses an artificial intelligence module to perform an initial analysis based on the stored information. During the initial analysis, the user's input information and emotional information are integrated and analyzed to generate proposals for optimizing and automating logistics schedules. These proposals are then sent to the user's device and displayed on a dashboard. The user can review these proposals and request further consultation if necessary.

[1316] When a detailed consultation is requested, the server provides the user with an interface for inputting additional information. The user uses this to input and submit additional specific issues or requests. The emotion engine continues to recognize the user's emotional state at this point.

[1317] The server then performs a re-analysis based on the collected detailed information and sentiment data. During the re-analysis, the AI ​​module generates specific solutions and proposals and provides them to the user. This allows the logistics center to develop actionable measures, such as more efficient delivery schedules and the introduction of automated systems.

[1318] Furthermore, the server analyzes the information and proposal data collected from users to extract overall needs and trends. Based on this, the server understands market trends and common needs of users and recommends optimal services and products. These recommendations are displayed on the dashboard, increasing user satisfaction.

[1319] Finally, the server searches for other users with similar issues and needs and matches them with each other. The emotion engine takes the user's emotional state into account when matching and suggests matches at the optimal time. This facilitates smooth cooperation between logistics centers and improves operational efficiency.

[1320] Hardware and software used

[1321] Hardware: User devices (smartphones, tablets, etc.), servers

[1322] Software: Flask (web framework), Pandas (data manipulation library), scikit-learn (machine learning library), emotion engine (Emotion Recognition)

[1323] Adding specific examples

[1324] As an example, suppose logistics center A registers with the system and the emotion engine recognizes that the user is in a high-stress state. An initial analysis generates a proposal to optimize the delivery schedule, and the user requests detailed consulting. A further analysis provides proposals for optimizing delivery routes and automating solutions. In addition, a collaboration with logistics center B, which has similar challenges, is suggested, realizing cost savings through joint deliveries.

[1325] Example prompt for a generative AI model:

[1326] "Generate proposals to optimize delivery schedules, taking into account the stress level of distribution center A."

[1327] In this way, the present invention provides a specific means for improving the operational efficiency of a logistics center.

[1328] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1329] Step 1:

[1330] A user accesses the system using a terminal and registers an account. The information entered is basic information about the logistics center and specific business tasks. The terminal sends this information to the database and stores it. The input data includes the company name, person in charge, contact information, task details, etc., and this information is recorded in the database.

[1331] Step 2:

[1332] The emotion engine recognizes the user's emotional state in real time as they input and stores that information in a database. At this stage, the emotion engine determines the user's stress level and emotional state from their input actions, facial expressions, voice, etc., and adds that information to the database.

[1333] Step 3:

[1334] The server performs an initial analysis based on the stored information. An AI module uses this information to analyze and generate proposals for optimizing logistics schedules and introducing automated systems. The user's input data (basic information, business issues) and emotional information are used as input data, which the AI ​​module analyzes to generate initial proposals. The generated proposals are sent to the terminal and displayed on the dashboard.

[1335] Step 4:

[1336] If the user checks the initial analysis results and requests detailed consulting, the server provides an interface for inputting additional information. The user inputs additional specific issues and requests, and the terminal sends the information to the server. The input data includes specific problems and requests for improvement.

[1337] Step 5:

[1338] The emotion engine recognizes the user's emotional state again and stores that information in the database. The user's emotional state is taken into account when reanalyzing, so the emotional information at the time of input is also added.

[1339] Step 6:

[1340] The server performs reanalysis based on the collected detailed information and emotional information. The artificial intelligence module analyzes the detailed information and emotional information and generates specific solutions and proposals. The input data (detailed information, additional tasks, emotional information) is processed and specific proposals are generated as a result of the reanalysis. The generated proposals are sent to the terminal and notified to the user.

[1341] Step 7:

[1342] The server then re-analyzes the collected information and proposal data to analyze overall needs and trends. An AI module analyzes large amounts of data to extract market trends and common needs. The input data includes past proposal data and user sentiment information, and the analysis outputs market trends and common needs.

[1343] Step 8:

[1344] The server generates proposals based on the analysis results to provide optimal services and solutions to users. It recommends optimal services and products and displays them on a dashboard. The input data includes analysis results and sentiment information, and proposals are generated based on this.

[1345] Step 9:

[1346] The server searches for other users with similar issues and needs and matches them with each other. An emotion engine takes into account the user's emotional state and suggests matching at the optimal time. Input data includes the user's business issues and emotional information, and the optimal match is selected based on this. Users can contact other logistics centers and work together.

[1347] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1348] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1349] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1350] [Fourth embodiment]

[1351] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1352] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1353] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1354] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1355] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1356] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1357] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1358] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1359] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1360] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1361] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1362] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1363] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1364] 1. User registration and information entry

[1365] The user accesses the system and registers an account. An interface for entering basic company information, job description, and specific tasks is displayed on the terminal. The user then enters the necessary information into the system and submits it.

[1366] The server receives the information entered by the user and stores it in a database. The stored information is used for analysis, so accurate and detailed information is required. After saving, the server sends a verification email to the user and activates the account.

[1367] 2. Initial analysis using AI

[1368] The server sends the saved user information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module compares the information with past databases and makes an initial assessment of the user's current situation and challenges.

[1369] The initial evaluation results are sent to the user's device and displayed on a dashboard. The user can review the results and request further consultation if necessary.

[1370] 3. Individual consulting proposals

[1371] When a user requests detailed consulting, the server provides an interface to initiate the collection of additional details, allowing the user to enter and submit more specific issues and requests.

[1372] The server then uses the details provided by the user to perform further analysis using the AI ​​module, which generates more specific solutions and suggestions and sends them back to the server in text format.

[1373] The generated suggestions are displayed on the user's dashboard, and the server provides detailed explanations and links to documentation for these suggestions, allowing the user to review the suggestions and receive guidance on actionable measures.

[1374] 4. Needs and Trends Analysis

[1375] The server then passes the information collected from users and the proposed data back to the AI ​​module, which analyzes the overall needs and trends. The AI ​​module then analyzes the large amount of data to extract current market trends and common user needs.

[1376] The analysis results are used to provide services and solutions that best suit the user's needs. Based on these results, the server recommends services and products that are suitable for the user and displays them on the dashboard.

[1377] 5. Matching users

[1378] The server searches for other users with similar challenges and needs and matches them with each other, potentially leading to joint projects and partnerships.

[1379] The server notifies users of the matching results and provides contact methods and partnership proposals to create business opportunities. Users can contact other companies and consider joint projects.

[1380] Specific examples

[1381] Example 1: Improving manufacturing efficiency

[1382] User A (a small to medium-sized manufacturing company) inputs the issue of improving the efficiency of its manufacturing process. The server sends this information to the AI ​​module, which performs an initial analysis. The AI ​​module then proposes measures to automate the production line and introduce an inventory management system, which the server provides to User A. User A then creates a specific implementation plan based on these proposals.

[1383] Example 2: Strengthening your marketing strategy

[1384] User B (an IT startup) is looking for a new marketing strategy. The server collects detailed information and reanalyzes it using the AI ​​module. The AI ​​module then suggests ways to expand the target market and strengthen the social media campaign, which the server then provides to User B. User B then takes specific steps to implement the proposed strategy.

[1385] Example 3: New business through user matching

[1386] User C (a logistics company) and User D (an e-commerce company) are both seeking to reduce logistics costs. Based on this information, the server matches the two parties and offers a joint delivery service proposal. User C and User D consider forming a partnership and actually start a joint project.

[1387] This system allows users to solve their own problems and discover new business opportunities. The entire system process is user-friendly and supports the growth and efficiency of companies.

[1388] The processing flow will be explained below.

[1389] Step 1:

[1390] A user accesses the consulting service system and enters detailed information such as company information, business details, and specific issues on the registration screen displayed on the terminal.

[1391] Step 2:

[1392] The server receives the information entered by the user and stores it in a database, after which the server sends a verification email to the user and activates the account.

[1393] Step 3:

[1394] The server sends the saved user information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module compares the information with a past database and makes an initial assessment of the user's current situation and challenges.

[1395] Step 4:

[1396] The AI ​​module generates initial analysis results and sends them back to the server, which receives them and displays them on the user's dashboard. The user can then view the initial analysis results.

[1397] Step 5:

[1398] When a user requests detailed consulting, the server provides the user with an interface for inputting detailed information, and the user inputs and submits additional specific issues and requests.

[1399] Step 6:

[1400] The server then uses the detailed information collected from the user to perform further analysis using the AI ​​module, which then generates specific solutions and suggestions and sends them back to the server.

[1401] Step 7:

[1402] The server displays the generated proposals on the user's dashboard, where the user can review the proposals and receive guidance on specific measures.

[1403] Step 8:

[1404] The server then passes the collected information and proposal data back to the AI ​​module, which analyzes overall needs and trends and extracts market trends and common user needs.

[1405] Step 9:

[1406] The server then recommends optimal services and solutions to the user based on the analysis results, and displays the recommendations on the user's dashboard with detailed explanations.

[1407] Step 10:

[1408] The server searches for other users with similar challenges and needs, matches users with each other, notifies users of the matching results, and provides contact methods and collaboration proposals to create business opportunities.

[1409] Step 11:

[1410] Users can contact other companies to discuss details of joint projects and partnerships, and the server provides functionality to support the necessary information sharing and exchange of materials.

[1411] This allows users to efficiently solve problems and explore new business opportunities.

[1412] Example 1

[1413] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1414] In today's business environment, companies need to respond quickly to diversifying challenges and needs. However, achieving this requires accurate information gathering, appropriate analysis, and specific proposals. Traditional methods make these processes time-consuming and labor-intensive, making it difficult to carry them out efficiently and effectively. Furthermore, it is not easy to find suitable partners for inter-company collaboration and matching. Therefore, an efficient system is needed to help companies solve their own challenges and discover new business opportunities.

[1415] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1416] In this invention, the server includes means for accepting information input from a user, means for saving the input information in a database, means for using an artificial intelligence module to perform an initial analysis based on the saved information, means for providing the initial analysis results to the user, means for using an artificial intelligence module to collect detailed information based on the initial analysis results and perform a re-analysis, means for generating individual proposals based on the re-analysis results and providing them to the user, means for using the artificial intelligence module to analyze the user's overall needs and trends, means for providing optimal services and solutions based on the analysis results, means for searching for other users who have similar issues or needs and matching users with each other, means for sending a verification email to the user and activating the account, means for receiving the user's detailed information, converting it into an appropriate format, and sending it to the artificial intelligence module, means for displaying the results of the re-analysis on the user's dashboard and providing related materials and links, and means for generating information recommended to the user based on the analysis results and displaying it on the dashboard.

[1417] This allows companies to quickly and accurately identify problems and receive solutions based on concrete proposals, while also promoting collaboration between companies and creating new business opportunities.

[1418] "User" refers to the entity that uses the system to input information and receive analysis results and suggestions.

[1419] "Means for accepting input of information" refers to the function of providing an interface that allows users to access the system and input company information and tasks.

[1420] "Database" refers to a storage or management system for structuring and storing received information.

[1421] An "artificial intelligence module" refers to a program with machine learning and data analysis capabilities that analyzes stored information and generates results.

[1422] "Initial analysis" refers to the initial information analysis process based on the basic information and issues provided by the user.

[1423] "Reanalysis" refers to the process of reanalyzing information based on more detailed information.

[1424] "Individual proposals" refer to specific solutions or action plans generated to address the user's specific challenges or requests.

[1425] "Needs and Trend Analysis" refers to the analytical process used to extract common issues and market trends based on data collected from users across the board.

[1426] "Verification Email" means the confirmation email sent to the email address provided by the User to activate the Account.

[1427] "Dashboard" refers to the web application interface that allows users to visually view analysis results and recommendations.

[1428] "Matching" refers to the process of searching for other users with similar challenges and needs and connecting suitable users with each other.

[1429] The present invention is a system for users to solve problems and discover new business opportunities. This system focuses on a series of processes in which users input information and receive analysis results and proposals.

[1430] User registration and information entry

[1431] Users access the system's registration page using a web browser on their device. They enter the required information through an interface that asks for company information, job description, and specific tasks, and then click the "Submit" button. The server receives this information as an HTTP request and stores it in a MySQL or PostgreSQL database. Once the information is saved, the server uses an email sending service such as SendGrid to send a verification email to the user. The user then clicks the link in the email to activate their account.

[1432] Initial analysis by AI

[1433] The server sends the saved user information to an AI analysis module such as TensorFlow or PyTorch in an appropriate format (JSON or CSV). The AI ​​module analyzes this information and compares it with past data to make an initial assessment of the user's current situation and challenges. Once the analysis is complete, the AI ​​module returns the results to the server, which displays them on the user's dashboard (built with React or Angular). The user can then view the initial assessment results on the dashboard using their device.

[1434] Individual consulting proposals

[1435] If the user requests detailed consulting, the server provides the user with an interface (such as an HTML form) to collect additional details. The user enters the details and clicks the "Submit" button again. The server receives this information and sends it back to the TensorFlow or PyTorch AI module in the appropriate format. The AI ​​module reanalyzes it and proposes a specific solution. The server displays this proposal on the user's dashboard, providing related materials and links. The user can then plan specific actions based on this.

[1436] Needs and trends analysis

[1437] The server performs large-scale data analysis on the information and proposal data collected from all users using big data processing platforms such as Hadoop and Spark. The AI ​​module uses this data to extract market trends and common user needs. The analysis results are returned to the server, which then uses this information to recommend optimal services and solutions to the user. This information is displayed on the user's dashboard.

[1438] Matching users

[1439] The server searches a database for other users with similar challenges and needs and matches them with suitable users. The matching results are provided to users via a dashboard and email notifications. Users can contact other companies based on the displayed information and consider joint projects. The server provides contact methods and partnership proposals, helping to create business opportunities.

[1440] Specific examples

[1441] (Example 1: Improving efficiency in manufacturing)

[1442] User A inputs the issue of improving the efficiency of the manufacturing process. The server sends this information to the AI ​​module, which performs an initial analysis. The AI ​​module then proposes measures such as automating the production line and introducing an inventory management system, which the server then provides to User A.

[1443] (Example 2: Strengthening marketing strategies)

[1444] User B wants to propose a new marketing strategy. The server collects detailed information and reanalyzes it with the AI ​​module. The AI ​​module then suggests expanding the target market or strengthening the social media campaign, which the server then provides to User B.

[1445] (Example 3: New business through user matching)

[1446] User C (a logistics company) and User D (an e-commerce company) are looking to reduce logistics costs. The server matches the two parties and offers a joint delivery service. User C and User D consider partnering and start a joint project.

[1447] Prompt Sentence Examples

[1448] "Please give us some specific suggestions on how to improve the efficiency of the manufacturing process."

[1449] "We're looking for suggestions for new marketing strategies."

[1450] "Please tell us some specific solutions to reduce logistics costs."

[1451] This system enables companies to quickly identify problems and find solutions, thereby improving operational efficiency and creating new business opportunities.

[1452] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1453] Step 1:

[1454] The user accesses the account registration page. Using a terminal, the user enters the specified URL into a web browser and arrives at the system's registration page. This page displays an interface for entering the required information. The input information includes company information, job description, specific challenges, etc.

[1455] Step 2:

[1456] The user enters information and submits it. The user enters the company name, business details, and the problem they want to solve from the terminal and clicks the "Submit" button. The entered data is sent as an HTTP request to the server.

[1457] Step 3:

[1458] The server receives the information and stores it in a database. The server analyzes the user's input information received as an HTTP request and stores it in a database (for example, MySQL or PostgreSQL). The stored data includes the user's company information, business details, and the problem they want to solve. The input is the information the user enters from their terminal, and the output is structured data stored in the database.

[1459] Step 4:

[1460] The server sends a verification email and the user activates the account. The server uses an email sending service (e.g. SendGrid) to send a verification email to the user's email address. The user checks their mailbox and clicks the verification link contained in the email to activate their account. The input is the user's email address stored by the server, and the output is the status of successful authentication.

[1461] Step 5:

[1462] The server sends user information to the AI ​​analysis module. The server converts the user information stored in the database into an appropriate format (e.g., JSON, CSV) and sends it to the AI ​​analysis module (e.g., TensorFlow or PyTorch) via an HTTP API. The input is the user information retrieved from the database, and the output is the completion status of transmission to the AI ​​analysis module.

[1463] Step 6:

[1464] The AI ​​module analyzes the information and generates results. The AI ​​module analyzes the received user information and compares it with past data to make an initial assessment of the user's current situation and issues. The input is the user information sent from the server, and the output is the analysis results.

[1465] Step 7:

[1466] The server displays the initial evaluation results on the user's dashboard. The server displays the initial evaluation results received from the AI ​​module on the user's dashboard (built with React or Angular). The user uses a terminal to check the initial evaluation results on the dashboard. The input is the initial evaluation result from the AI ​​module, and the output is the evaluation result displayed on the user's dashboard.

[1467] Step 8:

[1468] The user requests detailed consulting. The user clicks the "Request detailed consulting" button on the dashboard and proceeds to the interface for collecting additional information. The input is the user's request action, and the output is the display of the interface for entering detailed information.

[1469] Step 9:

[1470] The server provides an interface for the user to gather additional details. The server displays an interface (HTML form) to the user to gather additional details, including the specific problem in the business flow and the type of solution desired. The input is the server's interface display, and the output is preparation to accept user input.

[1471] Step 10:

[1472] User enters details and submits: The user enters details into a form and clicks the "Submit" button. The input is the details entered by the user at the terminal and the output is an HTTP request to the server.

[1473] Step 11:

[1474] The server uses the detailed information to perform re-analysis using the AI ​​module. The server converts the received detailed information into an appropriate format and sends it back to the AI ​​module. The AI ​​module then performs re-analysis and generates specific suggestions. The input is the detailed information sent by the user, and the output is the analysis result returned by the AI ​​module.

[1475] Step 12:

[1476] The server displays the generated suggestions on the user's dashboard. The server displays the suggestions received from the AI ​​module on the user's dashboard, and also provides related materials and links. The user uses their device to check the suggestions on the dashboard. The input is the analysis result of the AI ​​module, and the output is the suggestions displayed on the user's dashboard.

[1477] Step 13:

[1478] The server analyzes needs and trends based on the collected information and proposal data. The server analyzes all user data using Hadoop or Spark to extract market trends and common needs. The input is collected data from all users, and the output is the market trends and user needs analysis results.

[1479] Step 14:

[1480] The server provides the user with the optimal services and solutions based on the analysis results.The server then displays the optimal products and services on the user's dashboard based on the analysis results.The input is the analysis results, and the output is the recommended services and products that are displayed to the user.

[1481] Step 15:

[1482] The server searches for other users with similar issues and needs and performs matching. The server searches for similar users from the database and notifies the user of the matching results. The input is the user's issue information, and the output is the matching results for similar users.

[1483] Step 16:

[1484] Users contact other companies to consider joint projects. The server provides contact methods and collaboration proposals to help start joint projects. The input is the user's contact action, and the output is the provision of contact methods and collaboration proposals.

[1485] (Application example 1)

[1486] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1487] Modern factory operations require efficient management and optimization of production processes. However, manual information entry and management is time-consuming, making it difficult to make efficient decisions. It is also difficult to select appropriate solutions and services and to build a collaborative system between users. In addition, the lack of real-time feedback often delays productivity improvements.

[1488] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1489] In this invention, the server includes means for accepting information input from a user, means for storing the input information in a database, means for using an artificial intelligence module to perform an initial analysis based on the stored information, means for providing the results of the initial analysis to the user, means for using an artificial intelligence module to collect detailed information based on the results of the initial analysis and perform a reanalysis, means for generating individual proposals based on the results of the reanalysis and providing them to the user, means for using the artificial intelligence module to analyze the overall needs and trends of the user, means for providing optimal services and solutions based on the results of the analysis, means for searching for other users who have similar issues or needs and matching users with each other, means for providing an interface for managing information from multiple users in a unified manner, means for managing and optimizing automated factory equipment based on information input by the user, and means for providing real-time feedback to users to improve productivity. This enables efficient management and optimization of production processes, rapid decision-making, building a cooperative system among users, and improving productivity through real-time feedback.

[1490] "User" refers to an individual company or individual who uses the system.

[1491] "Means for accepting information input" refers to an interface that allows a user to input information into the system.

[1492] "Means for storing in a database" refers to a database system for storing and managing input information for a long period of time.

[1493] "Artificial intelligence module that performs initial analysis" refers to the AI ​​analysis engine that performs initial data analysis.

[1494] "Means for providing initial analysis results to a user" refers to means for displaying the analysis results on a user's dashboard or interface.

[1495] "Artificial intelligence module for reanalysis" refers to an AI analysis engine that reanalyzes data based on detailed information.

[1496] "Means for generating individual proposals and providing them to the user" refers to the part of the system that generates specific proposals based on the analysis results and notifies the user of them.

[1497] "Artificial intelligence module for analyzing overall needs and trends" refers to an AI engine for analyzing overall user data needs and market trends.

[1498] "Means for providing optimal services and solutions" refers to the part of the system that suggests the most suitable services and products to users based on the analysis results.

[1499] "Means for searching for other users with similar challenges and needs and matching users together" refers to the part of the system that connects users with common needs and challenges, providing opportunities for information sharing and collaborative projects.

[1500] "Interface for managing information from multiple users at once" refers to an interface for managing and displaying information obtained from a large number of users in a unified manner.

[1501] "Means for managing and optimizing automated factory equipment" refers to the system part for automating equipment within a factory and optimizing its operation.

[1502] "Means for providing real-time feedback" refers to the part of the system that immediately provides the user with feedback on analysis results and recommended actions.

[1503] MODE FOR CARRYING OUT THE INVENTION

[1504] This invention is a system that aims to improve the efficiency and optimization of production processes within factories. Specifically, it is a system that uses artificial intelligence (AI) to analyze information entered by users and propose appropriate solutions. This system consists of the following main components:

[1505] 1. User registration and information entry

[1506] First, the user accesses the system and registers an account. After registration, an interface is provided for entering basic factory information, current work content, and specific tasks, and the user then enters and submits the information required for the system. The entered information is saved in a database (e.g., MySQL) by the server. After saving, the server sends the user an authentication email and activates the account.

[1507] 2. Initial analysis using AI

[1508] The server sends the saved user information to an AI analysis module (e.g., TensorFlow, PyTorch) and begins initial analysis. The AI ​​module compares the information with past data and performs an initial assessment of the user's current situation and issues. The results of the initial assessment are notified to the user's device and displayed on a dashboard.

[1509] 3. Individual consulting proposals

[1510] When a user requests a detailed consultation, the server provides an interface to begin collecting additional details. The user then enters and submits a more specific challenge or request. The server then performs a re-analysis using the AI ​​module based on the details provided by the user. The generated proposals are displayed on the user's dashboard, and the server provides detailed explanations and links to resources related to these proposals.

[1511] 4. Factory equipment management and optimization

[1512] Based on the information entered by the user, the server manages and optimizes automated factory equipment, identifying bottlenecks on production lines within the factory and suggesting the introduction of automation tools or redistribution of tasks, thereby improving factory efficiency.

[1513] 5. Providing real-time feedback

[1514] Furthermore, the server provides users with real-time feedback to improve productivity. For example, if a decline in efficiency in a specific process is detected, the server immediately notifies the user of the problem and suggests improvement measures. The server also monitors the effectiveness of the implemented improvement measures in real time and provides the results as feedback to the user.

[1515] 6. Needs and Trend Analysis

[1516] The server then passes the information collected from users and the proposed data back to the AI ​​analysis module, which analyzes overall needs and trends. The AI ​​module analyzes large amounts of data to extract current market trends and common user needs. The analysis results are used to provide services and solutions that best suit the user's needs.

[1517] 7. User Matching

[1518] The server searches for other users with similar challenges and needs and matches them with each other, leading to the possibility of joint projects and partnerships. The server notifies users of the results of the matches and provides contact methods and partnership proposals to create business opportunities.

[1519] Specific examples

[1520] Example 1: Streamlining the manufacturing process

[1521] A factory inputs the issue of improving the efficiency of its production line into the system. The server sends this information to the AI ​​analysis module, which performs an initial analysis. As a result of the analysis, it identifies bottlenecks in specific processes and suggests ways to resolve them.

[1522] Example prompt sentence:

[1523] User: We are looking to improve the efficiency of our manufacturing line. Please suggest us what the bottlenecks are in our current production line and how to resolve them.

[1524] AI analysis:

[1525] We analyzed the current production line data and found that the bottleneck mainly occurs between process A and process B. Please try the following improvement suggestions.

[1526] 1. Introduction of automation tools for process A

[1527] 2. Introduction of task distribution and parallel processing in Process B

[1528] 3. Optimizing the overall inventory management system

[1529] By using the system in this way, each user can solve their own problems quickly and efficiently.

[1530] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1531] Application example processing steps

[1532] (Processing Steps)

[1533] Step 1:

[1534] Users access the system using a terminal and register an account. They then enter basic factory information, business operations, and specific tasks through an interface. The input data is sent to the server in JSON format.

[1535] Input: Basic information about the factory, business operations, specific issues

[1536] Output: User information data in JSON format

[1537] Step 2:

[1538] The server stores the received user information in a database, which is managed in a MySQL database and used for future analysis.

[1539] Input: User information data in JSON format

[1540] Output: User information stored in the database

[1541] Step 3:

[1542] The server sends the saved user information to an AI analysis module (TensorFlow, PyTorch) to begin initial analysis. The AI ​​module compares the information with past databases and makes an initial assessment of the user's current situation and challenges.

[1543] Input: User information data, historical database

[1544] Output: Initial analysis results

[1545] Step 4:

[1546] The server notifies the user of the analysis results and displays them on the dashboard, allowing the user to check the initial analysis results.

[1547] Input: Initial analysis results

[1548] Output: Analysis results displayed on a dashboard

[1549] Step 5:

[1550] When a user requests a detailed analysis, the server provides an interface to start collecting additional information. The user can then enter more specific issues or requests and submit them. The submitted data is then sent back to the server in JSON format.

[1551] Input: Additional details, specific issues or requests

[1552] Output: Additional information data in JSON format

[1553] Step 6:

[1554] The server then uses the detailed information provided by the user to perform further analysis using the AI ​​analysis module, which then generates more specific solutions and suggestions and sends them back to the server in text format.

[1555] Input: Additional information data

[1556] Output: Reanalysis results, specific solution proposals

[1557] Step 7:

[1558] The server displays the generated proposals on the user's dashboard, providing detailed explanations and links to related materials. The user can review the proposals and select actionable measures.

[1559] Input: Reanalysis results, specific solution proposals

[1560] Output: Detailed proposal information displayed in a dashboard

[1561] Step 8:

[1562] The server then passes the collected user data and proposal data back to the AI ​​analysis module to analyze overall needs and trends. The AI ​​module then extracts market trends and common needs and sends the results back to the server.

[1563] Input: User data, Proposal data

[1564] Output: Needs and trends analysis

[1565] Step 9:

[1566] Based on the analysis results, the server proposes optimal services and solutions to users, and displays related business solutions and new products on a dashboard.

[1567] Input: Needs and trends analysis results

[1568] Output: Recommended services and solutions

[1569] Step 10:

[1570] The server searches for other users with similar challenges and needs, matches them, notifies users of the matching results, and provides suggestions for collaborative projects.

[1571] Input: User data, analysis results

[1572] Output: Matching results, joint project proposals

[1573] Step 11:

[1574] Based on the information entered by the user, the server manages and optimizes automated factory equipment, identifying bottlenecks on production lines within the factory, deploying automation tools, redistributing tasks, and monitoring data in real time.

[1575] Input: Factory information, analysis results

[1576] Output: Optimized factory equipment management data

[1577] Step 12:

[1578] The server provides users with real-time feedback to improve productivity. For example, if a decrease in efficiency in a particular process is detected, the server immediately notifies the user of the problem and suggests a remedial measure.

[1579] Input: Real-time monitoring data

[1580] Output: Notification and suggestions for improvement

[1581] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1582] 1. User registration and information entry

[1583] A user accesses the system and registers an account. On the registration screen displayed on the terminal, the user enters basic company information, job description, and specific tasks. The emotion engine also monitors the user's input and actions during registration to recognize the user's emotional state. This information is also saved as data.

[1584] The server receives the information entered by the user and the emotional information recognized by the emotion engine and stores it in a database. The stored information is used for analysis, so accurate and detailed information is required. After saving, the server sends a verification email to the user and activates the account.

[1585] 2. Initial analysis using AI

[1586] The server sends the saved user information and emotional information to the AI ​​analysis module, which then performs an initial analysis. The AI ​​module takes into account the past database and the user's current emotional information to make an initial assessment of the user's current situation and challenges.

[1587] The initial evaluation results are sent to the user's device and displayed on a dashboard. The user can review the results and request further consultation if necessary.

[1588] 3. Individual consulting proposals

[1589] If the user requests detailed consultation, the server provides an interface for the user to enter detailed information. The user enters and submits additional specific issues or requests. The emotion engine continues to recognize the user's emotional state at this point.

[1590] The server then re-analyzes the AI ​​module based on the detailed information and emotional information collected from the user, and the AI ​​module takes the user's emotional state into account when generating specific solutions and suggestions.

[1591] The generated suggestions are displayed on the user's dashboard, and the server provides detailed explanations and links to resources about these suggestions. Depending on the user's emotional state, the suggestions may be adjusted or followed up. The user can review the suggestions and receive guidance on actionable measures.

[1592] 4. Needs and Trends Analysis

[1593] The server then passes the collected information and suggestion data, as well as emotional information, back to the AI ​​module, which analyzes the overall needs and trends. The AI ​​module then analyzes the large amount of data to extract current market trends, common user needs, and users' emotional responses.

[1594] The analysis results are used to provide services and solutions that best suit the user's needs. Based on these results, the server recommends services and products that are suitable for the user and displays them on a dashboard. Recommendations selected based on emotional information can increase user satisfaction.

[1595] 5. Matching users

[1596] The server searches for other users with similar issues and needs and matches them with each other. The emotion engine also takes the user's emotional state into account when matching, suggesting the best partner for building a better relationship.

[1597] The server notifies users of the matching results and provides contact and partnership suggestions to create business opportunities. Users can contact other companies and consider joint projects. Feedback from the emotion engine promotes better communication, making collaborations smoother.

[1598] Specific examples

[1599] Example 1: Improving manufacturing efficiency

[1600] User A (a small to medium-sized manufacturing company) inputs the issue of improving the efficiency of the manufacturing process. The emotion engine detects User A's stress level at the time of input and sends it to the AI ​​module. The server performs an initial analysis based on this information and proposes automating the production line and introducing an inventory management system. When explaining the proposal, the server uses language that reduces User A's stress. User A accepts the proposal with peace of mind and makes a specific implementation plan.

[1601] Example 2: Strengthening your marketing strategy

[1602] User B (an IT startup) is looking for a new marketing strategy. By providing detailed information along with emotional information, the server makes suggestions with the appropriate tone and content. The AI ​​module suggests expanding the target market or strengthening the social media campaign, and the server communicates this to User B, taking the emotional information into account. User B then takes concrete steps to implement the suggestions, improving the success rate.

[1603] Example 3: New business through user matching

[1604] User C (a logistics company) and User D (an e-commerce company) are both seeking to reduce logistics costs. The emotion engine monitors the emotional state of both parties when they use the system and matches them at the optimal time. Based on this information, the server provides proposals for joint delivery services. With the support of the emotion engine, User C and User D communicate smoothly and build a mutually satisfying cooperative relationship.

[1605] This system allows users to receive services that take their emotional state into consideration, enabling them to solve problems and explore new business opportunities efficiently. The entire system process is user-friendly, supporting the growth and efficiency of companies and increasing user satisfaction.

[1606] The processing flow will be explained below.

[1607] Step 1:

[1608] A user accesses the system and registers an account. On the registration screen displayed on the terminal, the user enters company information, job details, and specific tasks. The emotion engine monitors the user's input and operations and recognizes their emotional state.

[1609] Step 2:

[1610] The server receives the information entered by the user and the emotion information recognized by the emotion engine and stores them in a database. After saving, the server sends a verification email to the user to activate the account. The emotion information is also stored.

[1611] Step 3:

[1612] The server sends the saved user information and emotional information to the AI ​​analysis module, which then compares the user's emotional information with the past database and makes an initial assessment of the user's current situatio...

Claims

1. means for accepting input of information from a user; means for storing the input information in a database; using an artificial intelligence module to perform an initial analysis based on the stored information; means for providing the initial analysis result to a user; a means for using an artificial intelligence module to collect detailed information based on the results of the initial analysis and perform a reanalysis; means for generating and providing individualized proposals to a user based on the reanalysis results; means for using an artificial intelligence module to analyze the overall needs and trends of users; A means for providing optimal services and solutions based on the results of said analysis; A system that includes a means to search for other users with similar challenges or needs and match users with each other.

2. The system of claim 1 further comprising means for collecting detailed information and additional issues from the user.

3. The system according to claim 1 , further comprising means for providing a match result between the users and notifying the users of a proposal for creating business opportunities.

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