System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting requests through interaction with a user; means for analyzing the collected information and automatically generating a request for proposal; means for publishing and collecting the automatically generated request for proposal to a plurality of providers and collecting quotes and proposals from the providers; and means for presenting the collected quotes and proposals to the user and selecting an optimal provider.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] Many small and medium-sized enterprises and individuals face the challenge of not knowing how to create business systems and tools, and are unable to even create a request for proposal (RFP). They also face the problem of not knowing which provider to ask for development. This makes it difficult to improve business efficiency and introduce advanced business management systems, resulting in a decline in competitiveness. Furthermore, even for problems that can be solved with simple tools, they do not know how to solve them on their own, and are forced to continue working inefficiently. This invention aims to solve these problems. [Means for solving the problem]

[0005] The present invention provides a system that includes an interaction means for collecting requirements through dialogue with a user, a generation means for automatically generating a request for proposal by analyzing the collected information, a publishing and collection means for publishing the automatically generated request for proposal to a plurality of providers and collecting quotations and proposals from the providers, and a display and selection means for presenting the collected quotations and proposals to the user and allowing the user to select the most suitable provider. Furthermore, if the collected information is relatively simple, the system further includes a procedure presentation means for presenting a procedure for the user to create a system or tool themselves. By also including a correction means for checking and correcting the request for proposal generated based on the user's requirements, the system enables the user to create a request that meets the specific requirements desired and request development.

[0006] A "user" is a person or organization that desires the development of a system or tool and inputs its requirements into the system.

[0007] "Interaction means" refers to the functionality of tools and systems for gathering user requirements through interaction with the user.

[0008] A "Request for Proposal (RFP)" is a document that describes user requests and specific requirements, and is used to request development proposals and estimates from developers and providers.

[0009] "Generation means" refers to functions or tools that automatically create a request for proposal based on collected information.

[0010] "Disclosure and collection means" refers to a function or system for disclosing the generated request for proposal to multiple providers and collecting estimates and proposals from the providers.

[0011] "Display and selection means" refers to the functions and tools that allow the user to present the collected quotes and proposals and select the most suitable provider.

[0012] "Procedure presentation means" refers to a function or system that presents a procedure for users to create a system or tool themselves when the collected information is simple.

[0013] "Modification means" refers to a function or system that allows a user to review the generated request for proposal and enter corrections or additional information as necessary.

[0014] "Provider" refers to an individual or organization that has the technology to develop the system or tool desired by the user and provides estimates and proposals. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] This invention relates to a system that extracts requirements from users who wish to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotations and proposals. This invention enables improved business efficiency and advanced business management.

[0037] System Overview

[0038] This system has the following main functions:

[0039] 1. Means of interaction

[0040] 2. Generation means

[0041] 3. Disclosure and collection methods

[0042] 4. Display and Selection Means

[0043] 5. Procedure Presentation Methods

[0044] 6. Remedies

[0045] Explanation of program processing

[0046] 1. Means of interaction

[0047] A user accesses the system and creates a new project. The server launches an AI model to begin a dialogue with the user. The AI ​​generates an initial question, asking the user, "What kind of system or tool do you want?" The user then inputs a specific request (e.g., "Inventory management system").

[0048] 2. Generation means

[0049] The server analyzes the collected information and continues to ask questions to gather more detailed information. For example, if a user requests an "inventory management system," they will include specific requirements such as "real-time inventory management," "barcode scanning support," and "integrated inventory management for multiple warehouses." Based on this information, the AI ​​automatically fills in the information in a request for proposal (RFP) template.

[0050] 3. Disclosure and collection methods

[0051] The generated RFP is registered in the system by the server and notified to multiple providers. The providers view the RFP and submit quotations and proposals. The server collects these quotations and proposals and prepares them for presentation to the user.

[0052] 4. Display and Selection Means

[0053] The collected quotes and proposals are presented to the user via the terminal. The user compares and considers multiple proposals and selects the most suitable provider. Once the selection is complete, the server notifies the selected provider and proceeds with the contract procedure.

[0054] 5. Procedure Presentation Methods

[0055] If the collected information is relatively simple, the server's AI will determine that "this requirement can be met with a simple tool." In this case, the server will present specific steps and support the user in creating the tool themselves. For example, if automating expense reimbursement sheets, it will provide step-by-step instructions on how to use Excel and macros.

[0056] 6. Remedies

[0057] The user can review the generated RFP draft and enter any necessary corrections or additions. The server receives this information and updates the RFP.

[0058] Specific examples

[0059] Example 1: Inventory management system requirements

[0060] User: "I want to create an inventory management system."

[0061] Server: "Would you like specific features in that inventory management system?"

[0062] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[0063] Server: "Okay. Is there anything else you need?"

[0064] User: "I want to manage inventory across multiple warehouses."

[0065] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[0066] User: Checks the RFP draft and presses the publish button.

[0067] Server: Posts the RFP to providers and collects proposals.

[0068] Example 2: Support for creating simple tools

[0069] User: "I want to automate my expense reports."

[0070] Server: "What features do you need?"

[0071] User: "I'd like it to automatically extract the amount from a photo of a receipt and enter it into a spreadsheet."

[0072] Server: "That functionality can be achieved using an Excel macro. Please follow these steps:"

[0073] The server displays the steps for creating an Excel macro, and the user follows the steps to create the program.

[0074] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. It also supports the creation of simple tools to help small and medium-sized enterprises and individuals improve their business efficiency.

[0075] The processing flow will be explained below.

[0076] Step 1:

[0077] A user accesses the platform using a terminal and logs in. The user selects to create a new project and enters the project name and basic requirements (e.g., "Inventory Management System").

[0078] Step 2:

[0079] The server launches the AI ​​model and displays an initial question to the user, such as "What kind of system or tool do you want?"

[0080] Step 3:

[0081] The user inputs a specific request. For example, "I want to create an inventory management system."

[0082] Step 4:

[0083] The server's AI generates additional questions to gather more information based on the user's input, such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?"

[0084] Step 5:

[0085] The user answers additional questions, for example, "I'd like real-time inventory updates and support for barcode scanners."

[0086] Step 6:

[0087] The server's AI analyzes the collected information and automatically fills in the request for proposal (RFP) template with information such as "real-time inventory management," "barcode compatibility," and "integrated inventory management for multiple warehouses."

[0088] Step 7:

[0089] The generated RFP draft is displayed on the terminal for the user to review, and the user can enter corrections or additional requirements as necessary.

[0090] Step 8:

[0091] The user finally checks the RFP draft and presses the publish button, which makes the RFP available to providers.

[0092] Step 9:

[0093] The server notifies multiple providers of the RFP and collects quotations and proposals from them.

[0094] Step 10:

[0095] The server organizes the collected estimates and proposals and presents them to the user via the terminal.

[0096] Step 11:

[0097] The user compares multiple quotes and proposals displayed and selects the most suitable provider.

[0098] Step 12:

[0099] The server notifies the selected provider and initiates the contract process.

[0100] Step 13:

[0101] If the collected information is relatively simple, the server's AI will determine that the requirements can be met with a simple tool and provide specific instructions, such as instructions for automating expense reimbursement sheets.

[0102] Step 14:

[0103] It supports users to create simple tools by following the steps. For example, it guides users step by step through the steps to create an Excel macro.

[0104] Example 1

[0105] 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."

[0106] In conventional system development, it takes a great deal of time and effort for users to clarify their requirements and convert them into a request for proposal (RFP). Collecting quotes and proposals from multiple suppliers and selecting the most suitable provider is also complicated. Furthermore, creating simple tools on your own presents high technical hurdles, making it difficult for small and medium-sized enterprises and individuals to easily improve business efficiency.

[0107] 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.

[0108] In this invention, the server includes an interactive means, a generating means, a publishing and collecting means, a display and selecting means, and a procedure presenting means. This allows a user wishing to develop a system or tool to interactively collect the necessary information, automatically generate a request for proposal, and present it to multiple suppliers. Furthermore, when creating a simple tool, specific procedures are presented, improving work efficiency.

[0109] "Interaction means" refers to the interactive interface used by the user to access the system and to gather information between the user and the server.

[0110] "Generation means" refers to the functionality for analyzing collected information and automatically generating a request for proposal (RFP).

[0111] "Publication and collection means" refers to a function for publishing an automatically generated request for proposal to multiple suppliers and collecting quotations and proposals from the suppliers.

[0112] "Display and selection means" refers to a function that presents collected quotes and proposals to the user and enables the user to select the most suitable supplier.

[0113] The "procedure presentation means" refers to a function for presenting specific procedures and providing support when a user wishes to create a simple tool.

[0114] The "modification means" refers to a function for checking and modifying a request for proposal generated based on a user's request.

[0115] This system extracts requirements when a user wishes to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple suppliers to collect quotations and proposals. It also supports the creation of simple tools, improving business efficiency and providing advanced business management.

[0116] System Overview

[0117] This system has the following main functions:

[0118] Interaction methods

[0119] A user accesses the system and creates a new project. The server launches the generative AI model and begins a dialogue with the user. First, the server generates a prompt asking, "What kind of system or tool do you want?" and displays it to the user via the terminal. The user then inputs their specific request, for example, "Inventory management system."

[0120] generation means

[0121] The server analyzes the information provided by the user and automatically generates questions to gather more detailed information. For example, it checks specific requirements such as "real-time inventory management," "barcode scanning support," and "integrated inventory management across multiple warehouses." Based on this information, the server automatically inputs the information into a request for proposal (RFP) template.

[0122] Publication and collection methods

[0123] The generated RFP is registered in the system by the server and notified to multiple suppliers. Suppliers can view the RFP and submit quotations and proposals. The server collects, organizes, and stores these proposals.

[0124] Display and Selection Means

[0125] The collected quotes and proposals are presented to the user via the terminal. The user compares multiple proposals and selects the most suitable supplier. After the selection, the server notifies the selected supplier and proceeds with the contract procedure.

[0126] Procedure presentation method

[0127] If a user wants to create a simple tool, the server's generative AI model will provide specific instructions, such as "How to automate an expense report sheet using an Excel macro," and help the user create the tool by following the instructions.

[0128] Correction means

[0129] The user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server updates the RFP with this information.

[0130] Specific examples

[0131] Example 1: Inventory management system requirements

[0132] 1. User: "I want to create an inventory management system."

[0133] 2. Server: "Would you like specific features in that inventory management system?"

[0134] 3. User: "I want to update inventory in real time. I also want it to be compatible with barcode scanners."

[0135] 4. Server: "Okay. Is there anything else you need?"

[0136] 5. User: "I want to manage inventory across multiple warehouses."

[0137] 6. Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[0138] 7. User: Checks the RFP draft and presses the publish button.

[0139] 8. Server: Notifies suppliers of the RFP and collects proposals.

[0140] Example 2: Support for creating simple tools

[0141] 1. User: "I want to automate my expense report."

[0142] 2. Server: "What features do you need?"

[0143] 3. User: "I'd like the amount to be automatically extracted from a photo of a receipt and entered into a spreadsheet."

[0144] 4. Server: "That functionality can be achieved using an Excel macro. Please follow the steps below."

[0145] 5. The server displays the step-by-step instructions for creating an Excel macro, and the user follows them to write the program.

[0146] This system allows users to easily request the development of systems and tools, and efficiently collect and compare quotes and proposals from multiple suppliers.It also provides specific procedures for creating simple tools, helping to improve the efficiency of work for small and medium-sized enterprises and individuals.

[0147] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0148] Step 1: Create a project and start interacting

[0149] A user accesses the system and clicks the "Create a new project" button. This input is sent to the server. The server receives this action and launches a generative AI model. The server generates the initial prompt, "What kind of system or tool do you want?", and displays it to the user via the terminal. The user's response (e.g., inventory management system) is received as input.

[0150] Step 2: Refine your requirements

[0151] The server analyzes the user's responses and uses a generative AI model to create follow-up questions to gather more detailed information. For example, detailed questions such as "Do you manage inventory in real time?" or "Do you support barcode scanning?" are generated and displayed to the user via their device. The user answers these questions, and the answers are sent to the server as input data. The server accumulates this data and collects more detailed information for the RFP template.

[0152] Step 3: Generate an RFP

[0153] The server automatically generates an RFP draft based on the collected information. The input data is the collected user's request details, which are analyzed and automatically embedded in a request for proposal template. The generated RFP draft is displayed to the user via their terminal. The user checks the contents and makes corrections as necessary. This confirmation and correction information is also sent to the server as input data.

[0154] Step 4: Publish the RFP

[0155] The user checks the generated RFP draft and clicks the "Publish" button. This input causes the server to register the RFP in the system and send notifications to multiple suppliers. Suppliers view the RFP and send quotations and proposals to the server. These proposals are collected, organized, and stored by the server.

[0156] Step 5: Collect and display suggestions

[0157] The server organizes the collected estimates and proposals, presents them to the user as a list via the terminal, and provides the user with the information they need to compare proposals. The user then compares the proposals from each provider and enters the information to select the most suitable provider.

[0158] Step 6: Selection and notification of the best proposal

[0159] The user selects the best proposal and clicks a button to confirm the selection. Upon receiving this input, the server notifies the selected provider and initiates the contract process. At the same time, it notifies other suppliers of the selection result.

[0160] Step 7: Support for creating simple tools

[0161] When a user wants to create a simple tool (e.g., to automate expense reports), the generative AI model on the server presents specific steps to the user. For example, the generative AI model creates a step-by-step guide to "How to automate expense reports using Excel macros" and displays it to the user via their device. The user then follows the steps to create the tool.

[0162] The above is the flow of processing steps and specific operations in this system.

[0163] (Application example 1)

[0164] 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."

[0165] In today's world, when a user wishes to customize an autonomous vehicle, it is difficult to efficiently gather specific requirements and create an appropriate request for proposal (RFP). Conventional systems require users to consider detailed technical specifications themselves, which requires a lot of time and effort. Furthermore, the process of efficiently publishing the created RFP to multiple providers and collecting quotes and proposals is also cumbersome. Furthermore, even when simple customization is possible, there is a lack of support for users to understand and execute the procedure.

[0166] 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.

[0167] In this invention, the server includes a conversation means for collecting requirements through a dialogue with the user, a generation means for automatically generating a request for proposal by analyzing the collected information, a publishing and collection means for publishing the automatically generated request for proposal to multiple providers and collecting quotations and proposals from the providers, a display and selection means for presenting the collected quotations and proposals to the user and selecting the most suitable provider, a conversation means including automated vehicle customization information to support the generation of the request for proposal, and a DIY procedure presentation means for presenting a DIY procedure to the user based on the automated vehicle customization information. This allows the user to easily and efficiently collect and analyze automated vehicle customization requirements and receive quotations and proposals from appropriate providers. Furthermore, if the user can perform simple customization themselves, the procedure can be clearly guided.

[0168] A "user" is a person or organization that wishes to develop or customize a system or tool.

[0169] An "interactive means" is a mechanism for collecting requirements through communication with users, typically using AI to generate questions and obtain user answers.

[0170] A "generator" is a mechanism that analyzes the collected information and automatically generates a request for proposal (RFP) based on that information.

[0171] The "publication and collection means" is a mechanism for publishing the generated request for proposal to multiple providers and collecting quotations and proposals from the providers.

[0172] The "display and selection means" is a mechanism for presenting the collected quotes and proposals to the user and selecting the most suitable provider.

[0173] An "autonomous vehicle" is a vehicle equipped with autonomous driving technology that a user wishes to customize.

[0174] "Customization information" is information regarding specific changes or additional functions desired by the user.

[0175] The "DIY procedure presentation means" is a mechanism that presents the procedure to the user when simple customization can be performed by the user himself.

[0176] This invention provides a system that extracts user requirements for customizing an autonomous vehicle, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotations and proposals. To achieve this, the following hardware and software are used:

[0177] Hardware and software used

[0178] The system mainly uses the following hardware and software:

[0179] Hardware: Smartphone

[0180] software:

[0181] Interaction and generation: Python (Flask + GPT-4 API)

[0182] Notification and Collection: Firebase Cloud Messaging

[0183] Display and Selection: React Native

[0184] Fixes and instructions: JavaScript + HTML + CSS

[0185] System Overview

[0186] The system has the following main features:

[0187] 1. Means of interaction:

[0188] The server collects customization requests through dialogue with the user. This dialogue is carried out using a Flask-based web server and the GPT-4 API. When a user opens the smartphone app and creates a new customization project, the system generates initial questions, such as "Which part do you want to customize?", to obtain detailed requirements from the user.

[0189] 2. Generation means:

[0190] The server analyzes the information collected through the interactive means and automatically generates a request for proposal (RFP), using the GPT-4 API to automatically create an appropriate RFP template based on the collected requirements.

[0191] 3. Disclosure and collection methods:

[0192] The server publishes the generated RFP to multiple providers and uses Firebase Cloud Messaging to collect quotes and proposals. Providers are notified and can submit proposals through the system.

[0193] 4. Display and Selection Means:

[0194] The server displays the collected quotes and proposals to the user on a smartphone app using React Native, allowing the user to compare multiple proposals and select the best provider.

[0195] 5. DIY Instructions:

[0196] The server provides DIY instructions for simple customizations, showing users step-by-step how to customize the site themselves using JavaScript, HTML, and CSS.

[0197] Process example

[0198] Here, we will use a smartphone customization project for an autonomous vehicle as an example.

[0199] Examples:

[0200] 1. Means of interaction:

[0201] User: "I want to customize the interior of my self-driving car."

[0202] Server: "What specific parts would you like to customize?"

[0203] User: "I'd like to change the seat material. I'd also like to change the interior lighting."

[0204] 2. Generation means:

[0205] Server: Generates an RFP draft based on this information.

[0206] 3. Disclosure and collection methods:

[0207] Server: Notifies multiple providers of the generated RFP and collects proposals.

[0208] 4. Display and Selection Means:

[0209] Server: Displays the collected suggestions to the user.

[0210] User: Select the best offer.

[0211] 5. DIY Instructions:

[0212] Server: "You can also DIY the seat material change. Follow the steps below."

[0213] Prompt Sentence Examples

[0214] "When a user wants to customize an autonomous vehicle, we elicit the necessary requirements. The initial question is, 'What parts do you want to customize?' Based on the requirements collected, we generate a request for proposal (RFP) and notify the vendor."

[0215] This invention allows users to efficiently plan customization of autonomous vehicles and receive proposals from appropriate providers. It also supports users in carrying out the procedures themselves when simple customization is possible.

[0216] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0217] Step 1:

[0218] The server begins the initial interaction by having the user open the smartphone app and create a new customization project. The server uses the GPT-4 API to generate an initial question, asking the user, "What part do you want to customize?" The input in this step is information about the user's customization preferences, and the output is a specific request obtained from the user. The obtained request is stored in a database for further processing.

[0219] Step 2:

[0220] The server collects more detailed information based on the user's request information collected through the dialogue means. The server receives the user's answer, "I would like to change the seat material. I would also like to change the interior lights," as input, and generates follow-up questions related to those. For example, it asks questions such as, "What kind of material would you like to change?" or "Do you have any preferences regarding the color or brightness of the interior lights?" The output of this step is the additional detailed information obtained from the user.

[0221] Step 3:

[0222] The server uses the collected information to automatically generate a Request for Proposal (RFP) using an AI analysis module. The input of this step is all the collected user requirement information, and the output is the generated RFP draft. The RFP draft contains all the user's requests and specific requirements. The generated RFP is temporarily saved and used in the next step.

[0223] Step 4:

[0224] The server uses Firebase Cloud Messaging to notify multiple providers of the generated RFP. The input of this step is the RFP draft, and the output is notifications to providers. Providers who receive the notifications can submit proposals and quotes to the system. The server collects these proposals and stores them in a database.

[0225] Step 5:

[0226] The server displays the quotes and proposals received from providers to the user. React Native is used for the display. The input of this step is the collected quotes and proposals, and the output is a user interface that displays them. The user can compare the proposals through a smartphone app and select the best provider.

[0227] Step 6:

[0228] The user checks the contents of the request for proposal and enters corrections or additional requirements as necessary. The input for this step is the generated RFP draft and the user's new requirements, and the output is the revised RFP. The server notifies the proposal providers again and collects proposals again.

[0229] Step 7:

[0230] The server presents DIY instructions when simple customization is possible. Based on the user's request information, the server generates DIY instructions using JavaScript, HTML, and CSS and displays them to the user step by step. The input to this step is information about simple customization, and the output is specific DIY instructions.

[0231] This series of steps enables users to efficiently collect and analyze customization requirements for autonomous vehicles, receive proposals from appropriate providers, and also enables simple DIY customization.

[0232] 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.

[0233] This system extracts user requirements when a user wants to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotes and proposals. Furthermore, by combining it with an emotion engine that recognizes user emotions and optimizes the way dialogue and proposals are presented, a more user-friendly experience is provided.

[0234] System Overview

[0235] This system has the following main functions:

[0236] 1. Means of interaction

[0237] 2. Generation means

[0238] 3. Disclosure and collection methods

[0239] 4. Display and Selection Means

[0240] 5. Procedure Presentation Methods

[0241] 6. Remedies

[0242] 7. Emotion Engine

[0243] Explanation of program processing

[0244] 1. Means of interaction

[0245] A user accesses the system and creates a new project. The server launches an AI model to begin a dialogue with the user. The AI ​​generates an initial question, asking the user, "What kind of system or tool do you want?" The user then inputs a specific request (e.g., "Inventory management system").

[0246] 2. Emotion Engine

[0247] The server activates an emotion engine to analyze emotions from the user's voice and text. The AI ​​evaluates the user's emotions in real time and optimizes the content and tone of the dialogue. For example, if the user is feeling stressed, the system will shorten the questions.

[0248] 3. Generation means

[0249] The server analyzes the collected information and generates follow-up questions to gather more detailed information. The emotion engine considers the user's emotional state and asks questions in a way that minimizes the burden on the user. For example, questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[0250] 4. Procedure Presentation Method

[0251] If the collected information is relatively simple, the server will determine that "this requirement can be met with a simple tool." This function also integrates an emotion engine, which provides instructions based on the user's emotional state. For example, if the user is not anxious, detailed steps will be provided.

[0252] 5. Disclosure and Collection Methods

[0253] The generated RFP is sent to multiple providers by the server, who then view the RFP and submit quotes and proposals. The server then collects these quotes and proposals and prepares them for presentation to the user.

[0254] 6. Display and Selection Means

[0255] The collected estimates and suggestions are displayed to the user via the device. At this time, an emotion engine analyzes the user's emotions and presents information at the appropriate time. For example, it is designed to present important information when the user is relaxed.

[0256] 7. Remedies

[0257] The user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server receives this information and updates the RFP. During this process, the emotion engine monitors the user's state and provides appropriate feedback.

[0258] Specific examples

[0259] Example 1: Inventory management system requirements

[0260] User: "I want to create an inventory management system."

[0261] Server: "Would you like specific features in that inventory management system?"

[0262] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[0263] Server: "Okay. Is there anything else you need?"

[0264] If the user feels stressed, the server's emotion engine switches to a softer expression such as "Could you please tell me more about this?"

[0265] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[0266] User: Checks the RFP draft and presses the publish button.

[0267] Server: Posts the RFP to providers and collects proposals.

[0268] Example 2: Support for creating simple tools

[0269] User: "I want to automate my expense reports."

[0270] Server: "What features do you need?"

[0271] User: "I'd like it to automatically extract the amount from a photo of a receipt and enter it into a spreadsheet."

[0272] Server: "That functionality can be achieved using an Excel macro. Please follow these steps:"

[0273] The server monitors the user's emotional state and guides them through easy-to-understand steps.

[0274] The user follows the steps and creates a simple tool by themselves.

[0275] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. In addition, by combining it with an emotion engine, it is possible to efficiently and effectively collect requests and receive optimal proposals without causing stress to the user.

[0276] The processing flow will be explained below.

[0277] Step 1:

[0278] A user accesses the platform using a terminal and logs in. The user selects to create a new project and enters the project name and basic requirements (e.g., "Inventory Management System").

[0279] Step 2:

[0280] The server launches the AI ​​model and displays an initial question to the user, such as "What kind of system or tool do you want?"

[0281] Step 3:

[0282] The user inputs a specific request. For example, "I want to create an inventory management system."

[0283] Step 4:

[0284] The server's emotion engine analyzes the user's emotional state from their input and optimizes the conversation content to keep the conversation comfortable. If the user shows signs of anxiety or irritation, the server responds by presenting more specific questions in a softer tone.

[0285] Step 5:

[0286] The server's AI generates additional questions to gather more detailed information based on the user's input and the results of the emotion engine's analysis. For example, questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[0287] Step 6:

[0288] The user answers additional questions, for example, "I'd like real-time inventory updates and support for barcode scanners."

[0289] Step 7:

[0290] The server's AI analyzes the collected information and automatically fills in the request for proposal (RFP) template with information such as "real-time inventory management," "barcode compatibility," and "integrated inventory management for multiple warehouses."

[0291] Step 8:

[0292] The generated RFP draft is displayed on the terminal for the user to review. The user can enter corrections or additional requirements as needed, and the emotion engine will analyze the user's emotions and provide appropriate feedback.

[0293] Step 9:

[0294] The user finally checks the RFP draft and presses the publish button, which makes the RFP available to providers.

[0295] Step 10:

[0296] The server notifies multiple providers of the RFP and collects quotations and proposals from them.

[0297] Step 11:

[0298] The server organizes the collected estimates and proposals and presents them to the user via the device. At this time, the emotion engine analyzes the user's emotions and presents information at the appropriate time.

[0299] Step 12:

[0300] The user compares multiple quotes and proposals displayed and selects the most suitable provider.

[0301] Step 13:

[0302] The server notifies the selected provider and initiates the contract process.

[0303] Step 14:

[0304] If the collected information is relatively simple, the server's AI will determine that the requirements can be met with a simple tool and provide specific instructions, such as instructions for automating expense reimbursement sheets.

[0305] Step 15:

[0306] It supports users to create simple tools by following the steps. For example, it guides users step by step through the steps to create an Excel macro.

[0307] Example 2

[0308] 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."

[0309] In conventional systems, when a user requests the development of a system or tool, the process of accurately extracting requirements, creating a request for proposal (RFP), and collecting quotes and proposals from providers is cumbersome, placing a heavy burden on the user.In addition, since the effectiveness of the dialogue is affected by the user's emotional state, it is difficult to provide an appropriate interface.

[0310] 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.

[0311] In this invention, the server includes: an interaction means for collecting requirements through interaction with the user; an emotion engine for analyzing the user's emotions and optimizing the content and tone of the interaction; a generation means for automatically generating a request for proposal by analyzing the collected information; a publishing and collection means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers; and a display and selection means for presenting the collected estimates and proposals to the user and selecting the most suitable provider. This reduces the burden on the user, and makes it possible to efficiently and effectively collect requirements and receive the most suitable proposal.

[0312] The "interaction means" is a means for collecting requirements through interaction with the user.

[0313] An "emotion engine" is a means of analyzing a user's emotions and optimizing the content and tone of the dialogue.

[0314] The "generation means" is a means for automatically generating a request for proposal by analyzing the collected information.

[0315] The "publication and collection means" refers to a means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers.

[0316] The "display and selection means" is a means for presenting the collected estimates and proposals to the user and allowing the user to select the most suitable provider.

[0317] The "procedure presentation means" is a means for presenting a procedure for the user to create a system or tool by themselves when the collected information is relatively simple.

[0318] The "modification means" is a means for checking and modifying a request for proposal generated based on a user's request.

[0319] This system extracts user requirements when a user wants to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotes and proposals. Furthermore, by combining it with an emotion engine that recognizes user emotions and optimizes the way dialogue and proposals are presented, a more user-friendly experience is provided.

[0320] This system mainly uses the following hardware and software:

[0321] Hardware:

[0322] Server: A computer device that controls the entire system and processes data.

[0323] Terminal: The device from which the user accesses the site (PC, tablet, smartphone, etc.)

[0324] software:

[0325] Generative AI model: An AI model that gathers information through user interaction and automatically generates a request for proposal (RFP) (e.g., OpenAI GPT-4)

[0326] Emotion engine: An engine that analyzes user emotions in real time and optimizes the content and tone of conversations (e.g., Affectiva Emotion AI)

[0327] The operation of the system proceeds as follows.

[0328] First, when a user accesses the system to create a new project, the server launches the AI ​​model and begins a dialogue with the user. First, the AI ​​generates a question such as "What kind of system or tool do you want?" and poses the question to the user through a prompt. The user then enters the specific request, "Inventory management system."

[0329] The server then activates an emotion engine to analyze the user's emotions from their voice and text input. It evaluates their emotional state in real time and optimizes the content and tone of the dialogue. For example, if the user is feeling stressed, the AI ​​simplifies the question and displays a message saying, "Please let me know if you need a clearer explanation."

[0330] The server then analyzes the collected initial information and generates follow-up questions to gather more detailed information. The emotion engine considers the user's emotional state and generates questions that are displayed to the user in text format. For example, follow-up questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[0331] Based on the collected information, the server determines that the requirements for the inventory management system can be met with relatively simple tools and presents specific steps to the user. For example, detailed instructions are provided on how to set up a "real-time inventory update" function using an Excel macro, and the user can follow the steps to proceed.

[0332] The generated RFP is published by the server to multiple providers, who can view the RFP and submit quotes and proposals. The server collects these proposals in a database and stores them as data for the next step.

[0333] The collected suggestions are displayed to the user via the device. The emotion engine analyzes the user's emotional state and presents important information at the appropriate time. For example, detailed comparative information is provided when the user is relaxed.

[0334] Finally, the user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server receives this new information and updates the RFP. The emotion engine constantly monitors the user's state and provides appropriate feedback and guidance.

[0335] An example of a specific prompt might look like this:

[0336] Example 1: Inventory management system requirements

[0337] User: "I want to create an inventory management system."

[0338] Server: "Would you like specific features in that inventory management system?"

[0339] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[0340] Server: "Okay. Is there anything else you need?"

[0341] If the user feels stressed, the server's emotion engine switches to a softer expression, asking, "Could you please tell me more?"

[0342] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[0343] User: Checks the RFP draft and presses the publish button.

[0344] Server: Posts the RFP to providers and collects proposals.

[0345] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. In addition, by combining it with an emotion engine, it is possible to efficiently and effectively collect requests and receive optimal proposals without causing stress to the user.

[0346] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0347] Step 1:

[0348] A user accesses the system to create a new project. The user logs into the system's web interface using a terminal and clicks the Create New Project button. Input: User login information and project creation action. Output: A request to create a new project is sent to the server.

[0349] Step 2:

[0350] The server launches an AI model (e.g., a generative AI model) and begins a dialogue with the user. The server generates an initial question (e.g., "What kind of system or tool do you want?") and presents it to the user as a prompt. Input: A request to create a new project. Output: A prompt for the initial question to the user.

[0351] Step 3:

[0352] The user inputs a specific request (e.g., "inventory management system") in response to the initial question. The user inputs the answer using a terminal and sends it to the server. Input: User's answer. Output: The user's specific request is sent to the server.

[0353] Step 4:

[0354] The server launches an emotion engine to analyze emotions from the text entered by the user. The emotion engine analyzes the text data and evaluates the user's emotional state (e.g., stress, anxiety, etc.). Input: User's text response. Output: Analyzed emotion data.

[0355] Step 5:

[0356] The server generates follow-up questions taking into account the user's emotional state. To gather more detailed information, the server generates the next question (e.g., "Do you want to manage inventory in real time?") based on the output of the emotion engine. Input: User's emotional data. Output: Generation and presentation of follow-up questions.

[0357] Step 6:

[0358] The user answers the follow-up questions and provides detailed information. For example, answer "Yes" to "Do you want to manage inventory in real time?" Input: User's answer to the follow-up question. Output: Detailed information is sent to the server.

[0359] Step 7:

[0360] The server analyzes the collected information and automatically generates the required Request for Proposal (RFP) draft. Based on the collected details, the RFP draft is generated and created in a user-friendly format based on the output of the emotion engine. Input: User's detailed information. Output: Generated RFP draft.

[0361] Step 8:

[0362] The server publishes the generated RFP draft to multiple providers. The server sends notifications to providers and provides them with links to access the RFP draft. Input: Generated RFP draft. Output: Notifications and links sent to providers.

[0363] Step 9:

[0364] Provider views the RFP, creates a quote or proposal, and sends it to the server. Provider clicks on a link to view the RFP, enters a proposal or quote, and submits it. Input: Provider's proposal and quote. Output: Proposal and quote sent to the server.

[0365] Step 10:

[0366] The server stores the collected quotes and proposals in a database and prepares them to be presented to the user. The server organizes the information and lists it in a format that is easy for the user to understand. Input: Proposals and quotes from providers. Output: Information prepared for presentation to the user.

[0367] Step 11:

[0368] The user reviews the proposals and quotes through the terminal and selects the most suitable provider. The emotion engine monitors the user's emotional state and presents information at the appropriate time. Input: List of proposals and quotes. Output: User's provider selection.

[0369] Step 12:

[0370] The user reviews the generated RFP draft and enters any necessary corrections or additional requirements. The server receives the new information and updates the RFP. The emotion engine provides feedback and the updated RFP is available for the user to review. Input: Revised RFP draft and additional requirements. Output: Updated RFP.

[0371] In this way, through specific processing steps, the system can collect user requests, efficiently generate a request for proposal, and receive optimal proposals.

[0372] (Application example 2)

[0373] 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."

[0374] When users wish to develop new systems or tools, they need to be able to effectively extract their requirements and quickly and accurately create a request for proposal (RFP). However, conventional methods place a heavy burden on users, often resulting in emotional stress. It is also difficult to properly publish the generated RFP and reliably collect quotes and proposals from suppliers. Furthermore, for efficient operation within factories, integration with devices such as smart glasses is also important. A system that can solve these issues is needed.

[0375] The specification processing by the specification 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: a dialogue means for collecting requirements through dialogue with the user; a generation means for automatically generating a request for proposal by analyzing the collected information; a publication and collection means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers; a display and selection means for presenting the collected estimates and proposals to the user and selecting the most appropriate provider; an emotion analysis means for analyzing the user's emotions and optimizing the tone of the dialogue and the presentation of information; and a display device linkage means for providing an interface via a device worn by the user. This makes it possible to efficiently generate an RFP and collect proposals from appropriate providers while reducing stress on the user.

[0376] "User" refers to the entity that uses a system or device, typically a human operator.

[0377] "Dialogue means" refers to a function for gathering requests and information through conversation with the user.

[0378] "Generation means" refers to the functionality for analyzing collected information and automatically generating a request for proposal (RFP).

[0379] "Publication and collection means" refers to a function for publishing the generated request for proposal to multiple providers and collecting estimates and proposals from the providers.

[0380] "Display and selection means" refers to a function for presenting collected estimates and proposals to the user and allowing the user to select the most suitable provider.

[0381] "Emotion analysis means" refers to a function that analyzes the user's voice and facial expressions in real time to optimize the tone of the conversation and the presentation of information.

[0382] "Display device linking means" refers to a function for providing an interface via a device worn by a user (e.g., smart glasses).

[0383] A "Request for Proposal (RFP)" is a document that clearly states the user's requirements and specifications and requests quotes and proposals from providers.

[0384] "Provider" refers to the entity that provides an estimate or proposal based on a Request for Proposal.

[0385] "Collected Information" refers to specific details of your requests and desires obtained through your interactions with us.

[0386] To implement the invention, the system includes the following major functions:

[0387] Hardware and Software Use

[0388] Hardware: Smart glasses, factory server

[0389] Software: Sentiment analysis API (e.g., IBM Watson Emotion Analysis), dialogue generation models (e.g., GPT-4), cloud RFP management system

[0390] System Overview

[0391] The system provides an interface using smart glasses worn by the user. Each of the means will be described in detail below.

[0392] User interaction methods

[0393] First, the user puts on the smart glasses and accesses the system. The system then activates the voice assistant built into the smart glasses and starts a dialogue with the user. The following is an example of a specific dialogue:

[0394] Voice Assistant: "I'm starting a new project. What systems and tools would you like to use?"

[0395] User: "I want to build a robotic control system for a new assembly line."

[0396] Emotion analysis means

[0397] The system then uses the smart glasses' camera and microphone to analyze the user's voice and facial expressions in real time, and an emotion analysis API assesses the user's emotional state and optimizes the tone of the dialogue and the way information is presented based on this.

[0398] Example: If the user's stress level is assessed as high, the voice assistant will provide additional information such as, "Don't worry, we'll take it easy and proceed slowly."

[0399] Request for Proposal (RFP) generation tools

[0400] Based on the collected information, the dialogue generation model (GPT-4) generates detailed questions and gathers further information. Throughout this process, the sentiment analysis tool continues to operate, reducing the burden on the user.

[0401] Example prompt sentence:

[0402] "Do you want real-time updates?"

[0403] "How do you deal with barcode scanners?"

[0404] "Are there any special safety considerations?"

[0405] Publication and collection methods

[0406] The generated RFP is uploaded to a cloud RFP management system via an in-factory server and notified to multiple providers. The quotes and proposals from the providers are collected by the cloud system and displayed on the smart glasses screen.

[0407] Display and Selection Means

[0408] The collected quotes and proposals are presented to the user through the smart glasses for review and selection of the most suitable provider, with the user making selections and modifications using voice commands.

[0409] Example: The user confirms and then gives a voice command saying, "Please correct this part." The system then reflects the correction and re-sends the RFP to the provider.

[0410] The system allows users to efficiently generate RFPs and receive proposals from suitable providers with minimal stress.

[0411] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0412] Step 1:

[0413] The server launches the voice assistant in the smart glasses and asks the user, "I'm starting a new project. What kind of system and tools would you like?" The user replies, "I want to build a robotic control system for a new assembly line." This collects the initial requirements.

[0414] Input: User voice input

[0415] Output: Initial request data

[0416] Step 2:

[0417] The server analyzes the user's voice and facial expressions in real time using the smart glasses' camera and microphone, and evaluates the user's emotional state using an emotion analysis API (e.g., IBM Watson Emotion Analysis). The server then optimizes the tone of the dialogue and the way information is presented depending on the user's emotional state.

[0418] Input: User audio and video data

[0419] Output: User's emotional state data

[0420] Step 3:

[0421] The server uses a generative AI model (e.g., GPT-4) to generate detailed questions based on the collected initial request data and emotional state data. The questions are presented to the user through the smart glasses, and the user's answers are collected.

[0422] Input: Initial request data, emotional state data

[0423] Output: Detailed question data, user response data

[0424] Step 4:

[0425] The server automatically generates a Request for Proposal (RFP) based on all the collected information. It uses a generative AI model to analyze the input data and create a specific RFP document, which is then displayed on the smart glasses' display.

[0426] Input: User response data

[0427] Output: Request for Proposal (RFP) draft

[0428] Step 5:

[0429] The user checks the RFP draft displayed on the smart glasses display and makes any necessary corrections using voice commands. The server receives these correction instructions and updates the RFP draft.

[0430] Input: User correction instructions

[0431] Output: Updated RFP draft

[0432] Step 6:

[0433] The server uploads the completed RFP to a cloud RFP management system and notifies multiple providers. It also collects quotes and proposals from the providers. The proposal data collected by the cloud system is presented to the user through the smart glasses display.

[0434] Input: Updated RFP draft

[0435] Output: Quotation and proposal data from providers

[0436] Step 7:

[0437] The user reviews the quotes and proposals presented on the smart glasses display and selects the best provider using voice commands. The server records this selection data and completes the RFP process.

[0438] Input: Quote and proposal data from providers, user selection data

[0439] Output: Selection data for the best provider

[0440] 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.

[0441] 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.

[0442] 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.

[0443] [Second embodiment]

[0444] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0445] 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.

[0446] 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).

[0447] 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.

[0448] 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.

[0449] 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).

[0450] 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.

[0451] 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.

[0452] 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.

[0453] 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.

[0454] 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.

[0455] 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."

[0456] This invention relates to a system that extracts requirements from users who wish to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotations and proposals. This invention enables improved business efficiency and advanced business management.

[0457] System Overview

[0458] This system has the following main functions:

[0459] 1. Means of interaction

[0460] 2. Generation means

[0461] 3. Disclosure and collection methods

[0462] 4. Display and Selection Means

[0463] 5. Procedure Presentation Methods

[0464] 6. Remedies

[0465] Explanation of program processing

[0466] 1. Means of interaction

[0467] A user accesses the system and creates a new project. The server launches an AI model to begin a dialogue with the user. The AI ​​generates an initial question, asking the user, "What kind of system or tool do you want?" The user then inputs a specific request (e.g., "Inventory management system").

[0468] 2. Generation means

[0469] The server analyzes the collected information and continues to ask questions to gather more detailed information. For example, if a user requests an "inventory management system," they will include specific requirements such as "real-time inventory management," "barcode scanning support," and "integrated inventory management for multiple warehouses." Based on this information, the AI ​​automatically fills in the information in a request for proposal (RFP) template.

[0470] 3. Disclosure and collection methods

[0471] The generated RFP is registered in the system by the server and notified to multiple providers. The providers view the RFP and submit quotations and proposals. The server collects these quotations and proposals and prepares them for presentation to the user.

[0472] 4. Display and Selection Means

[0473] The collected quotes and proposals are presented to the user via the terminal. The user compares and considers multiple proposals and selects the most suitable provider. Once the selection is complete, the server notifies the selected provider and proceeds with the contract procedure.

[0474] 5. Procedure Presentation Methods

[0475] If the collected information is relatively simple, the server's AI will determine that "this requirement can be met with a simple tool." In this case, the server will present specific steps and support the user in creating the tool themselves. For example, if automating expense reimbursement sheets, it will provide step-by-step instructions on how to use Excel and macros.

[0476] 6. Remedies

[0477] The user can review the generated RFP draft and enter any necessary corrections or additions. The server receives this information and updates the RFP.

[0478] Specific examples

[0479] Example 1: Inventory management system requirements

[0480] User: "I want to create an inventory management system."

[0481] Server: "Would you like specific features in that inventory management system?"

[0482] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[0483] Server: "Okay. Is there anything else you need?"

[0484] User: "I want to manage inventory across multiple warehouses."

[0485] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[0486] User: Checks the RFP draft and presses the publish button.

[0487] Server: Posts the RFP to providers and collects proposals.

[0488] Example 2: Support for creating simple tools

[0489] User: "I want to automate my expense reports."

[0490] Server: "What features do you need?"

[0491] User: "I'd like it to automatically extract the amount from a photo of a receipt and enter it into a spreadsheet."

[0492] Server: "That functionality can be achieved using an Excel macro. Please follow these steps:"

[0493] The server displays the steps for creating an Excel macro, and the user follows the steps to create the program.

[0494] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. It also supports the creation of simple tools to help small and medium-sized enterprises and individuals improve their business efficiency.

[0495] The processing flow will be explained below.

[0496] Step 1:

[0497] A user accesses the platform using a terminal and logs in. The user selects to create a new project and enters the project name and basic requirements (e.g., "Inventory Management System").

[0498] Step 2:

[0499] The server launches the AI ​​model and displays an initial question to the user, such as "What kind of system or tool do you want?"

[0500] Step 3:

[0501] The user inputs a specific request. For example, "I want to create an inventory management system."

[0502] Step 4:

[0503] The server's AI generates additional questions to gather more information based on the user's input, such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?"

[0504] Step 5:

[0505] The user answers additional questions, for example, "I'd like real-time inventory updates and support for barcode scanners."

[0506] Step 6:

[0507] The server's AI analyzes the collected information and automatically fills in the request for proposal (RFP) template with information such as "real-time inventory management," "barcode compatibility," and "integrated inventory management for multiple warehouses."

[0508] Step 7:

[0509] The generated RFP draft is displayed on the terminal for the user to review, and the user can enter corrections or additional requirements as necessary.

[0510] Step 8:

[0511] The user finally checks the RFP draft and presses the publish button, which makes the RFP available to providers.

[0512] Step 9:

[0513] The server notifies multiple providers of the RFP and collects quotations and proposals from them.

[0514] Step 10:

[0515] The server organizes the collected estimates and proposals and presents them to the user via the terminal.

[0516] Step 11:

[0517] The user compares multiple quotes and proposals displayed and selects the most suitable provider.

[0518] Step 12:

[0519] The server notifies the selected provider and initiates the contract process.

[0520] Step 13:

[0521] If the collected information is relatively simple, the server's AI will determine that the requirements can be met with a simple tool and provide specific instructions, such as instructions for automating expense reimbursement sheets.

[0522] Step 14:

[0523] It supports users to create simple tools by following the steps. For example, it guides users step by step through the steps to create an Excel macro.

[0524] Example 1

[0525] 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."

[0526] In conventional system development, it takes a great deal of time and effort for users to clarify their requirements and convert them into a request for proposal (RFP). Collecting quotes and proposals from multiple suppliers and selecting the most suitable provider is also complicated. Furthermore, creating simple tools on your own presents high technical hurdles, making it difficult for small and medium-sized enterprises and individuals to easily improve business efficiency.

[0527] 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.

[0528] In this invention, the server includes an interactive means, a generating means, a publishing and collecting means, a display and selecting means, and a procedure presenting means. This allows a user wishing to develop a system or tool to interactively collect the necessary information, automatically generate a request for proposal, and present it to multiple suppliers. Furthermore, when creating a simple tool, specific procedures are presented, improving work efficiency.

[0529] "Interaction means" refers to the interactive interface used by the user to access the system and to gather information between the user and the server.

[0530] "Generation means" refers to the functionality for analyzing collected information and automatically generating a request for proposal (RFP).

[0531] "Publication and collection means" refers to a function for publishing an automatically generated request for proposal to multiple suppliers and collecting quotations and proposals from the suppliers.

[0532] "Display and selection means" refers to a function that presents collected quotes and proposals to the user and enables the user to select the most suitable supplier.

[0533] The "procedure presentation means" refers to a function for presenting specific procedures and providing support when a user wishes to create a simple tool.

[0534] The "modification means" refers to a function for checking and modifying a request for proposal generated based on a user's request.

[0535] This system extracts requirements when a user wishes to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple suppliers to collect quotations and proposals. It also supports the creation of simple tools, improving business efficiency and providing advanced business management.

[0536] System Overview

[0537] This system has the following main functions:

[0538] Interaction methods

[0539] A user accesses the system and creates a new project. The server launches the generative AI model and begins a dialogue with the user. First, the server generates a prompt asking, "What kind of system or tool do you want?" and displays it to the user via the terminal. The user then inputs their specific request, for example, "Inventory management system."

[0540] generation means

[0541] The server analyzes the information provided by the user and automatically generates questions to gather more detailed information. For example, it checks specific requirements such as "real-time inventory management," "barcode scanning support," and "integrated inventory management across multiple warehouses." Based on this information, the server automatically inputs the information into a request for proposal (RFP) template.

[0542] Publication and collection methods

[0543] The generated RFP is registered in the system by the server and notified to multiple suppliers. Suppliers can view the RFP and submit quotations and proposals. The server collects, organizes, and stores these proposals.

[0544] Display and Selection Means

[0545] The collected quotes and proposals are presented to the user via the terminal. The user compares multiple proposals and selects the most suitable supplier. After the selection, the server notifies the selected supplier and proceeds with the contract procedure.

[0546] Procedure presentation method

[0547] If a user wants to create a simple tool, the server's generative AI model will provide specific instructions, such as "How to automate an expense report sheet using an Excel macro," and help the user create the tool by following the instructions.

[0548] Correction means

[0549] The user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server updates the RFP with this information.

[0550] Specific examples

[0551] Example 1: Inventory management system requirements

[0552] 1. User: "I want to create an inventory management system."

[0553] 2. Server: "Would you like specific features in that inventory management system?"

[0554] 3. User: "I want to update inventory in real time. I also want it to be compatible with barcode scanners."

[0555] 4. Server: "Okay. Is there anything else you need?"

[0556] 5. User: "I want to manage inventory across multiple warehouses."

[0557] 6. Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[0558] 7. User: Checks the RFP draft and presses the publish button.

[0559] 8. Server: Notifies suppliers of the RFP and collects proposals.

[0560] Example 2: Support for creating simple tools

[0561] 1. User: "I want to automate my expense report."

[0562] 2. Server: "What features do you need?"

[0563] 3. User: "I'd like the amount to be automatically extracted from a photo of a receipt and entered into a spreadsheet."

[0564] 4. Server: "That functionality can be achieved using an Excel macro. Please follow the steps below."

[0565] 5. The server displays the step-by-step instructions for creating an Excel macro, and the user follows them to write the program.

[0566] This system allows users to easily request the development of systems and tools, and efficiently collect and compare quotes and proposals from multiple suppliers.It also provides specific procedures for creating simple tools, helping to improve the efficiency of work for small and medium-sized enterprises and individuals.

[0567] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0568] Step 1: Create a project and start interacting

[0569] A user accesses the system and clicks the "Create a new project" button. This input is sent to the server. The server receives this action and launches a generative AI model. The server generates the initial prompt, "What kind of system or tool do you want?", and displays it to the user via the terminal. The user's response (e.g., inventory management system) is received as input.

[0570] Step 2: Refine your requirements

[0571] The server analyzes the user's responses and uses a generative AI model to create follow-up questions to gather more detailed information. For example, detailed questions such as "Do you manage inventory in real time?" or "Do you support barcode scanning?" are generated and displayed to the user via their device. The user answers these questions, and the answers are sent to the server as input data. The server accumulates this data and collects more detailed information for the RFP template.

[0572] Step 3: Generate an RFP

[0573] The server automatically generates an RFP draft based on the collected information. The input data is the collected user's request details, which are analyzed and automatically embedded in a request for proposal template. The generated RFP draft is displayed to the user via their terminal. The user checks the contents and makes corrections as necessary. This confirmation and correction information is also sent to the server as input data.

[0574] Step 4: Publish the RFP

[0575] The user checks the generated RFP draft and clicks the "Publish" button. This input causes the server to register the RFP in the system and send notifications to multiple suppliers. Suppliers view the RFP and send quotations and proposals to the server. These proposals are collected, organized, and stored by the server.

[0576] Step 5: Collect and display suggestions

[0577] The server organizes the collected estimates and proposals, presents them to the user as a list via the terminal, and provides the user with the information they need to compare proposals. The user then compares the proposals from each provider and enters the information to select the most suitable provider.

[0578] Step 6: Selection and notification of the best proposal

[0579] The user selects the best proposal and clicks a button to confirm the selection. Upon receiving this input, the server notifies the selected provider and initiates the contract process. At the same time, it notifies other suppliers of the selection result.

[0580] Step 7: Support for creating simple tools

[0581] When a user wants to create a simple tool (e.g., to automate expense reports), the generative AI model on the server presents specific steps to the user. For example, the generative AI model creates a step-by-step guide to "How to automate expense reports using Excel macros" and displays it to the user via their device. The user then follows the steps to create the tool.

[0582] The above is the flow of processing steps and specific operations in this system.

[0583] (Application example 1)

[0584] 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."

[0585] In today's world, when a user wishes to customize an autonomous vehicle, it is difficult to efficiently gather specific requirements and create an appropriate request for proposal (RFP). Conventional systems require users to consider detailed technical specifications themselves, which requires a lot of time and effort. Furthermore, the process of efficiently publishing the created RFP to multiple providers and collecting quotes and proposals is also cumbersome. Furthermore, even when simple customization is possible, there is a lack of support for users to understand and execute the procedure.

[0586] 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.

[0587] In this invention, the server includes a conversation means for collecting requirements through a dialogue with the user, a generation means for automatically generating a request for proposal by analyzing the collected information, a publishing and collection means for publishing the automatically generated request for proposal to multiple providers and collecting quotations and proposals from the providers, a display and selection means for presenting the collected quotations and proposals to the user and selecting the most suitable provider, a conversation means including automated vehicle customization information to support the generation of the request for proposal, and a DIY procedure presentation means for presenting a DIY procedure to the user based on the automated vehicle customization information. This allows the user to easily and efficiently collect and analyze automated vehicle customization requirements and receive quotations and proposals from appropriate providers. Furthermore, if the user can perform simple customization themselves, the procedure can be clearly guided.

[0588] A "user" is a person or organization that wishes to develop or customize a system or tool.

[0589] An "interactive means" is a mechanism for collecting requirements through communication with users, typically using AI to generate questions and obtain user answers.

[0590] A "generator" is a mechanism that analyzes the collected information and automatically generates a request for proposal (RFP) based on that information.

[0591] The "publication and collection means" is a mechanism for publishing the generated request for proposal to multiple providers and collecting quotations and proposals from the providers.

[0592] The "display and selection means" is a mechanism for presenting the collected quotes and proposals to the user and selecting the most suitable provider.

[0593] An "autonomous vehicle" is a vehicle equipped with autonomous driving technology that a user wishes to customize.

[0594] "Customization information" is information regarding specific changes or additional functions desired by the user.

[0595] The "DIY procedure presentation means" is a mechanism that presents the procedure to the user when simple customization can be performed by the user himself.

[0596] This invention provides a system that extracts user requirements for customizing an autonomous vehicle, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotations and proposals. To achieve this, the following hardware and software are used:

[0597] Hardware and software used

[0598] The system mainly uses the following hardware and software:

[0599] Hardware: Smartphone

[0600] software:

[0601] Interaction and generation: Python (Flask + GPT-4 API)

[0602] Notification and Collection: Firebase Cloud Messaging

[0603] Display and Selection: React Native

[0604] Fixes and instructions: JavaScript + HTML + CSS

[0605] System Overview

[0606] The system has the following main features:

[0607] 1. Means of interaction:

[0608] The server collects customization requests through dialogue with the user. This dialogue is carried out using a Flask-based web server and the GPT-4 API. When a user opens the smartphone app and creates a new customization project, the system generates initial questions, such as "Which part do you want to customize?", to obtain detailed requirements from the user.

[0609] 2. Generation means:

[0610] The server analyzes the information collected through the interactive means and automatically generates a request for proposal (RFP), using the GPT-4 API to automatically create an appropriate RFP template based on the collected requirements.

[0611] 3. Disclosure and collection methods:

[0612] The server publishes the generated RFP to multiple providers and uses Firebase Cloud Messaging to collect quotes and proposals. Providers are notified and can submit proposals through the system.

[0613] 4. Display and Selection Means:

[0614] The server displays the collected quotes and proposals to the user on a smartphone app using React Native, allowing the user to compare multiple proposals and select the best provider.

[0615] 5. DIY Instructions:

[0616] The server provides DIY instructions for simple customizations, showing users step-by-step how to customize the site themselves using JavaScript, HTML, and CSS.

[0617] Process example

[0618] Here, we will use a smartphone customization project for an autonomous vehicle as an example.

[0619] Examples:

[0620] 1. Means of interaction:

[0621] User: "I want to customize the interior of my self-driving car."

[0622] Server: "What specific parts would you like to customize?"

[0623] User: "I'd like to change the seat material. I'd also like to change the interior lighting."

[0624] 2. Generation means:

[0625] Server: Generates an RFP draft based on this information.

[0626] 3. Disclosure and collection methods:

[0627] Server: Notifies multiple providers of the generated RFP and collects proposals.

[0628] 4. Display and Selection Means:

[0629] Server: Displays the collected suggestions to the user.

[0630] User: Select the best offer.

[0631] 5. DIY Instructions:

[0632] Server: "You can also DIY the seat material change. Follow the steps below."

[0633] Prompt Sentence Examples

[0634] "When a user wants to customize an autonomous vehicle, we elicit the necessary requirements. The initial question is, 'What parts do you want to customize?' Based on the requirements collected, we generate a request for proposal (RFP) and notify the vendor."

[0635] This invention allows users to efficiently plan customization of autonomous vehicles and receive proposals from appropriate providers. It also supports users in carrying out the procedures themselves when simple customization is possible.

[0636] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0637] Step 1:

[0638] The server begins the initial interaction by having the user open the smartphone app and create a new customization project. The server uses the GPT-4 API to generate an initial question, asking the user, "What part do you want to customize?" The input in this step is information about the user's customization preferences, and the output is a specific request obtained from the user. The obtained request is stored in a database for further processing.

[0639] Step 2:

[0640] The server collects more detailed information based on the user's request information collected through the dialogue means. The server receives the user's answer, "I would like to change the seat material. I would also like to change the interior lights," as input, and generates follow-up questions related to those. For example, it asks questions such as, "What kind of material would you like to change?" or "Do you have any preferences regarding the color or brightness of the interior lights?" The output of this step is the additional detailed information obtained from the user.

[0641] Step 3:

[0642] The server uses the collected information to automatically generate a Request for Proposal (RFP) using an AI analysis module. The input of this step is all the collected user requirement information, and the output is the generated RFP draft. The RFP draft contains all the user's requests and specific requirements. The generated RFP is temporarily saved and used in the next step.

[0643] Step 4:

[0644] The server uses Firebase Cloud Messaging to notify multiple providers of the generated RFP. The input of this step is the RFP draft, and the output is notifications to providers. Providers who receive the notifications can submit proposals and quotes to the system. The server collects these proposals and stores them in a database.

[0645] Step 5:

[0646] The server displays the quotes and proposals received from providers to the user. React Native is used for the display. The input of this step is the collected quotes and proposals, and the output is a user interface that displays them. The user can compare the proposals through a smartphone app and select the best provider.

[0647] Step 6:

[0648] The user checks the contents of the request for proposal and enters corrections or additional requirements as necessary. The input for this step is the generated RFP draft and the user's new requirements, and the output is the revised RFP. The server notifies the proposal providers again and collects proposals again.

[0649] Step 7:

[0650] The server presents DIY instructions when simple customization is possible. Based on the user's request information, the server generates DIY instructions using JavaScript, HTML, and CSS and displays them to the user step by step. The input to this step is information about simple customization, and the output is specific DIY instructions.

[0651] This series of steps enables users to efficiently collect and analyze customization requirements for autonomous vehicles, receive proposals from appropriate providers, and also enables simple DIY customization.

[0652] 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.

[0653] This system extracts user requirements when a user wants to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotes and proposals. Furthermore, by combining it with an emotion engine that recognizes user emotions and optimizes the way dialogue and proposals are presented, a more user-friendly experience is provided.

[0654] System Overview

[0655] This system has the following main functions:

[0656] 1. Means of interaction

[0657] 2. Generation means

[0658] 3. Disclosure and collection methods

[0659] 4. Display and Selection Means

[0660] 5. Procedure Presentation Methods

[0661] 6. Remedies

[0662] 7. Emotion Engine

[0663] Explanation of program processing

[0664] 1. Means of interaction

[0665] A user accesses the system and creates a new project. The server launches an AI model to begin a dialogue with the user. The AI ​​generates an initial question, asking the user, "What kind of system or tool do you want?" The user then inputs a specific request (e.g., "Inventory management system").

[0666] 2. Emotion Engine

[0667] The server activates an emotion engine to analyze emotions from the user's voice and text. The AI ​​evaluates the user's emotions in real time and optimizes the content and tone of the dialogue. For example, if the user is feeling stressed, the system will shorten the questions.

[0668] 3. Generation means

[0669] The server analyzes the collected information and generates follow-up questions to gather more detailed information. The emotion engine considers the user's emotional state and asks questions in a way that minimizes the burden on the user. For example, questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[0670] 4. Procedure Presentation Method

[0671] If the collected information is relatively simple, the server will determine that "this requirement can be met with a simple tool." This function also integrates an emotion engine, which provides instructions based on the user's emotional state. For example, if the user is not anxious, detailed steps will be provided.

[0672] 5. Disclosure and Collection Methods

[0673] The generated RFP is sent to multiple providers by the server, who then view the RFP and submit quotes and proposals. The server then collects these quotes and proposals and prepares them for presentation to the user.

[0674] 6. Display and Selection Means

[0675] The collected estimates and suggestions are displayed to the user via the device. At this time, an emotion engine analyzes the user's emotions and presents information at the appropriate time. For example, it is designed to present important information when the user is relaxed.

[0676] 7. Remedies

[0677] The user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server receives this information and updates the RFP. During this process, the emotion engine monitors the user's state and provides appropriate feedback.

[0678] Specific examples

[0679] Example 1: Inventory management system requirements

[0680] User: "I want to create an inventory management system."

[0681] Server: "Would you like specific features in that inventory management system?"

[0682] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[0683] Server: "Okay. Is there anything else you need?"

[0684] If the user feels stressed, the server's emotion engine switches to a softer expression such as "Could you please tell me more about this?"

[0685] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[0686] User: Checks the RFP draft and presses the publish button.

[0687] Server: Posts the RFP to providers and collects proposals.

[0688] Example 2: Support for creating simple tools

[0689] User: "I want to automate my expense reports."

[0690] Server: "What features do you need?"

[0691] User: "I'd like it to automatically extract the amount from a photo of a receipt and enter it into a spreadsheet."

[0692] Server: "That functionality can be achieved using an Excel macro. Please follow these steps:"

[0693] The server monitors the user's emotional state and guides them through easy-to-understand steps.

[0694] The user follows the steps and creates a simple tool by themselves.

[0695] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. In addition, by combining it with an emotion engine, it is possible to efficiently and effectively collect requests and receive optimal proposals without causing stress to the user.

[0696] The processing flow will be explained below.

[0697] Step 1:

[0698] A user accesses the platform using a terminal and logs in. The user selects to create a new project and enters the project name and basic requirements (e.g., "Inventory Management System").

[0699] Step 2:

[0700] The server launches the AI ​​model and displays an initial question to the user, such as "What kind of system or tool do you want?"

[0701] Step 3:

[0702] The user inputs a specific request. For example, "I want to create an inventory management system."

[0703] Step 4:

[0704] The server's emotion engine analyzes the user's emotional state from their input and optimizes the conversation content to keep the conversation comfortable. If the user shows signs of anxiety or irritation, the server responds by presenting more specific questions in a softer tone.

[0705] Step 5:

[0706] The server's AI generates additional questions to gather more detailed information based on the user's input and the results of the emotion engine's analysis. For example, questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[0707] Step 6:

[0708] The user answers additional questions, for example, "I'd like real-time inventory updates and support for barcode scanners."

[0709] Step 7:

[0710] The server's AI analyzes the collected information and automatically fills in the request for proposal (RFP) template with information such as "real-time inventory management," "barcode compatibility," and "integrated inventory management for multiple warehouses."

[0711] Step 8:

[0712] The generated RFP draft is displayed on the terminal for the user to review. The user can enter corrections or additional requirements as needed, and the emotion engine will analyze the user's emotions and provide appropriate feedback.

[0713] Step 9:

[0714] The user finally checks the RFP draft and presses the publish button, which makes the RFP available to providers.

[0715] Step 10:

[0716] The server notifies multiple providers of the RFP and collects quotations and proposals from them.

[0717] Step 11:

[0718] The server organizes the collected estimates and proposals and presents them to the user via the device. At this time, the emotion engine analyzes the user's emotions and presents information at the appropriate time.

[0719] Step 12:

[0720] The user compares multiple quotes and proposals displayed and selects the most suitable provider.

[0721] Step 13:

[0722] The server notifies the selected provider and initiates the contract process.

[0723] Step 14:

[0724] If the collected information is relatively simple, the server's AI will determine that the requirements can be met with a simple tool and provide specific instructions, such as instructions for automating expense reimbursement sheets.

[0725] Step 15:

[0726] It supports users to create simple tools by following the steps. For example, it guides users step by step through the steps to create an Excel macro.

[0727] Example 2

[0728] 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."

[0729] In conventional systems, when a user requests the development of a system or tool, the process of accurately extracting requirements, creating a request for proposal (RFP), and collecting quotes and proposals from providers is cumbersome, placing a heavy burden on the user.In addition, since the effectiveness of the dialogue is affected by the user's emotional state, it is difficult to provide an appropriate interface.

[0730] 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.

[0731] In this invention, the server includes: an interaction means for collecting requirements through interaction with the user; an emotion engine for analyzing the user's emotions and optimizing the content and tone of the interaction; a generation means for automatically generating a request for proposal by analyzing the collected information; a publishing and collection means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers; and a display and selection means for presenting the collected estimates and proposals to the user and selecting the most suitable provider. This reduces the burden on the user, and makes it possible to efficiently and effectively collect requirements and receive the most suitable proposal.

[0732] The "interaction means" is a means for collecting requirements through interaction with the user.

[0733] An "emotion engine" is a means of analyzing a user's emotions and optimizing the content and tone of the dialogue.

[0734] The "generation means" is a means for automatically generating a request for proposal by analyzing the collected information.

[0735] The "publication and collection means" refers to a means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers.

[0736] The "display and selection means" is a means for presenting the collected estimates and proposals to the user and allowing the user to select the most suitable provider.

[0737] The "procedure presentation means" is a means for presenting a procedure for the user to create a system or tool by themselves when the collected information is relatively simple.

[0738] The "modification means" is a means for checking and modifying a request for proposal generated based on a user's request.

[0739] This system extracts user requirements when a user wants to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotes and proposals. Furthermore, by combining it with an emotion engine that recognizes user emotions and optimizes the way dialogue and proposals are presented, a more user-friendly experience is provided.

[0740] This system mainly uses the following hardware and software:

[0741] Hardware:

[0742] Server: A computer device that controls the entire system and processes data.

[0743] Terminal: The device from which the user accesses the site (PC, tablet, smartphone, etc.)

[0744] software:

[0745] Generative AI model: An AI model that gathers information through user interaction and automatically generates a request for proposal (RFP) (e.g., OpenAI GPT-4)

[0746] Emotion engine: An engine that analyzes user emotions in real time and optimizes the content and tone of conversations (e.g., Affectiva Emotion AI)

[0747] The operation of the system proceeds as follows.

[0748] First, when a user accesses the system to create a new project, the server launches the AI ​​model and begins a dialogue with the user. First, the AI ​​generates a question such as "What kind of system or tool do you want?" and poses the question to the user through a prompt. The user then enters the specific request, "Inventory management system."

[0749] The server then activates an emotion engine to analyze the user's emotions from their voice and text input. It evaluates their emotional state in real time and optimizes the content and tone of the dialogue. For example, if the user is feeling stressed, the AI ​​simplifies the question and displays a message saying, "Please let me know if you need a clearer explanation."

[0750] The server then analyzes the collected initial information and generates follow-up questions to gather more detailed information. The emotion engine considers the user's emotional state and generates questions that are displayed to the user in text format. For example, follow-up questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[0751] Based on the collected information, the server determines that the requirements for the inventory management system can be met with relatively simple tools and presents specific steps to the user. For example, detailed instructions are provided on how to set up a "real-time inventory update" function using an Excel macro, and the user can follow the steps to proceed.

[0752] The generated RFP is published by the server to multiple providers, who can view the RFP and submit quotes and proposals. The server collects these proposals in a database and stores them as data for the next step.

[0753] The collected suggestions are displayed to the user via the device. The emotion engine analyzes the user's emotional state and presents important information at the appropriate time. For example, detailed comparative information is provided when the user is relaxed.

[0754] Finally, the user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server receives this new information and updates the RFP. The emotion engine constantly monitors the user's state and provides appropriate feedback and guidance.

[0755] An example of a specific prompt might look like this:

[0756] Example 1: Inventory management system requirements

[0757] User: "I want to create an inventory management system."

[0758] Server: "Would you like specific features in that inventory management system?"

[0759] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[0760] Server: "Okay. Is there anything else you need?"

[0761] If the user feels stressed, the server's emotion engine switches to a softer expression, asking, "Could you please tell me more?"

[0762] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[0763] User: Checks the RFP draft and presses the publish button.

[0764] Server: Posts the RFP to providers and collects proposals.

[0765] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. In addition, by combining it with an emotion engine, it is possible to efficiently and effectively collect requests and receive optimal proposals without causing stress to the user.

[0766] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0767] Step 1:

[0768] A user accesses the system to create a new project. The user logs into the system's web interface using a terminal and clicks the Create New Project button. Input: User login information and project creation action. Output: A request to create a new project is sent to the server.

[0769] Step 2:

[0770] The server launches an AI model (e.g., a generative AI model) and begins a dialogue with the user. The server generates an initial question (e.g., "What kind of system or tool do you want?") and presents it to the user as a prompt. Input: A request to create a new project. Output: A prompt for the initial question to the user.

[0771] Step 3:

[0772] The user inputs a specific request (e.g., "inventory management system") in response to the initial question. The user inputs the answer using a terminal and sends it to the server. Input: User's answer. Output: The user's specific request is sent to the server.

[0773] Step 4:

[0774] The server launches an emotion engine to analyze emotions from the text entered by the user. The emotion engine analyzes the text data and evaluates the user's emotional state (e.g., stress, anxiety, etc.). Input: User's text response. Output: Analyzed emotion data.

[0775] Step 5:

[0776] The server generates follow-up questions taking into account the user's emotional state. To gather more detailed information, the server generates the next question (e.g., "Do you want to manage inventory in real time?") based on the output of the emotion engine. Input: User's emotional data. Output: Generation and presentation of follow-up questions.

[0777] Step 6:

[0778] The user answers the follow-up questions and provides detailed information. For example, answer "Yes" to "Do you want to manage inventory in real time?" Input: User's answer to the follow-up question. Output: Detailed information is sent to the server.

[0779] Step 7:

[0780] The server analyzes the collected information and automatically generates the required Request for Proposal (RFP) draft. Based on the collected details, the RFP draft is generated and created in a user-friendly format based on the output of the emotion engine. Input: User's detailed information. Output: Generated RFP draft.

[0781] Step 8:

[0782] The server publishes the generated RFP draft to multiple providers. The server sends notifications to providers and provides them with links to access the RFP draft. Input: Generated RFP draft. Output: Notifications and links sent to providers.

[0783] Step 9:

[0784] Provider views the RFP, creates a quote or proposal, and sends it to the server. Provider clicks on a link to view the RFP, enters a proposal or quote, and submits it. Input: Provider's proposal and quote. Output: Proposal and quote sent to the server.

[0785] Step 10:

[0786] The server stores the collected quotes and proposals in a database and prepares them to be presented to the user. The server organizes the information and lists it in a format that is easy for the user to understand. Input: Proposals and quotes from providers. Output: Information prepared for presentation to the user.

[0787] Step 11:

[0788] The user reviews the proposals and quotes through the terminal and selects the most suitable provider. The emotion engine monitors the user's emotional state and presents information at the appropriate time. Input: List of proposals and quotes. Output: User's provider selection.

[0789] Step 12:

[0790] The user reviews the generated RFP draft and enters any necessary corrections or additional requirements. The server receives the new information and updates the RFP. The emotion engine provides feedback and the updated RFP is available for the user to review. Input: Revised RFP draft and additional requirements. Output: Updated RFP.

[0791] In this way, through specific processing steps, the system can collect user requests, efficiently generate a request for proposal, and receive optimal proposals.

[0792] (Application example 2)

[0793] 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."

[0794] When users wish to develop new systems or tools, they need to be able to effectively extract their requirements and quickly and accurately create a request for proposal (RFP). However, conventional methods place a heavy burden on users, often resulting in emotional stress. It is also difficult to properly publish the generated RFP and reliably collect quotes and proposals from suppliers. Furthermore, for efficient operation within factories, integration with devices such as smart glasses is also important. A system that can solve these issues is needed.

[0795] The specification processing by the specification 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: a dialogue means for collecting requirements through dialogue with the user; a generation means for automatically generating a request for proposal by analyzing the collected information; a publication and collection means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers; a display and selection means for presenting the collected estimates and proposals to the user and selecting the most appropriate provider; an emotion analysis means for analyzing the user's emotions and optimizing the tone of the dialogue and the presentation of information; and a display device linkage means for providing an interface via a device worn by the user. This makes it possible to efficiently generate an RFP and collect proposals from appropriate providers while reducing stress on the user.

[0796] "User" refers to the entity that uses a system or device, typically a human operator.

[0797] "Dialogue means" refers to a function for gathering requests and information through conversation with the user.

[0798] "Generation means" refers to the functionality for analyzing collected information and automatically generating a request for proposal (RFP).

[0799] "Publication and collection means" refers to a function for publishing the generated request for proposal to multiple providers and collecting estimates and proposals from the providers.

[0800] "Display and selection means" refers to a function for presenting collected estimates and proposals to the user and allowing the user to select the most suitable provider.

[0801] "Emotion analysis means" refers to a function that analyzes the user's voice and facial expressions in real time to optimize the tone of the conversation and the presentation of information.

[0802] "Display device linking means" refers to a function for providing an interface via a device worn by a user (e.g., smart glasses).

[0803] A "Request for Proposal (RFP)" is a document that clearly states the user's requirements and specifications and requests quotes and proposals from providers.

[0804] "Provider" refers to the entity that provides an estimate or proposal based on a Request for Proposal.

[0805] "Collected Information" refers to specific details of your requests and desires obtained through your interactions with us.

[0806] To implement the invention, the system includes the following major functions:

[0807] Hardware and Software Use

[0808] Hardware: Smart glasses, factory server

[0809] Software: Sentiment analysis API (e.g., IBM Watson Emotion Analysis), dialogue generation models (e.g., GPT-4), cloud RFP management system

[0810] System Overview

[0811] The system provides an interface using smart glasses worn by the user. Each of the means will be described in detail below.

[0812] User interaction methods

[0813] First, the user puts on the smart glasses and accesses the system. The system then activates the voice assistant built into the smart glasses and starts a dialogue with the user. The following is an example of a specific dialogue:

[0814] Voice Assistant: "I'm starting a new project. What systems and tools would you like to use?"

[0815] User: "I want to build a robotic control system for a new assembly line."

[0816] Emotion analysis means

[0817] The system then uses the smart glasses' camera and microphone to analyze the user's voice and facial expressions in real time, and an emotion analysis API assesses the user's emotional state and optimizes the tone of the dialogue and the way information is presented based on this.

[0818] Example: If the user's stress level is assessed as high, the voice assistant will provide additional information such as, "Don't worry, we'll take it easy and proceed slowly."

[0819] Request for Proposal (RFP) generation tools

[0820] Based on the collected information, the dialogue generation model (GPT-4) generates detailed questions and gathers further information. Throughout this process, the sentiment analysis tool continues to operate, reducing the burden on the user.

[0821] Example prompt sentence:

[0822] "Do you want real-time updates?"

[0823] "How do you deal with barcode scanners?"

[0824] "Are there any special safety considerations?"

[0825] Publication and collection methods

[0826] The generated RFP is uploaded to a cloud RFP management system via an in-factory server and notified to multiple providers. The quotes and proposals from the providers are collected by the cloud system and displayed on the smart glasses screen.

[0827] Display and Selection Means

[0828] The collected quotes and proposals are presented to the user through the smart glasses for review and selection of the most suitable provider, with the user making selections and modifications using voice commands.

[0829] Example: The user confirms and then gives a voice command saying, "Please correct this part." The system then reflects the correction and re-sends the RFP to the provider.

[0830] The system allows users to efficiently generate RFPs and receive proposals from suitable providers with minimal stress.

[0831] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0832] Step 1:

[0833] The server launches the voice assistant in the smart glasses and asks the user, "I'm starting a new project. What kind of system and tools would you like?" The user replies, "I want to build a robotic control system for a new assembly line." This collects the initial requirements.

[0834] Input: User voice input

[0835] Output: Initial request data

[0836] Step 2:

[0837] The server analyzes the user's voice and facial expressions in real time using the smart glasses' camera and microphone, and evaluates the user's emotional state using an emotion analysis API (e.g., IBM Watson Emotion Analysis). The server then optimizes the tone of the dialogue and the way information is presented depending on the user's emotional state.

[0838] Input: User audio and video data

[0839] Output: User's emotional state data

[0840] Step 3:

[0841] The server uses a generative AI model (e.g., GPT-4) to generate detailed questions based on the collected initial request data and emotional state data. The questions are presented to the user through the smart glasses, and the user's answers are collected.

[0842] Input: Initial request data, emotional state data

[0843] Output: Detailed question data, user response data

[0844] Step 4:

[0845] The server automatically generates a Request for Proposal (RFP) based on all the collected information. It uses a generative AI model to analyze the input data and create a specific RFP document, which is then displayed on the smart glasses' display.

[0846] Input: User response data

[0847] Output: Request for Proposal (RFP) draft

[0848] Step 5:

[0849] The user checks the RFP draft displayed on the smart glasses display and makes any necessary corrections using voice commands. The server receives these correction instructions and updates the RFP draft.

[0850] Input: User correction instructions

[0851] Output: Updated RFP draft

[0852] Step 6:

[0853] The server uploads the completed RFP to a cloud RFP management system and notifies multiple providers. It also collects quotes and proposals from the providers. The proposal data collected by the cloud system is presented to the user through the smart glasses display.

[0854] Input: Updated RFP draft

[0855] Output: Quotation and proposal data from providers

[0856] Step 7:

[0857] The user reviews the quotes and proposals presented on the smart glasses display and selects the best provider using voice commands. The server records this selection data and completes the RFP process.

[0858] Input: Quote and proposal data from providers, user selection data

[0859] Output: Selection data for the best provider

[0860] 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.

[0861] 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.

[0862] 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.

[0863] [Third embodiment]

[0864] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0865] 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.

[0866] 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).

[0867] 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.

[0868] 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.

[0869] 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).

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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.

[0875] 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."

[0876] This invention relates to a system that extracts requirements from users who wish to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotations and proposals. This invention enables improved business efficiency and advanced business management.

[0877] System Overview

[0878] This system has the following main functions:

[0879] 1. Means of interaction

[0880] 2. Generation means

[0881] 3. Disclosure and collection methods

[0882] 4. Display and Selection Means

[0883] 5. Procedure Presentation Methods

[0884] 6. Remedies

[0885] Explanation of program processing

[0886] 1. Means of interaction

[0887] A user accesses the system and creates a new project. The server launches an AI model to begin a dialogue with the user. The AI ​​generates an initial question, asking the user, "What kind of system or tool do you want?" The user then inputs a specific request (e.g., "Inventory management system").

[0888] 2. Generation means

[0889] The server analyzes the collected information and continues to ask questions to gather more detailed information. For example, if a user requests an "inventory management system," they will include specific requirements such as "real-time inventory management," "barcode scanning support," and "integrated inventory management for multiple warehouses." Based on this information, the AI ​​automatically fills in the information in a request for proposal (RFP) template.

[0890] 3. Disclosure and collection methods

[0891] The generated RFP is registered in the system by the server and notified to multiple providers. The providers view the RFP and submit quotations and proposals. The server collects these quotations and proposals and prepares them for presentation to the user.

[0892] 4. Display and Selection Means

[0893] The collected quotes and proposals are presented to the user via the terminal. The user compares and considers multiple proposals and selects the most suitable provider. Once the selection is complete, the server notifies the selected provider and proceeds with the contract procedure.

[0894] 5. Procedure Presentation Methods

[0895] If the collected information is relatively simple, the server's AI will determine that "this requirement can be met with a simple tool." In this case, the server will present specific steps and support the user in creating the tool themselves. For example, if automating expense reimbursement sheets, it will provide step-by-step instructions on how to use Excel and macros.

[0896] 6. Remedies

[0897] The user can review the generated RFP draft and enter any necessary corrections or additions. The server receives this information and updates the RFP.

[0898] Specific examples

[0899] Example 1: Inventory management system requirements

[0900] User: "I want to create an inventory management system."

[0901] Server: "Would you like specific features in that inventory management system?"

[0902] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[0903] Server: "Okay. Is there anything else you need?"

[0904] User: "I want to manage inventory across multiple warehouses."

[0905] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[0906] User: Checks the RFP draft and presses the publish button.

[0907] Server: Posts the RFP to providers and collects proposals.

[0908] Example 2: Support for creating simple tools

[0909] User: "I want to automate my expense reports."

[0910] Server: "What features do you need?"

[0911] User: "I'd like it to automatically extract the amount from a photo of a receipt and enter it into a spreadsheet."

[0912] Server: "That functionality can be achieved using an Excel macro. Please follow these steps:"

[0913] The server displays the steps for creating an Excel macro, and the user follows the steps to create the program.

[0914] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. It also supports the creation of simple tools to help small and medium-sized enterprises and individuals improve their business efficiency.

[0915] The processing flow will be explained below.

[0916] Step 1:

[0917] A user accesses the platform using a terminal and logs in. The user selects to create a new project and enters the project name and basic requirements (e.g., "Inventory Management System").

[0918] Step 2:

[0919] The server launches the AI ​​model and displays an initial question to the user, such as "What kind of system or tool do you want?"

[0920] Step 3:

[0921] The user inputs a specific request. For example, "I want to create an inventory management system."

[0922] Step 4:

[0923] The server's AI generates additional questions to gather more information based on the user's input, such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?"

[0924] Step 5:

[0925] The user answers additional questions, for example, "I'd like real-time inventory updates and support for barcode scanners."

[0926] Step 6:

[0927] The server's AI analyzes the collected information and automatically fills in the request for proposal (RFP) template with information such as "real-time inventory management," "barcode compatibility," and "integrated inventory management for multiple warehouses."

[0928] Step 7:

[0929] The generated RFP draft is displayed on the terminal for the user to review, and the user can enter corrections or additional requirements as necessary.

[0930] Step 8:

[0931] The user finally checks the RFP draft and presses the publish button, which makes the RFP available to providers.

[0932] Step 9:

[0933] The server notifies multiple providers of the RFP and collects quotations and proposals from them.

[0934] Step 10:

[0935] The server organizes the collected estimates and proposals and presents them to the user via the terminal.

[0936] Step 11:

[0937] The user compares multiple quotes and proposals displayed and selects the most suitable provider.

[0938] Step 12:

[0939] The server notifies the selected provider and initiates the contract process.

[0940] Step 13:

[0941] If the collected information is relatively simple, the server's AI will determine that the requirements can be met with a simple tool and provide specific instructions, such as instructions for automating expense reimbursement sheets.

[0942] Step 14:

[0943] It supports users to create simple tools by following the steps. For example, it guides users step by step through the steps to create an Excel macro.

[0944] Example 1

[0945] 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."

[0946] In conventional system development, it takes a great deal of time and effort for users to clarify their requirements and convert them into a request for proposal (RFP). Collecting quotes and proposals from multiple suppliers and selecting the most suitable provider is also complicated. Furthermore, creating simple tools on your own presents high technical hurdles, making it difficult for small and medium-sized enterprises and individuals to easily improve business efficiency.

[0947] 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.

[0948] In this invention, the server includes an interactive means, a generating means, a publishing and collecting means, a display and selecting means, and a procedure presenting means. This allows a user wishing to develop a system or tool to interactively collect the necessary information, automatically generate a request for proposal, and present it to multiple suppliers. Furthermore, when creating a simple tool, specific procedures are presented, improving work efficiency.

[0949] "Interaction means" refers to the interactive interface used by the user to access the system and to gather information between the user and the server.

[0950] "Generation means" refers to the functionality for analyzing collected information and automatically generating a request for proposal (RFP).

[0951] "Publication and collection means" refers to a function for publishing an automatically generated request for proposal to multiple suppliers and collecting quotations and proposals from the suppliers.

[0952] "Display and selection means" refers to a function that presents collected quotes and proposals to the user and enables the user to select the most suitable supplier.

[0953] The "procedure presentation means" refers to a function for presenting specific procedures and providing support when a user wishes to create a simple tool.

[0954] The "modification means" refers to a function for checking and modifying a request for proposal generated based on a user's request.

[0955] This system extracts requirements when a user wishes to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple suppliers to collect quotations and proposals. It also supports the creation of simple tools, improving business efficiency and providing advanced business management.

[0956] System Overview

[0957] This system has the following main functions:

[0958] Interaction methods

[0959] A user accesses the system and creates a new project. The server launches the generative AI model and begins a dialogue with the user. First, the server generates a prompt asking, "What kind of system or tool do you want?" and displays it to the user via the terminal. The user then inputs their specific request, for example, "Inventory management system."

[0960] generation means

[0961] The server analyzes the information provided by the user and automatically generates questions to gather more detailed information. For example, it checks specific requirements such as "real-time inventory management," "barcode scanning support," and "integrated inventory management across multiple warehouses." Based on this information, the server automatically inputs the information into a request for proposal (RFP) template.

[0962] Publication and collection methods

[0963] The generated RFP is registered in the system by the server and notified to multiple suppliers. Suppliers can view the RFP and submit quotations and proposals. The server collects, organizes, and stores these proposals.

[0964] Display and Selection Means

[0965] The collected quotes and proposals are presented to the user via the terminal. The user compares multiple proposals and selects the most suitable supplier. After the selection, the server notifies the selected supplier and proceeds with the contract procedure.

[0966] Procedure presentation method

[0967] If a user wants to create a simple tool, the server's generative AI model will provide specific instructions, such as "How to automate an expense report sheet using an Excel macro," and help the user create the tool by following the instructions.

[0968] Correction means

[0969] The user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server updates the RFP with this information.

[0970] Specific examples

[0971] Example 1: Inventory management system requirements

[0972] 1. User: "I want to create an inventory management system."

[0973] 2. Server: "Would you like specific features in that inventory management system?"

[0974] 3. User: "I want to update inventory in real time. I also want it to be compatible with barcode scanners."

[0975] 4. Server: "Okay. Is there anything else you need?"

[0976] 5. User: "I want to manage inventory across multiple warehouses."

[0977] 6. Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[0978] 7. User: Checks the RFP draft and presses the publish button.

[0979] 8. Server: Notifies suppliers of the RFP and collects proposals.

[0980] Example 2: Support for creating simple tools

[0981] 1. User: "I want to automate my expense report."

[0982] 2. Server: "What features do you need?"

[0983] 3. User: "I'd like the amount to be automatically extracted from a photo of a receipt and entered into a spreadsheet."

[0984] 4. Server: "That functionality can be achieved using an Excel macro. Please follow the steps below."

[0985] 5. The server displays the step-by-step instructions for creating an Excel macro, and the user follows them to write the program.

[0986] This system allows users to easily request the development of systems and tools, and efficiently collect and compare quotes and proposals from multiple suppliers.It also provides specific procedures for creating simple tools, helping to improve the efficiency of work for small and medium-sized enterprises and individuals.

[0987] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0988] Step 1: Create a project and start interacting

[0989] A user accesses the system and clicks the "Create a new project" button. This input is sent to the server. The server receives this action and launches a generative AI model. The server generates the initial prompt, "What kind of system or tool do you want?", and displays it to the user via the terminal. The user's response (e.g., inventory management system) is received as input.

[0990] Step 2: Refine your requirements

[0991] The server analyzes the user's responses and uses a generative AI model to create follow-up questions to gather more detailed information. For example, detailed questions such as "Do you manage inventory in real time?" or "Do you support barcode scanning?" are generated and displayed to the user via their device. The user answers these questions, and the answers are sent to the server as input data. The server accumulates this data and collects more detailed information for the RFP template.

[0992] Step 3: Generate an RFP

[0993] The server automatically generates an RFP draft based on the collected information. The input data is the collected user's request details, which are analyzed and automatically embedded in a request for proposal template. The generated RFP draft is displayed to the user via their terminal. The user checks the contents and makes corrections as necessary. This confirmation and correction information is also sent to the server as input data.

[0994] Step 4: Publish the RFP

[0995] The user checks the generated RFP draft and clicks the "Publish" button. This input causes the server to register the RFP in the system and send notifications to multiple suppliers. Suppliers view the RFP and send quotations and proposals to the server. These proposals are collected, organized, and stored by the server.

[0996] Step 5: Collect and display suggestions

[0997] The server organizes the collected estimates and proposals, presents them to the user as a list via the terminal, and provides the user with the information they need to compare proposals. The user then compares the proposals from each provider and enters the information to select the most suitable provider.

[0998] Step 6: Selection and notification of the best proposal

[0999] The user selects the best proposal and clicks a button to confirm the selection. Upon receiving this input, the server notifies the selected provider and initiates the contract process. At the same time, it notifies other suppliers of the selection result.

[1000] Step 7: Support for creating simple tools

[1001] When a user wants to create a simple tool (e.g., to automate expense reports), the generative AI model on the server presents specific steps to the user. For example, the generative AI model creates a step-by-step guide to "How to automate expense reports using Excel macros" and displays it to the user via their device. The user then follows the steps to create the tool.

[1002] The above is the flow of processing steps and specific operations in this system.

[1003] (Application example 1)

[1004] 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."

[1005] In today's world, when a user wishes to customize an autonomous vehicle, it is difficult to efficiently gather specific requirements and create an appropriate request for proposal (RFP). Conventional systems require users to consider detailed technical specifications themselves, which requires a lot of time and effort. Furthermore, the process of efficiently publishing the created RFP to multiple providers and collecting quotes and proposals is also cumbersome. Furthermore, even when simple customization is possible, there is a lack of support for users to understand and execute the procedure.

[1006] 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.

[1007] In this invention, the server includes a conversation means for collecting requirements through a dialogue with the user, a generation means for automatically generating a request for proposal by analyzing the collected information, a publishing and collection means for publishing the automatically generated request for proposal to multiple providers and collecting quotations and proposals from the providers, a display and selection means for presenting the collected quotations and proposals to the user and selecting the most suitable provider, a conversation means including automated vehicle customization information to support the generation of the request for proposal, and a DIY procedure presentation means for presenting a DIY procedure to the user based on the automated vehicle customization information. This allows the user to easily and efficiently collect and analyze automated vehicle customization requirements and receive quotations and proposals from appropriate providers. Furthermore, if the user can perform simple customization themselves, the procedure can be clearly guided.

[1008] A "user" is a person or organization that wishes to develop or customize a system or tool.

[1009] An "interactive means" is a mechanism for collecting requirements through communication with users, typically using AI to generate questions and obtain user answers.

[1010] A "generator" is a mechanism that analyzes the collected information and automatically generates a request for proposal (RFP) based on that information.

[1011] The "publication and collection means" is a mechanism for publishing the generated request for proposal to multiple providers and collecting quotations and proposals from the providers.

[1012] The "display and selection means" is a mechanism for presenting the collected quotes and proposals to the user and selecting the most suitable provider.

[1013] An "autonomous vehicle" is a vehicle equipped with autonomous driving technology that a user wishes to customize.

[1014] "Customization information" is information regarding specific changes or additional functions desired by the user.

[1015] The "DIY procedure presentation means" is a mechanism that presents the procedure to the user when simple customization can be performed by the user himself.

[1016] This invention provides a system that extracts user requirements for customizing an autonomous vehicle, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotations and proposals. To achieve this, the following hardware and software are used:

[1017] Hardware and software used

[1018] The system mainly uses the following hardware and software:

[1019] Hardware: Smartphone

[1020] software:

[1021] Interaction and generation: Python (Flask + GPT-4 API)

[1022] Notification and Collection: Firebase Cloud Messaging

[1023] Display and Selection: React Native

[1024] Fixes and instructions: JavaScript + HTML + CSS

[1025] System Overview

[1026] The system has the following main features:

[1027] 1. Means of interaction:

[1028] The server collects customization requests through dialogue with the user. This dialogue is carried out using a Flask-based web server and the GPT-4 API. When a user opens the smartphone app and creates a new customization project, the system generates initial questions, such as "Which part do you want to customize?", to obtain detailed requirements from the user.

[1029] 2. Generation means:

[1030] The server analyzes the information collected through the interactive means and automatically generates a request for proposal (RFP), using the GPT-4 API to automatically create an appropriate RFP template based on the collected requirements.

[1031] 3. Disclosure and collection methods:

[1032] The server publishes the generated RFP to multiple providers and uses Firebase Cloud Messaging to collect quotes and proposals. Providers are notified and can submit proposals through the system.

[1033] 4. Display and Selection Means:

[1034] The server displays the collected quotes and proposals to the user on a smartphone app using React Native, allowing the user to compare multiple proposals and select the best provider.

[1035] 5. DIY Instructions:

[1036] The server provides DIY instructions for simple customizations, showing users step-by-step how to customize the site themselves using JavaScript, HTML, and CSS.

[1037] Process example

[1038] Here, we will use a smartphone customization project for an autonomous vehicle as an example.

[1039] Examples:

[1040] 1. Means of interaction:

[1041] User: "I want to customize the interior of my self-driving car."

[1042] Server: "What specific parts would you like to customize?"

[1043] User: "I'd like to change the seat material. I'd also like to change the interior lighting."

[1044] 2. Generation means:

[1045] Server: Generates an RFP draft based on this information.

[1046] 3. Disclosure and collection methods:

[1047] Server: Notifies multiple providers of the generated RFP and collects proposals.

[1048] 4. Display and Selection Means:

[1049] Server: Displays the collected suggestions to the user.

[1050] User: Select the best offer.

[1051] 5. DIY Instructions:

[1052] Server: "You can also DIY the seat material change. Follow the steps below."

[1053] Prompt Sentence Examples

[1054] "When a user wants to customize an autonomous vehicle, we elicit the necessary requirements. The initial question is, 'What parts do you want to customize?' Based on the requirements collected, we generate a request for proposal (RFP) and notify the vendor."

[1055] This invention allows users to efficiently plan customization of autonomous vehicles and receive proposals from appropriate providers. It also supports users in carrying out the procedures themselves when simple customization is possible.

[1056] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1057] Step 1:

[1058] The server begins the initial interaction by having the user open the smartphone app and create a new customization project. The server uses the GPT-4 API to generate an initial question, asking the user, "What part do you want to customize?" The input in this step is information about the user's customization preferences, and the output is a specific request obtained from the user. The obtained request is stored in a database for further processing.

[1059] Step 2:

[1060] The server collects more detailed information based on the user's request information collected through the dialogue means. The server receives the user's answer, "I would like to change the seat material. I would also like to change the interior lights," as input, and generates follow-up questions related to those. For example, it asks questions such as, "What kind of material would you like to change?" or "Do you have any preferences regarding the color or brightness of the interior lights?" The output of this step is the additional detailed information obtained from the user.

[1061] Step 3:

[1062] The server uses the collected information to automatically generate a Request for Proposal (RFP) using an AI analysis module. The input of this step is all the collected user requirement information, and the output is the generated RFP draft. The RFP draft contains all the user's requests and specific requirements. The generated RFP is temporarily saved and used in the next step.

[1063] Step 4:

[1064] The server uses Firebase Cloud Messaging to notify multiple providers of the generated RFP. The input of this step is the RFP draft, and the output is notifications to providers. Providers who receive the notifications can submit proposals and quotes to the system. The server collects these proposals and stores them in a database.

[1065] Step 5:

[1066] The server displays the quotes and proposals received from providers to the user. React Native is used for the display. The input of this step is the collected quotes and proposals, and the output is a user interface that displays them. The user can compare the proposals through a smartphone app and select the best provider.

[1067] Step 6:

[1068] The user checks the contents of the request for proposal and enters corrections or additional requirements as necessary. The input for this step is the generated RFP draft and the user's new requirements, and the output is the revised RFP. The server notifies the proposal providers again and collects proposals again.

[1069] Step 7:

[1070] The server presents DIY instructions when simple customization is possible. Based on the user's request information, the server generates DIY instructions using JavaScript, HTML, and CSS and displays them to the user step by step. The input to this step is information about simple customization, and the output is specific DIY instructions.

[1071] This series of steps enables users to efficiently collect and analyze customization requirements for autonomous vehicles, receive proposals from appropriate providers, and also enables simple DIY customization.

[1072] 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.

[1073] This system extracts user requirements when a user wants to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotes and proposals. Furthermore, by combining it with an emotion engine that recognizes user emotions and optimizes the way dialogue and proposals are presented, a more user-friendly experience is provided.

[1074] System Overview

[1075] This system has the following main functions:

[1076] 1. Means of interaction

[1077] 2. Generation means

[1078] 3. Disclosure and collection methods

[1079] 4. Display and Selection Means

[1080] 5. Procedure Presentation Methods

[1081] 6. Remedies

[1082] 7. Emotion Engine

[1083] Explanation of program processing

[1084] 1. Means of interaction

[1085] A user accesses the system and creates a new project. The server launches an AI model to begin a dialogue with the user. The AI ​​generates an initial question, asking the user, "What kind of system or tool do you want?" The user then inputs a specific request (e.g., "Inventory management system").

[1086] 2. Emotion Engine

[1087] The server activates an emotion engine to analyze emotions from the user's voice and text. The AI ​​evaluates the user's emotions in real time and optimizes the content and tone of the dialogue. For example, if the user is feeling stressed, the system will shorten the questions.

[1088] 3. Generation means

[1089] The server analyzes the collected information and generates follow-up questions to gather more detailed information. The emotion engine considers the user's emotional state and asks questions in a way that minimizes the burden on the user. For example, questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[1090] 4. Procedure Presentation Method

[1091] If the collected information is relatively simple, the server will determine that "this requirement can be met with a simple tool." This function also integrates an emotion engine, which provides instructions based on the user's emotional state. For example, if the user is not anxious, detailed steps will be provided.

[1092] 5. Disclosure and Collection Methods

[1093] The generated RFP is sent to multiple providers by the server, who then view the RFP and submit quotes and proposals. The server then collects these quotes and proposals and prepares them for presentation to the user.

[1094] 6. Display and Selection Means

[1095] The collected estimates and suggestions are displayed to the user via the device. At this time, an emotion engine analyzes the user's emotions and presents information at the appropriate time. For example, it is designed to present important information when the user is relaxed.

[1096] 7. Remedies

[1097] The user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server receives this information and updates the RFP. During this process, the emotion engine monitors the user's state and provides appropriate feedback.

[1098] Specific examples

[1099] Example 1: Inventory management system requirements

[1100] User: "I want to create an inventory management system."

[1101] Server: "Would you like specific features in that inventory management system?"

[1102] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[1103] Server: "Okay. Is there anything else you need?"

[1104] If the user feels stressed, the server's emotion engine switches to a softer expression such as "Could you please tell me more about this?"

[1105] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[1106] User: Checks the RFP draft and presses the publish button.

[1107] Server: Posts the RFP to providers and collects proposals.

[1108] Example 2: Support for creating simple tools

[1109] User: "I want to automate my expense reports."

[1110] Server: "What features do you need?"

[1111] User: "I'd like it to automatically extract the amount from a photo of a receipt and enter it into a spreadsheet."

[1112] Server: "That functionality can be achieved using an Excel macro. Please follow these steps:"

[1113] The server monitors the user's emotional state and guides them through easy-to-understand steps.

[1114] The user follows the steps and creates a simple tool by themselves.

[1115] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. In addition, by combining it with an emotion engine, it is possible to efficiently and effectively collect requests and receive optimal proposals without causing stress to the user.

[1116] The processing flow will be explained below.

[1117] Step 1:

[1118] A user accesses the platform using a terminal and logs in. The user selects to create a new project and enters the project name and basic requirements (e.g., "Inventory Management System").

[1119] Step 2:

[1120] The server launches the AI ​​model and displays an initial question to the user, such as "What kind of system or tool do you want?"

[1121] Step 3:

[1122] The user inputs a specific request. For example, "I want to create an inventory management system."

[1123] Step 4:

[1124] The server's emotion engine analyzes the user's emotional state from their input and optimizes the conversation content to keep the conversation comfortable. If the user shows signs of anxiety or irritation, the server responds by presenting more specific questions in a softer tone.

[1125] Step 5:

[1126] The server's AI generates additional questions to gather more detailed information based on the user's input and the results of the emotion engine's analysis. For example, questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[1127] Step 6:

[1128] The user answers additional questions, for example, "I'd like real-time inventory updates and support for barcode scanners."

[1129] Step 7:

[1130] The server's AI analyzes the collected information and automatically fills in the request for proposal (RFP) template with information such as "real-time inventory management," "barcode compatibility," and "integrated inventory management for multiple warehouses."

[1131] Step 8:

[1132] The generated RFP draft is displayed on the terminal for the user to review. The user can enter corrections or additional requirements as needed, and the emotion engine will analyze the user's emotions and provide appropriate feedback.

[1133] Step 9:

[1134] The user finally checks the RFP draft and presses the publish button, which makes the RFP available to providers.

[1135] Step 10:

[1136] The server notifies multiple providers of the RFP and collects quotations and proposals from them.

[1137] Step 11:

[1138] The server organizes the collected estimates and proposals and presents them to the user via the device. At this time, the emotion engine analyzes the user's emotions and presents information at the appropriate time.

[1139] Step 12:

[1140] The user compares multiple quotes and proposals displayed and selects the most suitable provider.

[1141] Step 13:

[1142] The server notifies the selected provider and initiates the contract process.

[1143] Step 14:

[1144] If the collected information is relatively simple, the server's AI will determine that the requirements can be met with a simple tool and provide specific instructions, such as instructions for automating expense reimbursement sheets.

[1145] Step 15:

[1146] It supports users to create simple tools by following the steps. For example, it guides users step by step through the steps to create an Excel macro.

[1147] Example 2

[1148] 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."

[1149] In conventional systems, when a user requests the development of a system or tool, the process of accurately extracting requirements, creating a request for proposal (RFP), and collecting quotes and proposals from providers is cumbersome, placing a heavy burden on the user.In addition, since the effectiveness of the dialogue is affected by the user's emotional state, it is difficult to provide an appropriate interface.

[1150] 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.

[1151] In this invention, the server includes: an interaction means for collecting requirements through interaction with the user; an emotion engine for analyzing the user's emotions and optimizing the content and tone of the interaction; a generation means for automatically generating a request for proposal by analyzing the collected information; a publishing and collection means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers; and a display and selection means for presenting the collected estimates and proposals to the user and selecting the most suitable provider. This reduces the burden on the user, and makes it possible to efficiently and effectively collect requirements and receive the most suitable proposal.

[1152] The "interaction means" is a means for collecting requirements through interaction with the user.

[1153] An "emotion engine" is a means of analyzing a user's emotions and optimizing the content and tone of the dialogue.

[1154] The "generation means" is a means for automatically generating a request for proposal by analyzing the collected information.

[1155] The "publication and collection means" refers to a means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers.

[1156] The "display and selection means" is a means for presenting the collected estimates and proposals to the user and allowing the user to select the most suitable provider.

[1157] The "procedure presentation means" is a means for presenting a procedure for the user to create a system or tool by themselves when the collected information is relatively simple.

[1158] The "modification means" is a means for checking and modifying a request for proposal generated based on a user's request.

[1159] This system extracts user requirements when a user wants to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotes and proposals. Furthermore, by combining it with an emotion engine that recognizes user emotions and optimizes the way dialogue and proposals are presented, a more user-friendly experience is provided.

[1160] This system mainly uses the following hardware and software:

[1161] Hardware:

[1162] Server: A computer device that controls the entire system and processes data.

[1163] Terminal: The device from which the user accesses the site (PC, tablet, smartphone, etc.)

[1164] software:

[1165] Generative AI model: An AI model that gathers information through user interaction and automatically generates a request for proposal (RFP) (e.g., OpenAI GPT-4)

[1166] Emotion engine: An engine that analyzes user emotions in real time and optimizes the content and tone of conversations (e.g., Affectiva Emotion AI)

[1167] The operation of the system proceeds as follows.

[1168] First, when a user accesses the system to create a new project, the server launches the AI ​​model and begins a dialogue with the user. First, the AI ​​generates a question such as "What kind of system or tool do you want?" and poses the question to the user through a prompt. The user then enters the specific request, "Inventory management system."

[1169] The server then activates an emotion engine to analyze the user's emotions from their voice and text input. It evaluates their emotional state in real time and optimizes the content and tone of the dialogue. For example, if the user is feeling stressed, the AI ​​simplifies the question and displays a message saying, "Please let me know if you need a clearer explanation."

[1170] The server then analyzes the collected initial information and generates follow-up questions to gather more detailed information. The emotion engine considers the user's emotional state and generates questions that are displayed to the user in text format. For example, follow-up questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[1171] Based on the collected information, the server determines that the requirements for the inventory management system can be met with relatively simple tools and presents specific steps to the user. For example, detailed instructions are provided on how to set up a "real-time inventory update" function using an Excel macro, and the user can follow the steps to proceed.

[1172] The generated RFP is published by the server to multiple providers, who can view the RFP and submit quotes and proposals. The server collects these proposals in a database and stores them as data for the next step.

[1173] The collected suggestions are displayed to the user via the device. The emotion engine analyzes the user's emotional state and presents important information at the appropriate time. For example, detailed comparative information is provided when the user is relaxed.

[1174] Finally, the user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server receives this new information and updates the RFP. The emotion engine constantly monitors the user's state and provides appropriate feedback and guidance.

[1175] An example of a specific prompt might look like this:

[1176] Example 1: Inventory management system requirements

[1177] User: "I want to create an inventory management system."

[1178] Server: "Would you like specific features in that inventory management system?"

[1179] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[1180] Server: "Okay. Is there anything else you need?"

[1181] If the user feels stressed, the server's emotion engine switches to a softer expression, asking, "Could you please tell me more?"

[1182] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[1183] User: Checks the RFP draft and presses the publish button.

[1184] Server: Posts the RFP to providers and collects proposals.

[1185] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. In addition, by combining it with an emotion engine, it is possible to efficiently and effectively collect requests and receive optimal proposals without causing stress to the user.

[1186] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1187] Step 1:

[1188] A user accesses the system to create a new project. The user logs into the system's web interface using a terminal and clicks the Create New Project button. Input: User login information and project creation action. Output: A request to create a new project is sent to the server.

[1189] Step 2:

[1190] The server launches an AI model (e.g., a generative AI model) and begins a dialogue with the user. The server generates an initial question (e.g., "What kind of system or tool do you want?") and presents it to the user as a prompt. Input: A request to create a new project. Output: A prompt for the initial question to the user.

[1191] Step 3:

[1192] The user inputs a specific request (e.g., "inventory management system") in response to the initial question. The user inputs the answer using a terminal and sends it to the server. Input: User's answer. Output: The user's specific request is sent to the server.

[1193] Step 4:

[1194] The server launches an emotion engine to analyze emotions from the text entered by the user. The emotion engine analyzes the text data and evaluates the user's emotional state (e.g., stress, anxiety, etc.). Input: User's text response. Output: Analyzed emotion data.

[1195] Step 5:

[1196] The server generates follow-up questions taking into account the user's emotional state. To gather more detailed information, the server generates the next question (e.g., "Do you want to manage inventory in real time?") based on the output of the emotion engine. Input: User's emotional data. Output: Generation and presentation of follow-up questions.

[1197] Step 6:

[1198] The user answers the follow-up questions and provides detailed information. For example, answer "Yes" to "Do you want to manage inventory in real time?" Input: User's answer to the follow-up question. Output: Detailed information is sent to the server.

[1199] Step 7:

[1200] The server analyzes the collected information and automatically generates the required Request for Proposal (RFP) draft. Based on the collected details, the RFP draft is generated and created in a user-friendly format based on the output of the emotion engine. Input: User's detailed information. Output: Generated RFP draft.

[1201] Step 8:

[1202] The server publishes the generated RFP draft to multiple providers. The server sends notifications to providers and provides them with links to access the RFP draft. Input: Generated RFP draft. Output: Notifications and links sent to providers.

[1203] Step 9:

[1204] Provider views the RFP, creates a quote or proposal, and sends it to the server. Provider clicks on a link to view the RFP, enters a proposal or quote, and submits it. Input: Provider's proposal and quote. Output: Proposal and quote sent to the server.

[1205] Step 10:

[1206] The server stores the collected quotes and proposals in a database and prepares them to be presented to the user. The server organizes the information and lists it in a format that is easy for the user to understand. Input: Proposals and quotes from providers. Output: Information prepared for presentation to the user.

[1207] Step 11:

[1208] The user reviews the proposals and quotes through the terminal and selects the most suitable provider. The emotion engine monitors the user's emotional state and presents information at the appropriate time. Input: List of proposals and quotes. Output: User's provider selection.

[1209] Step 12:

[1210] The user reviews the generated RFP draft and enters any necessary corrections or additional requirements. The server receives the new information and updates the RFP. The emotion engine provides feedback and the updated RFP is available for the user to review. Input: Revised RFP draft and additional requirements. Output: Updated RFP.

[1211] In this way, through specific processing steps, the system can collect user requests, efficiently generate a request for proposal, and receive optimal proposals.

[1212] (Application example 2)

[1213] 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."

[1214] When users wish to develop new systems or tools, they need to be able to effectively extract their requirements and quickly and accurately create a request for proposal (RFP). However, conventional methods place a heavy burden on users, often resulting in emotional stress. It is also difficult to properly publish the generated RFP and reliably collect quotes and proposals from suppliers. Furthermore, for efficient operation within factories, integration with devices such as smart glasses is also important. A system that can solve these issues is needed.

[1215] The specification processing by the specification 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: a dialogue means for collecting requirements through dialogue with the user; a generation means for automatically generating a request for proposal by analyzing the collected information; a publication and collection means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers; a display and selection means for presenting the collected estimates and proposals to the user and selecting the most appropriate provider; an emotion analysis means for analyzing the user's emotions and optimizing the tone of the dialogue and the presentation of information; and a display device linkage means for providing an interface via a device worn by the user. This makes it possible to efficiently generate an RFP and collect proposals from appropriate providers while reducing stress on the user.

[1216] "User" refers to the entity that uses a system or device, typically a human operator.

[1217] "Dialogue means" refers to a function for gathering requests and information through conversation with the user.

[1218] "Generation means" refers to the functionality for analyzing collected information and automatically generating a request for proposal (RFP).

[1219] "Publication and collection means" refers to a function for publishing the generated request for proposal to multiple providers and collecting estimates and proposals from the providers.

[1220] "Display and selection means" refers to a function for presenting collected estimates and proposals to the user and allowing the user to select the most suitable provider.

[1221] "Emotion analysis means" refers to a function that analyzes the user's voice and facial expressions in real time to optimize the tone of the conversation and the presentation of information.

[1222] "Display device linking means" refers to a function for providing an interface via a device worn by a user (e.g., smart glasses).

[1223] A "Request for Proposal (RFP)" is a document that clearly states the user's requirements and specifications and requests quotes and proposals from providers.

[1224] "Provider" refers to the entity that provides an estimate or proposal based on a Request for Proposal.

[1225] "Collected Information" refers to specific details of your requests and desires obtained through your interactions with us.

[1226] To implement the invention, the system includes the following major functions:

[1227] Hardware and Software Use

[1228] Hardware: Smart glasses, factory server

[1229] Software: Sentiment analysis API (e.g., IBM Watson Emotion Analysis), dialogue generation models (e.g., GPT-4), cloud RFP management system

[1230] System Overview

[1231] The system provides an interface using smart glasses worn by the user. Each of the means will be described in detail below.

[1232] User interaction methods

[1233] First, the user puts on the smart glasses and accesses the system. The system then activates the voice assistant built into the smart glasses and starts a dialogue with the user. The following is an example of a specific dialogue:

[1234] Voice Assistant: "I'm starting a new project. What systems and tools would you like to use?"

[1235] User: "I want to build a robotic control system for a new assembly line."

[1236] Emotion analysis means

[1237] The system then uses the smart glasses' camera and microphone to analyze the user's voice and facial expressions in real time, and an emotion analysis API assesses the user's emotional state and optimizes the tone of the dialogue and the way information is presented based on this.

[1238] Example: If the user's stress level is assessed as high, the voice assistant will provide additional information such as, "Don't worry, we'll take it easy and proceed slowly."

[1239] Request for Proposal (RFP) generation tools

[1240] Based on the collected information, the dialogue generation model (GPT-4) generates detailed questions and gathers further information. Throughout this process, the sentiment analysis tool continues to operate, reducing the burden on the user.

[1241] Example prompt sentence:

[1242] "Do you want real-time updates?"

[1243] "How do you deal with barcode scanners?"

[1244] "Are there any special safety considerations?"

[1245] Publication and collection methods

[1246] The generated RFP is uploaded to a cloud RFP management system via an in-factory server and notified to multiple providers. The quotes and proposals from the providers are collected by the cloud system and displayed on the smart glasses screen.

[1247] Display and Selection Means

[1248] The collected quotes and proposals are presented to the user through the smart glasses for review and selection of the most suitable provider, with the user making selections and modifications using voice commands.

[1249] Example: The user confirms and then gives a voice command saying, "Please correct this part." The system then reflects the correction and re-sends the RFP to the provider.

[1250] The system allows users to efficiently generate RFPs and receive proposals from suitable providers with minimal stress.

[1251] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1252] Step 1:

[1253] The server launches the voice assistant in the smart glasses and asks the user, "I'm starting a new project. What kind of system and tools would you like?" The user replies, "I want to build a robotic control system for a new assembly line." This collects the initial requirements.

[1254] Input: User voice input

[1255] Output: Initial request data

[1256] Step 2:

[1257] The server analyzes the user's voice and facial expressions in real time using the smart glasses' camera and microphone, and evaluates the user's emotional state using an emotion analysis API (e.g., IBM Watson Emotion Analysis). The server then optimizes the tone of the dialogue and the way information is presented depending on the user's emotional state.

[1258] Input: User audio and video data

[1259] Output: User's emotional state data

[1260] Step 3:

[1261] The server uses a generative AI model (e.g., GPT-4) to generate detailed questions based on the collected initial request data and emotional state data. The questions are presented to the user through the smart glasses, and the user's answers are collected.

[1262] Input: Initial request data, emotional state data

[1263] Output: Detailed question data, user response data

[1264] Step 4:

[1265] The server automatically generates a Request for Proposal (RFP) based on all the collected information. It uses a generative AI model to analyze the input data and create a specific RFP document, which is then displayed on the smart glasses' display.

[1266] Input: User response data

[1267] Output: Request for Proposal (RFP) draft

[1268] Step 5:

[1269] The user checks the RFP draft displayed on the smart glasses display and makes any necessary corrections using voice commands. The server receives these correction instructions and updates the RFP draft.

[1270] Input: User correction instructions

[1271] Output: Updated RFP draft

[1272] Step 6:

[1273] The server uploads the completed RFP to a cloud RFP management system and notifies multiple providers. It also collects quotes and proposals from the providers. The proposal data collected by the cloud system is presented to the user through the smart glasses display.

[1274] Input: Updated RFP draft

[1275] Output: Quotation and proposal data from providers

[1276] Step 7:

[1277] The user reviews the quotes and proposals presented on the smart glasses display and selects the best provider using voice commands. The server records this selection data and completes the RFP process.

[1278] Input: Quote and proposal data from providers, user selection data

[1279] Output: Selection data for the best provider

[1280] 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.

[1281] 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.

[1282] 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.

[1283] [Fourth embodiment]

[1284] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1285] 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.

[1286] 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).

[1287] 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.

[1288] 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.

[1289] 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).

[1290] 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.

[1291] 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.

[1292] 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.

[1293] 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.

[1294] 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.

[1295] 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.

[1296] 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."

[1297] This invention relates to a system that extracts requirements from users who wish to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotations and proposals. This invention enables improved business efficiency and advanced business management.

[1298] System Overview

[1299] This system has the following main functions:

[1300] 1. Means of interaction

[1301] 2. Generation means

[1302] 3. Disclosure and collection methods

[1303] 4. Display and Selection Means

[1304] 5. Procedure Presentation Methods

[1305] 6. Remedies

[1306] Explanation of program processing

[1307] 1. Means of interaction

[1308] A user accesses the system and creates a new project. The server launches an AI model to begin a dialogue with the user. The AI ​​generates an initial question, asking the user, "What kind of system or tool do you want?" The user then inputs a specific request (e.g., "Inventory management system").

[1309] 2. Generation means

[1310] The server analyzes the collected information and continues to ask questions to gather more detailed information. For example, if a user requests an "inventory management system," they will include specific requirements such as "real-time inventory management," "barcode scanning support," and "integrated inventory management for multiple warehouses." Based on this information, the AI ​​automatically fills in the information in a request for proposal (RFP) template.

[1311] 3. Disclosure and collection methods

[1312] The generated RFP is registered in the system by the server and notified to multiple providers. The providers view the RFP and submit quotations and proposals. The server collects these quotations and proposals and prepares them for presentation to the user.

[1313] 4. Display and Selection Means

[1314] The collected quotes and proposals are presented to the user via the terminal. The user compares and considers multiple proposals and selects the most suitable provider. Once the selection is complete, the server notifies the selected provider and proceeds with the contract procedure.

[1315] 5. Procedure Presentation Methods

[1316] If the collected information is relatively simple, the server's AI will determine that "this requirement can be met with a simple tool." In this case, the server will present specific steps and support the user in creating the tool themselves. For example, if automating expense reimbursement sheets, it will provide step-by-step instructions on how to use Excel and macros.

[1317] 6. Remedies

[1318] The user can review the generated RFP draft and enter any necessary corrections or additions. The server receives this information and updates the RFP.

[1319] Specific examples

[1320] Example 1: Inventory management system requirements

[1321] User: "I want to create an inventory management system."

[1322] Server: "Would you like specific features in that inventory management system?"

[1323] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[1324] Server: "Okay. Is there anything else you need?"

[1325] User: "I want to manage inventory across multiple warehouses."

[1326] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[1327] User: Checks the RFP draft and presses the publish button.

[1328] Server: Posts the RFP to providers and collects proposals.

[1329] Example 2: Support for creating simple tools

[1330] User: "I want to automate my expense reports."

[1331] Server: "What features do you need?"

[1332] User: "I'd like it to automatically extract the amount from a photo of a receipt and enter it into a spreadsheet."

[1333] Server: "That functionality can be achieved using an Excel macro. Please follow these steps:"

[1334] The server displays the steps for creating an Excel macro, and the user follows the steps to create the program.

[1335] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. It also supports the creation of simple tools to help small and medium-sized enterprises and individuals improve their business efficiency.

[1336] The processing flow will be explained below.

[1337] Step 1:

[1338] A user accesses the platform using a terminal and logs in. The user selects to create a new project and enters the project name and basic requirements (e.g., "Inventory Management System").

[1339] Step 2:

[1340] The server launches the AI ​​model and displays an initial question to the user, such as "What kind of system or tool do you want?"

[1341] Step 3:

[1342] The user inputs a specific request. For example, "I want to create an inventory management system."

[1343] Step 4:

[1344] The server's AI generates additional questions to gather more information based on the user's input, such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?"

[1345] Step 5:

[1346] The user answers additional questions, for example, "I'd like real-time inventory updates and support for barcode scanners."

[1347] Step 6:

[1348] The server's AI analyzes the collected information and automatically fills in the request for proposal (RFP) template with information such as "real-time inventory management," "barcode compatibility," and "integrated inventory management for multiple warehouses."

[1349] Step 7:

[1350] The generated RFP draft is displayed on the terminal for the user to review, and the user can enter corrections or additional requirements as necessary.

[1351] Step 8:

[1352] The user finally checks the RFP draft and presses the publish button, which makes the RFP available to providers.

[1353] Step 9:

[1354] The server notifies multiple providers of the RFP and collects quotations and proposals from them.

[1355] Step 10:

[1356] The server organizes the collected estimates and proposals and presents them to the user via the terminal.

[1357] Step 11:

[1358] The user compares multiple quotes and proposals displayed and selects the most suitable provider.

[1359] Step 12:

[1360] The server notifies the selected provider and initiates the contract process.

[1361] Step 13:

[1362] If the collected information is relatively simple, the server's AI will determine that the requirements can be met with a simple tool and provide specific instructions, such as instructions for automating expense reimbursement sheets.

[1363] Step 14:

[1364] It supports users to create simple tools by following the steps. For example, it guides users step by step through the steps to create an Excel macro.

[1365] Example 1

[1366] 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."

[1367] In conventional system development, it takes a great deal of time and effort for users to clarify their requirements and convert them into a request for proposal (RFP). Collecting quotes and proposals from multiple suppliers and selecting the most suitable provider is also complicated. Furthermore, creating simple tools on your own presents high technical hurdles, making it difficult for small and medium-sized enterprises and individuals to easily improve business efficiency.

[1368] 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.

[1369] In this invention, the server includes an interactive means, a generating means, a publishing and collecting means, a display and selecting means, and a procedure presenting means. This allows a user wishing to develop a system or tool to interactively collect the necessary information, automatically generate a request for proposal, and present it to multiple suppliers. Furthermore, when creating a simple tool, specific procedures are presented, improving work efficiency.

[1370] "Interaction means" refers to the interactive interface used by the user to access the system and to gather information between the user and the server.

[1371] "Generation means" refers to the functionality for analyzing collected information and automatically generating a request for proposal (RFP).

[1372] "Publication and collection means" refers to a function for publishing an automatically generated request for proposal to multiple suppliers and collecting quotations and proposals from the suppliers.

[1373] "Display and selection means" refers to a function that presents collected quotes and proposals to the user and enables the user to select the most suitable supplier.

[1374] The "procedure presentation means" refers to a function for presenting specific procedures and providing support when a user wishes to create a simple tool.

[1375] The "modification means" refers to a function for checking and modifying a request for proposal generated based on a user's request.

[1376] This system extracts requirements when a user wishes to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple suppliers to collect quotations and proposals. It also supports the creation of simple tools, improving business efficiency and providing advanced business management.

[1377] System Overview

[1378] This system has the following main functions:

[1379] Interaction methods

[1380] A user accesses the system and creates a new project. The server launches the generative AI model and begins a dialogue with the user. First, the server generates a prompt asking, "What kind of system or tool do you want?" and displays it to the user via the terminal. The user then inputs their specific request, for example, "Inventory management system."

[1381] generation means

[1382] The server analyzes the information provided by the user and automatically generates questions to gather more detailed information. For example, it checks specific requirements such as "real-time inventory management," "barcode scanning support," and "integrated inventory management across multiple warehouses." Based on this information, the server automatically inputs the information into a request for proposal (RFP) template.

[1383] Publication and collection methods

[1384] The generated RFP is registered in the system by the server and notified to multiple suppliers. Suppliers can view the RFP and submit quotations and proposals. The server collects, organizes, and stores these proposals.

[1385] Display and Selection Means

[1386] The collected quotes and proposals are presented to the user via the terminal. The user compares multiple proposals and selects the most suitable supplier. After the selection, the server notifies the selected supplier and proceeds with the contract procedure.

[1387] Procedure presentation method

[1388] If a user wants to create a simple tool, the server's generative AI model will provide specific instructions, such as "How to automate an expense report sheet using an Excel macro," and help the user create the tool by following the instructions.

[1389] Correction means

[1390] The user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server updates the RFP with this information.

[1391] Specific examples

[1392] Example 1: Inventory management system requirements

[1393] 1. User: "I want to create an inventory management system."

[1394] 2. Server: "Would you like specific features in that inventory management system?"

[1395] 3. User: "I want to update inventory in real time. I also want it to be compatible with barcode scanners."

[1396] 4. Server: "Okay. Is there anything else you need?"

[1397] 5. User: "I want to manage inventory across multiple warehouses."

[1398] 6. Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[1399] 7. User: Checks the RFP draft and presses the publish button.

[1400] 8. Server: Notifies suppliers of the RFP and collects proposals.

[1401] Example 2: Support for creating simple tools

[1402] 1. User: "I want to automate my expense report."

[1403] 2. Server: "What features do you need?"

[1404] 3. User: "I'd like the amount to be automatically extracted from a photo of a receipt and entered into a spreadsheet."

[1405] 4. Server: "That functionality can be achieved using an Excel macro. Please follow the steps below."

[1406] 5. The server displays the step-by-step instructions for creating an Excel macro, and the user follows them to write the program.

[1407] This system allows users to easily request the development of systems and tools, and efficiently collect and compare quotes and proposals from multiple suppliers.It also provides specific procedures for creating simple tools, helping to improve the efficiency of work for small and medium-sized enterprises and individuals.

[1408] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1409] Step 1: Create a project and start interacting

[1410] A user accesses the system and clicks the "Create a new project" button. This input is sent to the server. The server receives this action and launches a generative AI model. The server generates the initial prompt, "What kind of system or tool do you want?", and displays it to the user via the terminal. The user's response (e.g., inventory management system) is received as input.

[1411] Step 2: Refine your requirements

[1412] The server analyzes the user's responses and uses a generative AI model to create follow-up questions to gather more detailed information. For example, detailed questions such as "Do you manage inventory in real time?" or "Do you support barcode scanning?" are generated and displayed to the user via their device. The user answers these questions, and the answers are sent to the server as input data. The server accumulates this data and collects more detailed information for the RFP template.

[1413] Step 3: Generate an RFP

[1414] The server automatically generates an RFP draft based on the collected information. The input data is the collected user's request details, which are analyzed and automatically embedded in a request for proposal template. The generated RFP draft is displayed to the user via their terminal. The user checks the contents and makes corrections as necessary. This confirmation and correction information is also sent to the server as input data.

[1415] Step 4: Publish the RFP

[1416] The user checks the generated RFP draft and clicks the "Publish" button. This input causes the server to register the RFP in the system and send notifications to multiple suppliers. Suppliers view the RFP and send quotations and proposals to the server. These proposals are collected, organized, and stored by the server.

[1417] Step 5: Collect and display suggestions

[1418] The server organizes the collected estimates and proposals, presents them to the user as a list via the terminal, and provides the user with the information they need to compare proposals. The user then compares the proposals from each provider and enters the information to select the most suitable provider.

[1419] Step 6: Selection and notification of the best proposal

[1420] The user selects the best proposal and clicks a button to confirm the selection. Upon receiving this input, the server notifies the selected provider and initiates the contract process. At the same time, it notifies other suppliers of the selection result.

[1421] Step 7: Support for creating simple tools

[1422] When a user wants to create a simple tool (e.g., to automate expense reports), the generative AI model on the server presents specific steps to the user. For example, the generative AI model creates a step-by-step guide to "How to automate expense reports using Excel macros" and displays it to the user via their device. The user then follows the steps to create the tool.

[1423] The above is the flow of processing steps and specific operations in this system.

[1424] (Application example 1)

[1425] 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."

[1426] In today's world, when a user wishes to customize an autonomous vehicle, it is difficult to efficiently gather specific requirements and create an appropriate request for proposal (RFP). Conventional systems require users to consider detailed technical specifications themselves, which requires a lot of time and effort. Furthermore, the process of efficiently publishing the created RFP to multiple providers and collecting quotes and proposals is also cumbersome. Furthermore, even when simple customization is possible, there is a lack of support for users to understand and execute the procedure.

[1427] 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.

[1428] In this invention, the server includes a conversation means for collecting requirements through a dialogue with the user, a generation means for automatically generating a request for proposal by analyzing the collected information, a publishing and collection means for publishing the automatically generated request for proposal to multiple providers and collecting quotations and proposals from the providers, a display and selection means for presenting the collected quotations and proposals to the user and selecting the most suitable provider, a conversation means including automated vehicle customization information to support the generation of the request for proposal, and a DIY procedure presentation means for presenting a DIY procedure to the user based on the automated vehicle customization information. This allows the user to easily and efficiently collect and analyze automated vehicle customization requirements and receive quotations and proposals from appropriate providers. Furthermore, if the user can perform simple customization themselves, the procedure can be clearly guided.

[1429] A "user" is a person or organization that wishes to develop or customize a system or tool.

[1430] An "interactive means" is a mechanism for collecting requirements through communication with users, typically using AI to generate questions and obtain user answers.

[1431] A "generator" is a mechanism that analyzes the collected information and automatically generates a request for proposal (RFP) based on that information.

[1432] The "publication and collection means" is a mechanism for publishing the generated request for proposal to multiple providers and collecting quotations and proposals from the providers.

[1433] The "display and selection means" is a mechanism for presenting the collected quotes and proposals to the user and selecting the most suitable provider.

[1434] An "autonomous vehicle" is a vehicle equipped with autonomous driving technology that a user wishes to customize.

[1435] "Customization information" is information regarding specific changes or additional functions desired by the user.

[1436] The "DIY procedure presentation means" is a mechanism that presents the procedure to the user when simple customization can be performed by the user himself.

[1437] This invention provides a system that extracts user requirements for customizing an autonomous vehicle, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotations and proposals. To achieve this, the following hardware and software are used:

[1438] Hardware and software used

[1439] The system mainly uses the following hardware and software:

[1440] Hardware: Smartphone

[1441] software:

[1442] Interaction and generation: Python (Flask + GPT-4 API)

[1443] Notification and Collection: Firebase Cloud Messaging

[1444] Display and Selection: React Native

[1445] Fixes and instructions: JavaScript + HTML + CSS

[1446] System Overview

[1447] The system has the following main features:

[1448] 1. Means of interaction:

[1449] The server collects customization requests through dialogue with the user. This dialogue is carried out using a Flask-based web server and the GPT-4 API. When a user opens the smartphone app and creates a new customization project, the system generates initial questions, such as "Which part do you want to customize?", to obtain detailed requirements from the user.

[1450] 2. Generation means:

[1451] The server analyzes the information collected through the interactive means and automatically generates a request for proposal (RFP), using the GPT-4 API to automatically create an appropriate RFP template based on the collected requirements.

[1452] 3. Disclosure and collection methods:

[1453] The server publishes the generated RFP to multiple providers and uses Firebase Cloud Messaging to collect quotes and proposals. Providers are notified and can submit proposals through the system.

[1454] 4. Display and Selection Means:

[1455] The server displays the collected quotes and proposals to the user on a smartphone app using React Native, allowing the user to compare multiple proposals and select the best provider.

[1456] 5. DIY Instructions:

[1457] The server provides DIY instructions for simple customizations, showing users step-by-step how to customize the site themselves using JavaScript, HTML, and CSS.

[1458] Process example

[1459] Here, we will use a smartphone customization project for an autonomous vehicle as an example.

[1460] Examples:

[1461] 1. Means of interaction:

[1462] User: "I want to customize the interior of my self-driving car."

[1463] Server: "What specific parts would you like to customize?"

[1464] User: "I'd like to change the seat material. I'd also like to change the interior lighting."

[1465] 2. Generation means:

[1466] Server: Generates an RFP draft based on this information.

[1467] 3. Disclosure and collection methods:

[1468] Server: Notifies multiple providers of the generated RFP and collects proposals.

[1469] 4. Display and Selection Means:

[1470] Server: Displays the collected suggestions to the user.

[1471] User: Select the best offer.

[1472] 5. DIY Instructions:

[1473] Server: "You can also DIY the seat material change. Follow the steps below."

[1474] Prompt Sentence Examples

[1475] "When a user wants to customize an autonomous vehicle, we elicit the necessary requirements. The initial question is, 'What parts do you want to customize?' Based on the requirements collected, we generate a request for proposal (RFP) and notify the vendor."

[1476] This invention allows users to efficiently plan customization of autonomous vehicles and receive proposals from appropriate providers. It also supports users in carrying out the procedures themselves when simple customization is possible.

[1477] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1478] Step 1:

[1479] The server begins the initial interaction by having the user open the smartphone app and create a new customization project. The server uses the GPT-4 API to generate an initial question, asking the user, "What part do you want to customize?" The input in this step is information about the user's customization preferences, and the output is a specific request obtained from the user. The obtained request is stored in a database for further processing.

[1480] Step 2:

[1481] The server collects more detailed information based on the user's request information collected through the dialogue means. The server receives the user's answer, "I would like to change the seat material. I would also like to change the interior lights," as input, and generates follow-up questions related to those. For example, it asks questions such as, "What kind of material would you like to change?" or "Do you have any preferences regarding the color or brightness of the interior lights?" The output of this step is the additional detailed information obtained from the user.

[1482] Step 3:

[1483] The server uses the collected information to automatically generate a Request for Proposal (RFP) using an AI analysis module. The input of this step is all the collected user requirement information, and the output is the generated RFP draft. The RFP draft contains all the user's requests and specific requirements. The generated RFP is temporarily saved and used in the next step.

[1484] Step 4:

[1485] The server uses Firebase Cloud Messaging to notify multiple providers of the generated RFP. The input of this step is the RFP draft, and the output is notifications to providers. Providers who receive the notifications can submit proposals and quotes to the system. The server collects these proposals and stores them in a database.

[1486] Step 5:

[1487] The server displays the quotes and proposals received from providers to the user. React Native is used for the display. The input of this step is the collected quotes and proposals, and the output is a user interface that displays them. The user can compare the proposals through a smartphone app and select the best provider.

[1488] Step 6:

[1489] The user checks the contents of the request for proposal and enters corrections or additional requirements as necessary. The input for this step is the generated RFP draft and the user's new requirements, and the output is the revised RFP. The server notifies the proposal providers again and collects proposals again.

[1490] Step 7:

[1491] The server presents DIY instructions when simple customization is possible. Based on the user's request information, the server generates DIY instructions using JavaScript, HTML, and CSS and displays them to the user step by step. The input to this step is information about simple customization, and the output is specific DIY instructions.

[1492] This series of steps enables users to efficiently collect and analyze customization requirements for autonomous vehicles, receive proposals from appropriate providers, and also enables simple DIY customization.

[1493] 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.

[1494] This system extracts user requirements when a user wants to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotes and proposals. Furthermore, by combining it with an emotion engine that recognizes user emotions and optimizes the way dialogue and proposals are presented, a more user-friendly experience is provided.

[1495] System Overview

[1496] This system has the following main functions:

[1497] 1. Means of interaction

[1498] 2. Generation means

[1499] 3. Disclosure and collection methods

[1500] 4. Display and Selection Means

[1501] 5. Procedure Presentation Methods

[1502] 6. Remedies

[1503] 7. Emotion Engine

[1504] Explanation of program processing

[1505] 1. Means of interaction

[1506] A user accesses the system and creates a new project. The server launches an AI model to begin a dialogue with the user. The AI ​​generates an initial question, asking the user, "What kind of system or tool do you want?" The user then inputs a specific request (e.g., "Inventory management system").

[1507] 2. Emotion Engine

[1508] The server activates an emotion engine to analyze emotions from the user's voice and text. The AI ​​evaluates the user's emotions in real time and optimizes the content and tone of the dialogue. For example, if the user is feeling stressed, the system will shorten the questions.

[1509] 3. Generation means

[1510] The server analyzes the collected information and generates follow-up questions to gather more detailed information. The emotion engine considers the user's emotional state and asks questions in a way that minimizes the burden on the user. For example, questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[1511] 4. Procedure Presentation Method

[1512] If the collected information is relatively simple, the server will determine that "this requirement can be met with a simple tool." This function also integrates an emotion engine, which provides instructions based on the user's emotional state. For example, if the user is not anxious, detailed steps will be provided.

[1513] 5. Disclosure and Collection Methods

[1514] The generated RFP is sent to multiple providers by the server, who then view the RFP and submit quotes and proposals. The server then collects these quotes and proposals and prepares them for presentation to the user.

[1515] 6. Display and Selection Means

[1516] The collected estimates and suggestions are displayed to the user via the device. At this time, an emotion engine analyzes the user's emotions and presents information at the appropriate time. For example, it is designed to present important information when the user is relaxed.

[1517] 7. Remedies

[1518] The user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server receives this information and updates the RFP. During this process, the emotion engine monitors the user's state and provides appropriate feedback.

[1519] Specific examples

[1520] Example 1: Inventory management system requirements

[1521] User: "I want to create an inventory management system."

[1522] Server: "Would you like specific features in that inventory management system?"

[1523] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[1524] Server: "Okay. Is there anything else you need?"

[1525] If the user feels stressed, the server's emotion engine switches to a softer expression such as "Could you please tell me more about this?"

[1526] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[1527] User: Checks the RFP draft and presses the publish button.

[1528] Server: Posts the RFP to providers and collects proposals.

[1529] Example 2: Support for creating simple tools

[1530] User: "I want to automate my expense reports."

[1531] Server: "What features do you need?"

[1532] User: "I'd like it to automatically extract the amount from a photo of a receipt and enter it into a spreadsheet."

[1533] Server: "That functionality can be achieved using an Excel macro. Please follow these steps:"

[1534] The server monitors the user's emotional state and guides them through easy-to-understand steps.

[1535] The user follows the steps and creates a simple tool by themselves.

[1536] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. In addition, by combining it with an emotion engine, it is possible to efficiently and effectively collect requests and receive optimal proposals without causing stress to the user.

[1537] The processing flow will be explained below.

[1538] Step 1:

[1539] A user accesses the platform using a terminal and logs in. The user selects to create a new project and enters the project name and basic requirements (e.g., "Inventory Management System").

[1540] Step 2:

[1541] The server launches the AI ​​model and displays an initial question to the user, such as "What kind of system or tool do you want?"

[1542] Step 3:

[1543] The user inputs a specific request. For example, "I want to create an inventory management system."

[1544] Step 4:

[1545] The server's emotion engine analyzes the user's emotional state from their input and optimizes the conversation content to keep the conversation comfortable. If the user shows signs of anxiety or irritation, the server responds by presenting more specific questions in a softer tone.

[1546] Step 5:

[1547] The server's AI generates additional questions to gather more detailed information based on the user's input and the results of the emotion engine's analysis. For example, questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[1548] Step 6:

[1549] The user answers additional questions, for example, "I'd like real-time inventory updates and support for barcode scanners."

[1550] Step 7:

[1551] The server's AI analyzes the collected information and automatically fills in the request for proposal (RFP) template with information such as "real-time inventory management," "barcode compatibility," and "integrated inventory management for multiple warehouses."

[1552] Step 8:

[1553] The generated RFP draft is displayed on the terminal for the user to review. The user can enter corrections or additional requirements as needed, and the emotion engine will analyze the user's emotions and provide appropriate feedback.

[1554] Step 9:

[1555] The user finally checks the RFP draft and presses the publish button, which makes the RFP available to providers.

[1556] Step 10:

[1557] The server notifies multiple providers of the RFP and collects quotations and proposals from them.

[1558] Step 11:

[1559] The server organizes the collected estimates and proposals and presents them to the user via the device. At this time, the emotion engine analyzes the user's emotions and presents information at the appropriate time.

[1560] Step 12:

[1561] The user compares multiple quotes and proposals displayed and selects the most suitable provider.

[1562] Step 13:

[1563] The server notifies the selected provider and initiates the contract process.

[1564] Step 14:

[1565] If the collected information is relatively simple, the server's AI will determine that the requirements can be met with a simple tool and provide specific instructions, such as instructions for automating expense reimbursement sheets.

[1566] Step 15:

[1567] It supports users to create simple tools by following the steps. For example, it guides users step by step through the steps to create an Excel macro.

[1568] Example 2

[1569] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1570] In conventional systems, when a user requests the development of a system or tool, the process of accurately extracting requirements, creating a request for proposal (RFP), and collecting quotes and proposals from providers is cumbersome, placing a heavy burden on the user.In addition, since the effectiveness of the dialogue is affected by the user's emotional state, it is difficult to provide an appropriate interface.

[1571] 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.

[1572] In this invention, the server includes: an interaction means for collecting requirements through interaction with the user; an emotion engine for analyzing the user's emotions and optimizing the content and tone of the interaction; a generation means for automatically generating a request for proposal by analyzing the collected information; a publishing and collection means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers; and a display and selection means for presenting the collected estimates and proposals to the user and selecting the most suitable provider. This reduces the burden on the user, and makes it possible to efficiently and effectively collect requirements and receive the most suitable proposal.

[1573] The "interaction means" is a means for collecting requirements through interaction with the user.

[1574] An "emotion engine" is a means of analyzing a user's emotions and optimizing the content and tone of the dialogue.

[1575] The "generation means" is a means for automatically generating a request for proposal by analyzing the collected information.

[1576] The "publication and collection means" refers to a means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers.

[1577] The "display and selection means" is a means for presenting the collected estimates and proposals to the user and allowing the user to select the most suitable provider.

[1578] The "procedure presentation means" is a means for presenting a procedure for the user to create a system or tool by themselves when the collected information is relatively simple.

[1579] The "modification means" is a means for checking and modifying a request for proposal generated based on a user's request.

[1580] This system extracts user requirements when a user wants to develop a system or tool, automatically creates a request for proposal (RFP), and publishes it to multiple providers to collect quotes and proposals. Furthermore, by combining it with an emotion engine that recognizes user emotions and optimizes the way dialogue and proposals are presented, a more user-friendly experience is provided.

[1581] This system mainly uses the following hardware and software:

[1582] Hardware:

[1583] Server: A computer device that controls the entire system and processes data.

[1584] Terminal: The device from which the user accesses the site (PC, tablet, smartphone, etc.)

[1585] software:

[1586] Generative AI model: An AI model that gathers information through user interaction and automatically generates a request for proposal (RFP) (e.g., OpenAI GPT-4)

[1587] Emotion engine: An engine that analyzes user emotions in real time and optimizes the content and tone of conversations (e.g., Affectiva Emotion AI)

[1588] The operation of the system proceeds as follows.

[1589] First, when a user accesses the system to create a new project, the server launches the AI ​​model and begins a dialogue with the user. First, the AI ​​generates a question such as "What kind of system or tool do you want?" and poses the question to the user through a prompt. The user then enters the specific request, "Inventory management system."

[1590] The server then activates an emotion engine to analyze the user's emotions from their voice and text input. It evaluates their emotional state in real time and optimizes the content and tone of the dialogue. For example, if the user is feeling stressed, the AI ​​simplifies the question and displays a message saying, "Please let me know if you need a clearer explanation."

[1591] The server then analyzes the collected initial information and generates follow-up questions to gather more detailed information. The emotion engine considers the user's emotional state and generates questions that are displayed to the user in text format. For example, follow-up questions such as "Do you want to manage inventory in real time?" or "Do you need support for barcode scanners?" are displayed.

[1592] Based on the collected information, the server determines that the requirements for the inventory management system can be met with relatively simple tools and presents specific steps to the user. For example, detailed instructions are provided on how to set up a "real-time inventory update" function using an Excel macro, and the user can follow the steps to proceed.

[1593] The generated RFP is published by the server to multiple providers, who can view the RFP and submit quotes and proposals. The server collects these proposals in a database and stores them as data for the next step.

[1594] The collected suggestions are displayed to the user via the device. The emotion engine analyzes the user's emotional state and presents important information at the appropriate time. For example, detailed comparative information is provided when the user is relaxed.

[1595] Finally, the user can review the generated RFP draft and enter any necessary corrections or additional requirements. The server receives this new information and updates the RFP. The emotion engine constantly monitors the user's state and provides appropriate feedback and guidance.

[1596] An example of a specific prompt might look like this:

[1597] Example 1: Inventory management system requirements

[1598] User: "I want to create an inventory management system."

[1599] Server: "Would you like specific features in that inventory management system?"

[1600] User: "I want real-time inventory updates. I also want it to be compatible with barcode scanners."

[1601] Server: "Okay. Is there anything else you need?"

[1602] If the user feels stressed, the server's emotion engine switches to a softer expression, asking, "Could you please tell me more?"

[1603] Server: Generates an RFP draft based on the collected information and displays it on the terminal.

[1604] User: Checks the RFP draft and presses the publish button.

[1605] Server: Posts the RFP to providers and collects proposals.

[1606] In this way, the system of the present invention automatically generates RFPs based on user requests and provides a function to match users with providers. In addition, by combining it with an emotion engine, it is possible to efficiently and effectively collect requests and receive optimal proposals without causing stress to the user.

[1607] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1608] Step 1:

[1609] A user accesses the system to create a new project. The user logs into the system's web interface using a terminal and clicks the Create New Project button. Input: User login information and project creation action. Output: A request to create a new project is sent to the server.

[1610] Step 2:

[1611] The server launches an AI model (e.g., a generative AI model) and begins a dialogue with the user. The server generates an initial question (e.g., "What kind of system or tool do you want?") and presents it to the user as a prompt. Input: A request to create a new project. Output: A prompt for the initial question to the user.

[1612] Step 3:

[1613] The user inputs a specific request (e.g., "inventory management system") in response to the initial question. The user inputs the answer using a terminal and sends it to the server. Input: User's answer. Output: The user's specific request is sent to the server.

[1614] Step 4:

[1615] The server launches an emotion engine to analyze emotions from the text entered by the user. The emotion engine analyzes the text data and evaluates the user's emotional state (e.g., stress, anxiety, etc.). Input: User's text response. Output: Analyzed emotion data.

[1616] Step 5:

[1617] The server generates follow-up questions taking into account the user's emotional state. To gather more detailed information, the server generates the next question (e.g., "Do you want to manage inventory in real time?") based on the output of the emotion engine. Input: User's emotional data. Output: Generation and presentation of follow-up questions.

[1618] Step 6:

[1619] The user answers the follow-up questions and provides detailed information. For example, answer "Yes" to "Do you want to manage inventory in real time?" Input: User's answer to the follow-up question. Output: Detailed information is sent to the server.

[1620] Step 7:

[1621] The server analyzes the collected information and automatically generates the required Request for Proposal (RFP) draft. Based on the collected details, the RFP draft is generated and created in a user-friendly format based on the output of the emotion engine. Input: User's detailed information. Output: Generated RFP draft.

[1622] Step 8:

[1623] The server publishes the generated RFP draft to multiple providers. The server sends notifications to providers and provides them with links to access the RFP draft. Input: Generated RFP draft. Output: Notifications and links sent to providers.

[1624] Step 9:

[1625] Provider views the RFP, creates a quote or proposal, and sends it to the server. Provider clicks on a link to view the RFP, enters a proposal or quote, and submits it. Input: Provider's proposal and quote. Output: Proposal and quote sent to the server.

[1626] Step 10:

[1627] The server stores the collected quotes and proposals in a database and prepares them to be presented to the user. The server organizes the information and lists it in a format that is easy for the user to understand. Input: Proposals and quotes from providers. Output: Information prepared for presentation to the user.

[1628] Step 11:

[1629] The user reviews the proposals and quotes through the terminal and selects the most suitable provider. The emotion engine monitors the user's emotional state and presents information at the appropriate time. Input: List of proposals and quotes. Output: User's provider selection.

[1630] Step 12:

[1631] The user reviews the generated RFP draft and enters any necessary corrections or additional requirements. The server receives the new information and updates the RFP. The emotion engine provides feedback and the updated RFP is available for the user to review. Input: Revised RFP draft and additional requirements. Output: Updated RFP.

[1632] In this way, through specific processing steps, the system can collect user requests, efficiently generate a request for proposal, and receive optimal proposals.

[1633] (Application example 2)

[1634] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1635] When users wish to develop new systems or tools, they need to be able to effectively extract their requirements and quickly and accurately create a request for proposal (RFP). However, conventional methods place a heavy burden on users, often resulting in emotional stress. It is also difficult to properly publish the generated RFP and reliably collect quotes and proposals from suppliers. Furthermore, for efficient operation within factories, integration with devices such as smart glasses is also important. A system that can solve these issues is needed.

[1636] The specification processing by the specification 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: a dialogue means for collecting requirements through dialogue with the user; a generation means for automatically generating a request for proposal by analyzing the collected information; a publication and collection means for publishing the automatically generated request for proposal to a plurality of providers and collecting estimates and proposals from the providers; a display and selection means for presenting the collected estimates and proposals to the user and selecting the most appropriate provider; an emotion analysis means for analyzing the user's emotions and optimizing the tone of the dialogue and the presentation of information; and a display device linkage means for providing an interface via a device worn by the user. This makes it possible to efficiently generate an RFP and collect proposals from appropriate providers while reducing stress on the user.

[1637] "User" refers to the entity that uses a system or device, typically a human operator.

[1638] "Dialogue means" refers to a function for gathering requests and information through conversation with the user.

[1639] "Generation means" refers to the functionality for analyzing collected information and automatically generating a request for proposal (RFP).

[1640] "Publication and collection means" refers to a function for publishing the generated request for proposal to multiple providers and collecting estimates and proposals from the providers.

[1641] "Display and selection means" refers to a function for presenting collected estimates and proposals to the user and allowing the user to select the most suitable provider.

[1642] "Emotion analysis means" refers to a function that analyzes the user's voice and facial expressions in real time to optimize the tone of the conversation and the presentation of information.

[1643] "Display device linking means" refers to a function for providing an interface via a device worn by a user (e.g., smart glasses).

[1644] A "Request for Proposal (RFP)" is a document that clearly states the user's requirements and specifications and requests quotes and proposals from providers.

[1645] "Provider" refers to the entity that provides an estimate or proposal based on a Request for Proposal.

[1646] "Collected Information" refers to specific details of your requests and desires obtained through your interactions with us.

[1647] To implement the invention, the system includes the following major functions:

[1648] Hardware and Software Use

[1649] Hardware: Smart glasses, factory server

[1650] Software: Sentiment analysis API (e.g., IBM Watson Emotion Analysis), dialogue generation models (e.g., GPT-4), cloud RFP management system

[1651] System Overview

[1652] The system provides an interface using smart glasses worn by the user. Each of the means will be described in detail below.

[1653] User interaction methods

[1654] First, the user puts on the smart glasses and accesses the system. The system then activates the voice assistant built into the smart glasses and starts a dialogue with the user. The following is an example of a specific dialogue:

[1655] Voice Assistant: "I'm starting a new project. What systems and tools would you like to use?"

[1656] User: "I want to build a robotic control system for a new assembly line."

[1657] Emotion analysis means

[1658] The system then uses the smart glasses' camera and microphone to analyze the user's voice and facial expressions in real time, and an emotion analysis API assesses the user's emotional state and optimizes the tone of the dialogue and the way information is presented based on this.

[1659] Example: If the user's stress level is assessed as high, the voice assistant will provide additional information such as, "Don't worry, we'll take it easy and proceed slowly."

[1660] Request for Proposal (RFP) generation tools

[1661] Based on the collected information, the dialogue generation model (GPT-4) generates detailed questions and gathers further information. Throughout this process, the sentiment analysis tool continues to operate, reducing the burden on the user.

[1662] Example prompt sentence:

[1663] "Do you want real-time updates?"

[1664] "How do you deal with barcode scanners?"

[1665] "Are there any special safety considerations?"

[1666] Publication and collection methods

[1667] The generated RFP is uploaded to a cloud RFP management system via an in-factory server and notified to multiple providers. The quotes and proposals from the providers are collected by the cloud system and displayed on the smart glasses screen.

[1668] Display and Selection Means

[1669] The collected quotes and proposals are presented to the user through the smart glasses for review and selection of the most suitable provider, with the user making selections and modifications using voice commands.

[1670] Example: The user confirms and then gives a voice command saying, "Please correct this part." The system then reflects the correction and re-sends the RFP to the provider.

[1671] The system allows users to efficiently generate RFPs and receive proposals from suitable providers with minimal stress.

[1672] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1673] Step 1:

[1674] The server launches the voice assistant in the smart glasses and asks the user, "I'm starting a new project. What kind of system and tools would you like?" The user replies, "I want to build a robotic control system for a new assembly line." This collects the initial requirements.

[1675] Input: User voice input

[1676] Output: Initial request data

[1677] Step 2:

[1678] The server analyzes the user's voice and facial expressions in real time using the smart glasses' camera and microphone, and evaluates the user's emotional state using an emotion analysis API (e.g., IBM Watson Emotion Analysis). The server then optimizes the tone of the dialogue and the way information is presented depending on the user's emotional state.

[1679] Input: User audio and video data

[1680] Output: User's emotional state data

[1681] Step 3:

[1682] The server uses a generative AI model (e.g., GPT-4) to generate detailed questions based on the collected initial request data and emotional state data. The questions are presented to the user through the smart glasses, and the user's answers are collected.

[1683] Input: Initial request data, emotional state data

[1684] Output: Detailed question data, user response data

[1685] Step 4:

[1686] The server automatically generates a Request for Proposal (RFP) based on all the collected information. It uses a generative AI model to analyze the input data and create a specific RFP document, which is then displayed on the smart glasses' display.

[1687] Input: User response data

[1688] Output: Request for Proposal (RFP) draft

[1689] Step 5:

[1690] The user checks the RFP draft displayed on the smart glasses display and makes any necessary corrections using voice commands. The server receives these correction instructions and updates the RFP draft.

[1691] Input: User correction instructions

[1692] Output: Updated RFP draft

[1693] Step 6:

[1694] The server uploads the completed RFP to a cloud RFP management system and notifies multiple providers. It also collects quotes and proposals from the providers. The proposal data collected by the cloud system is presented to the user through the smart glasses display.

[1695] Input: Updated RFP draft

[1696] Output: Quotation and proposal data from providers

[1697] Step 7:

[1698] The user reviews the quotes and proposals presented on the smart glasses display and selects the best provider using voice commands. The server records this selection data and completes the RFP process.

[1699] Input: Quote and proposal data from providers, user selection data

[1700] Output: Selection data for the best provider

[1701] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1702] 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.

[1703] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1704] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1705] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1706] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1707] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1708] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1709] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1710] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1711] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1712] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1713] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1714] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1715] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1716] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1717] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1718] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1719] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1720] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1721] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1722] The following is further disclosed regarding the above embodiment.

[1723] (Claim 1)

[1724] a conversation means for collecting requirements through a dialogue with a user;

[1725] a generating means for analyzing the collected information and automatically generating a request for proposal;

[1726] a publishing and collecting means for publishing the automatically generated request for proposal to a plurality of providers and collecting quotations and proposals from the providers;

[1727] a display and selection means for presenting the collected quotes and proposals to the user and selecting the most suitable provider;

[1728] A system including:

[1729] (Claim 2)

[1730] 2. The system according to claim 1, further comprising a procedure presenting means for presenting a procedure for the user to create a system or tool by himself / herself when the collected information is relatively simple.

[1731] (Claim 3)

[1732] 10. The system of claim 1, further comprising a modifying means for reviewing and modifying the request for proposal generated based on a user request.

[1733] "Example 1"

[1734] (Claim 1)

[1735] an interaction means for collecting requirements through interaction with a user;

[1736] a generating means for analyzing the collected information and automatically generating a request for proposal;

[1737] a publishing and collecting means for publishing the automatically generated request for proposal to a plurality of suppliers and collecting quotations and proposals from the suppliers;

[1738] display and selection means for presenting the collected quotes and proposals to the user and selecting the most suitable supplier;

[1739] a procedure presentation means for presenting and supporting specific procedures when a user desires to create a simple tool;

[1740] A system including:

[1741] (Claim 2)

[1742] 2. The system according to claim 1, further comprising a procedure presenting means for presenting a procedure for the user to create the generation tool by himself / herself when the collected information is relatively simple.

[1743] (Claim 3)

[1744] 10. The system of claim 1, further comprising a modifying means for reviewing and modifying the request for proposal generated based on a user request.

[1745] "Application Example 1"

[1746] (Claim 1)

[1747] a conversation means for collecting requirements through a dialogue with a user;

[1748] a generating means for analyzing the collected information and automatically generating a request for proposal;

[1749] a publishing and collecting means for publishing the automatically generated request for proposal to a plurality of providers and collecting quotations and proposals from the providers;

[1750] a display and selection means for presenting the collected quotes and proposals to the user and selecting the most suitable provider;

[1751] an interaction means including automated vehicle customization information to assist in generating a request for proposal;

[1752] a DIY procedure presentation means for presenting a DIY procedure to a user based on information about customization of the autonomous driving vehicle;

[1753] A system including:

[1754] (Claim 2)

[1755] 2. The system according to claim 1, further comprising a procedure presenting means for presenting a procedure for the user to create a system or tool by himself / herself when the collected information is relatively simple.

[1756] (Claim 3)

[1757] 10. The system of claim 1, further comprising a modifying means for reviewing and modifying the request for proposal generated based on a user request.

[1758] "Example 2: Combining Emotion Engines"

[1759] (Claim 1)

[1760] an interaction means for collecting requirements through interaction with a user;

[1761] An emotion engine that analyzes user emotions and optimizes the content and tone of the conversation;

[1762] a generating means for analyzing the collected information and automatically generating a request for proposal;

[1763] a publishing and collecting means for publishing the automatically generated request for proposal to a plurality of providers and collecting quotations and proposals from the providers;

[1764] a display and selection means for presenting the collected quotes and proposals to the user and selecting the most suitable provider;

[1765] A system including:

[1766] (Claim 2)

[1767] 2. The system according to claim 1, further comprising: a procedure presenting means for presenting a procedure for the user to create a system or tool by himself / herself when the collected information is relatively simple; and an emotion engine.

[1768] (Claim 3)

[1769] 10. The system of claim 1, further comprising: a revising means for reviewing and revising the generated request for proposal based on a user request; and an emotion engine.

[1770] "Application example 2 when combining emotion engines"

[1771] (Claim 1)

[1772] a conversation means for collecting requirements through a dialogue with a user;

[1773] a generating means for analyzing the collected information and automatically generating a request for proposal;

[1774] a publishing and collecting means for publishing the automatically generated request for proposal to a plurality of providers and collecting quotations and proposals from the providers;

[1775] a display and selection means for presenting the collected quotes and proposals to the user and selecting the most suitable provider;

[1776] a sentiment analysis means for analyzing a user's sentiment and optimizing the tone of the dialogue and the presentation of information;

[1777] a display device linking means for providing an interface via a device worn by a user;

[1778] A system including:

[1779] (Claim 2)

[1780] 2. The system according to claim 1, further comprising a procedure presenting means for presenting a procedure for the user to create a system or tool by himself / herself when the collected information is relatively simple.

[1781] (Claim 3)

[1782] 10. The system of claim 1, further comprising a modifying means for reviewing and modifying the request for proposal generated based on a user request. [Explanation of symbols]

[1783] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a conversation means for collecting requirements through a dialogue with a user; a generating means for analyzing the collected information and automatically generating a request for proposal; a publishing and collecting means for publishing the automatically generated request for proposal to a plurality of providers and collecting quotations and proposals from the providers; a display and selection means for presenting the collected quotes and proposals to the user and selecting the most suitable provider; A system including:

2. 2. The system according to claim 1, further comprising a procedure presenting means for presenting a procedure for the user to create a system or tool by himself / herself when the collected information is relatively simple.

3. The system of claim 1 , further comprising a modifying means for reviewing and modifying the generated request for proposal based on a user request.

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