system

Abstract

Provide a system. The present invention includes: a means for receiving requirements input by a user and collecting web information based on the requirements; A method for analyzing collected web information and listing providers that fit the requirements, a means for selecting the most suitable source from the list of sources; A means for automatically generating a requirements definition document based on input data from a user; A system including:

Description

[Technical Field]

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

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

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

[0004] In traditional system development projects, the process of selecting the right vendor and defining requirements requires a lot of time and effort, and development delays and quality degradation often occur due to missed interviews and ambiguous requirements. Furthermore, the sheer number of vendors makes it extremely difficult to select the optimal vendor. This hinders project managers and developers from efficiently progressing the project, ultimately reducing the overall success rate of the project. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides a system that utilizes generative AI. This system includes a means for receiving requirements entered by a user and collecting web information based on the requirements, a means for analyzing the collected web information and listing providers that fit the requirements, a means for selecting the optimal provider from the list of providers, and a means for automatically generating a requirements definition document based on data entered by the user. This system automates the collection of web information, efficiently selects the optimal provider, and quickly generates a requirements definition document, thereby improving the efficiency and quality of system development projects.

[0006] "User" means any person or entity that uses the system, enters requirements, or obtains information.

[0007] "Requirements" refers to specific functions, performance, specifications, and other requirements related to system development.

[0008] "Web information" refers to information such as data, documents, and evaluations that are publicly available on the Internet.

[0009] "Provider" refers to a vendor or provider that can provide the services and products necessary for system development.

[0010] "Generative AI" refers to artificial intelligence technology that uses machine learning and natural language processing to collect, analyze, and generate information.

[0011] "Listing" refers to selecting sources that meet the requirements based on the collected information and presenting them as a list.

[0012] A "requirements definition document" refers to a document that details the requirements necessary for system development.

[0013] "Automatic generation" refers to the process of mechanically creating documents, lists, etc. without human intervention.

[0014] A "system" refers to a set of components in which users input requirements and generative AI is used to collect, analyze, and generate documents. [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] The system of the present invention collects information based on requirements entered by a user, selects appropriate providers, and automatically generates a requirements definition document, and includes the following main functions. Specific embodiments of the system are described below.

[0037] Collecting web information

[0038] The user inputs requirements for system development (e.g., "Development of an e-commerce site") through a terminal.

[0039] The terminal receives the input requirements and transmits them to the server.

[0040] The server passes the received requirements to a generative AI, which searches for information on the internet using specific keywords (e.g., "e-commerce site development vendor reviews").

[0041] The server collects relevant web information and stores it in a database, where it is categorized and organized for analysis.

[0042] Vendor Selection

[0043] The server analyzes the collected web information and lists providers (vendors) that meet the requirements.

[0044] The server generates a list of providers and organizes information such as each provider's reputation and past project history.

[0045] A list of providers from which the terminal was generated is displayed on the user's screen.

[0046] The user selects the most suitable provider from the displayed providers.

[0047] Automating requirements definition

[0048] The user inputs the specific requirements for the system (e.g., "user registration function," "product search function," "cart function," "payment function," etc.) into the terminal.

[0049] The terminal sends these detailed input data to the server.

[0050] The generative AI on the server analyzes the input data and automatically generates an initial requirements definition document.

[0051] The terminal presents the generated requirements definition document to the user.

[0052] When the user checks the requirements definition document and enters any missing points or additional requirements, the terminal sends it to the server.

[0053] The server reflects the added and modified requirements and generates the final requirements specification document.

[0054] The terminal presents the final requirements definition document to the user and requests final confirmation and approval.

[0055] Specific examples

[0056] For example, a specific example will be given in which a user requests "construction of a small online shop."

[0057] 1. The user enters the following into the terminal: "Building a small online shop," "Budget: 1 million yen," and "Required functions: product search, cart, payment."

[0058] 2. The device sends the input data to the server.

[0059] 3. The server uses generative AI to search and collect information on the Internet using keywords such as "online shop vendor reviews."

[0060] 4. The server analyzes the collected information and lists the providers, such as "Vendor X," "Vendor Y," and "Vendor Z."

[0061] 5. The device displays the details of the provider to the user.

[0062] 6. The user selects "Vendor X" and "Vendor Y."

[0063] 7. The user enters specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payment").

[0064] 8. The device sends detailed requirements to the server.

[0065] 9. The server generates a requirements definition document using generative AI and presents it to the user via their terminal for confirmation.

[0066] This system enables users to efficiently and quickly select appropriate providers and create requirements definition documents without any hassle, which is expected to improve the quality of system development projects.

[0067] The processing flow will be explained below.

[0068] Step 1:

[0069] A user uses a terminal to input requirements related to system development (e.g., "Development of an e-commerce site").

[0070] Step 2:

[0071] The terminal receives the input requirements and transmits them to the server.

[0072] Step 3:

[0073] The server analyzes the requirements it receives and instructs the generative AI to collect web information.

[0074] Step 4:

[0075] The generative AI on the server performs an internet search based on specified keywords (e.g., "e-commerce site development vendor reviews").

[0076] Step 5:

[0077] The server collects the information from the relevant websites and databases, converts it into an appropriate format and stores it in the database.

[0078] Step 6:

[0079] The server organizes and classifies the collected data and analyzes it based on the provider's (vendor's) evaluation information and past project history.

[0080] Step 7:

[0081] The server generates a list of providers that meet the requirements based on the analysis results.

[0082] Step 8:

[0083] The device displays a list of providers on the user's screen and provides detailed information about each provider (e.g., ratings, past project history, specialized technologies, etc.).

[0084] Step 9:

[0085] The user selects an appropriate provider from the displayed list of providers and transmits the selection result to the server via the terminal.

[0086] Step 10:

[0087] The user enters detailed functional requirements (e.g., "user registration function," "product search function," "cart function," "payment function") into the terminal.

[0088] Step 11:

[0089] The terminal sends the detailed functional requirements to the server.

[0090] Step 12:

[0091] The server uses generative AI to analyze the detailed requirements sent and automatically generate an initial requirements definition document.

[0092] Step 13:

[0093] The terminal presents the generated initial requirements definition document to the user for confirmation.

[0094] Step 14:

[0095] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[0096] Step 15:

[0097] The device sends the modified and additional requirements to the server.

[0098] Step 16:

[0099] The server reflects the added and modified data and generates the final requirements specification document.

[0100] Step 17:

[0101] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[0102] As a result, the entire process proceeds automatically and efficiently, significantly reducing the user's workload and improving the quality of system development.

[0103] Example 1

[0104] 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."

[0105] In conventional system development projects, the process of users entering requirements, collecting appropriate information, and generating a requirements definition document required a great deal of time and effort. Furthermore, selecting the optimal provider and generating the requirements definition document were often done manually, resulting in issues with efficiency and accuracy. This resulted in problems with the quality and speed of system development projects.

[0106] 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.

[0107] In this invention, the server includes means for receiving requirements entered by a user and collecting information on the Internet based on the requirements, means for classifying and organizing the collected information and listing providers that meet the requirements, means for selecting the most suitable provider based on the provider's evaluation and past project history, etc., and means for automatically generating a requirements definition document based on detailed functional requirements from the user. This allows the user to efficiently and quickly select an appropriate provider without hassle and generate a highly accurate requirements definition document.

[0108] A "user" is a user who uses the system to input requirements and request the selection of the most suitable provider and the generation of a requirements definition document.

[0109] "Requirements" are information that expresses the functions and conditions that users require when developing a system.

[0110] "Information gathering means" is a function that searches for and acquires related information on the Internet based on requirements entered by the user.

[0111] "Classification and organization means" is a function that systematically organizes collected information and stores it in a database for later analysis and selection.

[0112] A "provider" is a business or organization that develops systems or provides services, selected based on the user's requirements.

[0113] The "listing method" is a function that generates a list of providers that meet the requirements based on classified and organized information.

[0114] "Evaluation" refers to the criteria for judging reliability and suitability based on the provider's service quality and past project history.

[0115] The "selection method" is a function for selecting the most suitable provider from the listed providers.

[0116] "Detailed functional requirements" are information that details the system functions and conditions that users specifically require.

[0117] A "requirements definition document" is a specification document required for system development that is automatically generated based on detailed functional requirements entered by the user.

[0118] The "automatic generation means" is a function that analyzes the information entered by the user and automatically creates a requirements definition document.

[0119] The system of the present invention collects information based on requirements entered by a user, selects appropriate providers, and automatically generates a requirements definition document. This system includes a server, a terminal, and a generative AI model. Specific embodiments of the system are described in detail below.

[0120] Collecting web information

[0121] The user uses a terminal to input requirements for system development (e.g., "Build a small online shop," "Budget: 1 million yen," "Required functions: product search, cart, payment"). The terminal formats this requirements data and sends it to the server. The server passes the received requirements data to a generative AI model (e.g., GPT-3 (registered trademark)), which then calls an internet search engine API to search for information on the internet using specific keywords (e.g., "online shop vendor reviews"). The collected information is stored in a database on the server and systematically categorized and organized.

[0122] Vendor Selection

[0123] The server analyzes the information stored in the database and lists providers (vendors) that meet the user's requirements. During this process, generative AI analyzes the vendors' ratings and past project history to select reliable providers. The device receives the list of providers from the server and displays it on the user's screen. This list includes detailed information such as each vendor's rating, project history, and services provided.

[0124] Automating requirements definition

[0125] After the user reviews the list of providers and selects the most suitable provider, they enter specific functional requirements into the device. Examples of input include "add a filtering function to the product search function" and "support credit cards and PayPal for payment." The device formats the detailed requirements data and sends it back to the server. A generative AI model on the server analyzes this requirements data and automatically generates an initial requirements specification document. The requirements specification document contains detailed descriptions of the specific requirements entered by the user.

[0126] Review, revise and approve requirements definition documents

[0127] The generated requirements definition document is presented to the user via the terminal. The user reviews the document and inputs any deficiencies or corrections that need to be made. The terminal sends this to the server, which then regenerates the revised requirements definition document using a generative AI model. The final generated requirements definition document is then presented to the user via the terminal, who makes a final review and approves the document. At this stage, the final requirements definition document is finalized and serves as the basis for the system development project to proceed.

[0128] This system allows users to efficiently and quickly select appropriate providers without hassle and generate highly accurate requirements definition documents. Specific examples of prompt sentences are shown below.

[0129] Prompt Sentence Examples

[0130] "Building a small online shop"

[0131] "Online Shop Vendor Evaluation"

[0132] "Added filtering function to product search function"

[0133] Supports credit card and PayPal payments

[0134] As described above, this system allows users to efficiently carry out each step of system development, which is expected to improve the overall project quality.

[0135] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0136] Step 1:

[0137] The user inputs the requirements for system development into the terminal. As an example, we use "Building a small online shop," "Budget 1 million yen," and "Required functions: product search, cart, payment." Once the user has completed the input, the terminal sends it to the server.

[0138] Input: User-entered requirements information

[0139] Output: Formatted requirements data sent to the server

[0140] Step 2:

[0141] The server passes the received requirements data to the generative AI model, which then collects information on the Internet using specific keywords (e.g., "online shop vendor evaluation"). The server then calls the Internet search engine API to retrieve the information and stores it in a database.

[0142] Input: Requirement data received by the server

[0143] Output: Collected information stored in a database

[0144] Step 3:

[0145] The server analyzes the information stored in the database and uses a generative AI model to list providers (vendors) that meet the user's requirements. The server analyzes provider ratings and past project history to select reliable providers.

[0146] Input: Collected information stored in a database

[0147] Output: A list of matching sources

[0148] Step 4:

[0149] The terminal receives a list of providers from the server and displays it on the user's screen. This list includes detailed information such as each provider's rating, project history, and services provided, allowing the user to review and rate the list.

[0150] Input: A list of providers sent from the server

[0151] Output: A list of providers displayed to the user.

[0152] Step 5:

[0153] The user selects the most suitable provider from the displayed providers. The information of the provider selected by the user is entered into the terminal, and the terminal sends it to the server.

[0154] Input: User-selected provider

[0155] Output: Send the selected provider information to the server

[0156] Step 6:

[0157] The user enters specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payments") into the terminal. The user's detailed requirements data is formatted by the terminal and sent to the server.

[0158] Input: Detailed functional requirements entered by the user

[0159] Output: Send formatted requirements data to the server

[0160] Step 7:

[0161] The server uses a generative AI model to analyze the user's detailed requirements data and automatically generate an initial requirements specification document, which is then sent to the device.

[0162] Input: Detailed functional requirements data

[0163] Output: Generated initial requirements document

[0164] Step 8:

[0165] The device presents the generated requirements specification document to the user. The user checks the document and re-enters any missing or necessary corrections into the device. This is sent to the server, and the generative AI model regenerates the requirements specification document reflecting the corrections.

[0166] Input: Changes and corrections requirements from users

[0167] Output: Modified requirements document

[0168] Step 9:

[0169] The terminal presents the final requirements definition document to the user, who then confirms and approves it. The server then finalizes the requirements definition document, which becomes the basis for starting the system development project.

[0170] Input: Finalized and approved requirements document

[0171] Output: Final requirements document

[0172] Through the above processing steps, the user can efficiently and quickly select an appropriate provider without much effort and generate a highly accurate requirements definition document.

[0173] (Application example 1)

[0174] 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."

[0175] In recent years, as the introduction of robots has progressed in industrial sites such as factories and warehouses, efficient robot deployment plans and the selection of appropriate providers have become important issues. Until now, it was necessary to collect and analyze information from each provider individually and create deployment plans manually, which was time-consuming and labor-intensive, making it difficult to quickly formulate optimal deployment plans. Furthermore, because the evaluation criteria for providers were vague, there was a risk that the selected robot would not perform as expected. In this situation, there is a need to develop a system that can solve these issues.

[0176] 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.

[0177] In this invention, the server includes means for receiving requirements entered by a user and collecting web information based on the requirements, means for analyzing the collected web information and listing providers that fit the requirements, means for selecting the optimal provider from the list of providers, means for automatically generating a requirements definition document based on data entered by the user, means for presenting the generated requirements definition document to the user, acquiring revised requirements, and generating a final document, means for creating an efficient layout plan for industrial equipment, means for collecting and analyzing information for the layout plan from the Internet, and means for evaluating and comparing industrial equipment providers based on the collected information. This allows users to efficiently and quickly select an appropriate provider and formulate an optimal robot layout plan without hassle.

[0178] A "user" is a person or organization that inputs requests or data into the system.

[0179] "Requirements" are a list of conditions or capabilities that must be met by a system or project.

[0180] "Web information" refers to various types of information that are publicly available on the Internet.

[0181] "Collection" refers to gathering information for a specific purpose.

[0182] "Analysis" is the process of analyzing collected information and finding meaning and patterns.

[0183] A "provider" is a company or organization that offers a particular product or service.

[0184] "Listing" refers to the act of creating a list of items selected based on specific criteria.

[0185] "Selection" is the process of choosing the right thing from a large number of options.

[0186] A "requirements definition document" is a document that clearly states the requirements and conditions of a system or project.

[0187] "Auto-generated" refers to content that is automatically created by a system without human intervention.

[0188] "Industrial equipment" is a general term for machines and equipment used in industrial sites such as factories and warehouses.

[0189] A "layout plan" is a document for efficiently allocating industrial equipment and resources.

[0190] "Evaluation" refers to the act of judging the value and performance of the provider and selected items based on collected information.

[0191] "Comparison" refers to the act of comparing multiple selection items and checking their different features and performance.

[0192] This invention is a system that collects information based on requirements entered by the user, selects appropriate providers, and automatically generates an optimal layout plan. This system can collect web information, select providers, automatically generate requirements definition documents, create layout plans for industrial equipment, and evaluate and compare providers.

[0193] The main components of the system are as follows:

[0194] 1. Collecting web information

[0195] A user accesses the system and inputs requirements for industrial equipment (e.g., "Deployment plan for a new factory robot"). The terminal receives the input requirements and sends them to the server. The server uses the requirements to search for information on the Internet using specific keywords. This search uses the requests module and BeautifulSoup to retrieve information from web pages. The collected information is stored in the server's database for later analysis.

[0196] 2. Selection of provider

[0197] The server analyzes the collected web information and lists providers that meet the requirements. This analysis uses natural language processing technology to analyze the collected information. Sample links and page content are evaluated, and a list of appropriate providers is generated. For the generated providers, information such as each provider's evaluation and past project history is organized. The device displays this list on the user's screen, allowing the user to select the most suitable provider.

[0198] 3. Automatic generation of requirements definition documents

[0199] When the user inputs specific functional requirements and work content, the device sends this to the server. The server uses generative AI (e.g., OpenAI's (registered trademark) text-davinci-003) to analyze the input data and automatically generate a requirements definition document. This generated requirements definition document is presented to the user via the device, and the user can confirm and modify the contents.

[0200] 4. Creation of industrial equipment layout plans

[0201] The server generates an optimal industrial equipment layout plan based on the requirements entered by the user. This uses a generative AI model and prompts the user with the requirements. The generated layout plan is presented to the user, who can then make modifications as needed.

[0202] For example, if a user requests a "layout plan for a new factory robot," the procedure would be as follows:

[0203] 1. The user inputs requirements into the terminal, such as "Plan for the placement of a new factory robot," "Budget: 1 million yen," and "Required functions: object recognition, precision operation."

[0204] 2. The device sends the input data to the server.

[0205] 3. The server uses generative AI to collect information using keywords such as "factory robot provider evaluation" and lists appropriate providers.

[0206] 4. The device presents a list of providers to the user, and the user selects the most suitable provider.

[0207] 5. The user enters detailed requirements, which the server parses and generates a requirements specification document.

[0208] 6. Present the generated requirements specification document to the user, who then makes modifications and generates the final document.

[0209] 7. Based on the final document, a generative AI model is used to create an optimal robot placement plan.

[0210] By automating this entire process, users can efficiently create layout plans for industrial equipment without any hassle, which is expected to improve the quality of system development projects.

[0211] Example prompt sentence:

[0212] "User requirements input: New factory robot placement plan, budget 1 million yen, required functions: object recognition, precision operation"

[0213] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0214] Step 1:

[0215] The user inputs requirements into the terminal. For example, detailed requirements such as "Deployment plan for a new factory robot," "Budget: 1 million yen," and "Required functions: object recognition, precision operation" are input into the terminal. This input data is sent from the terminal to the server.

[0216] Step 2:

[0217] The server collects web information based on the received requirements. Specifically, it retrieves information on the Internet using specific keywords (e.g., "factory robot supplier reviews") using the requests module and BeautifulSoup. This collected information is stored in the server's database.

[0218] Step 3:

[0219] The server analyzes the web information stored in the database. During this process, it uses natural language processing technology to analyze the collected information and generate a list of providers that match the user's requirements. This list is organized based on the requested attributes (e.g., technical features, ratings, past project history).

[0220] Step 4:

[0221] The terminal displays the list provided by the server on the user's screen. The user looks at the list of providers and selects the provider that they think is most suitable. This selected information is then sent back to the server from the terminal.

[0222] Step 5:

[0223] The user inputs specific functional requirements and work content into the terminal. For example, when the user inputs specific requirements such as "object recognition" or "precise operation," this detailed input data is also sent from the terminal to the server.

[0224] Step 6:

[0225] The server analyzes the input data using generative AI (e.g., OpenAI's text-davinci-003) and automatically generates a requirements specification document. The generated requirements specification document is displayed to the user via their terminal.

[0226] Step 7:

[0227] The user checks and modifies the generated requirements definition document. When the user inputs the modified requirements into the terminal, the terminal sends them to the server, and the final requirements definition document is generated.

[0228] Step 8:

[0229] Based on the final requirements specification document, the server uses a generative AI model to create an optimal industrial equipment layout plan, which is also presented to the user for modification as needed.

[0230] Step 9:

[0231] After all the information is confirmed, an optimal industrial equipment layout plan is presented to the user, which includes the specific layout and operating parameters of the industrial equipment, allowing the user to efficiently and quickly implement robot layout.

[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] The system of the present invention collects web information based on requirements entered by the user, selects appropriate providers, and automatically generates requirements definition documents. By combining it with an emotion engine that recognizes the user's emotions, it provides more user-friendly development support. Specific embodiments of this system are described below.

[0234] Web information collection and emotion recognition

[0235] The user inputs requirements for system development through a terminal, and the emotion engine analyzes the emotions (e.g., excitement, irritation, anxiety, etc.) that the user is expressing during the input.

[0236] The terminal transmits the input requirements and emotion data to the server.

[0237] The server instructs the generative AI to collect web information based on requirements, and collects information taking into account emotional data.

[0238] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[0239] Vendor Selection

[0240] The server analyzes the collected web information and lists providers (vendors) that meet the requirements, taking into account the user's emotional state.

[0241] The server organizes detailed information about the providers (e.g., ratings, past project history, specialized technologies, etc.) and sets priorities based on sentiment data.

[0242] The device displays a list of providers on the user's screen and provides advice and suggestions based on the emotion data.

[0243] The user selects an appropriate provider from the provider list and sends the result to the server via the terminal.

[0244] Automating requirements definition

[0245] The user inputs specific functional requirements into the device in detail, and the emotion engine re-recognizes and analyzes the emotions being input.

[0246] The device sends the detailed functional requirements and emotion data to the server.

[0247] The server uses generative AI to analyze detailed requirements and emotional data, automatically generating an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[0248] The device presents the initial requirements specification document to the user and also provides advice based on emotional data (e.g., "It seems you are unsure about this part. We recommend that you check it in more detail").

[0249] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[0250] The device sends the corrections and additional requirements and emotion data to the server.

[0251] The server reflects the revised and added requirements and generates the final requirements specification document. The final document is also provided in a format that takes user feelings into consideration.

[0252] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[0253] Specific examples

[0254] For example, a specific example will be given in which a user requests "construction of a small online shop" and feels frustrated while inputting information.

[0255] 1. When a user enters "Building a small online shop," "Budget: 1 million yen," and "Required functions: product search, cart, payment" into a terminal, the emotion engine detects irritation.

[0256] 2. The device sends the input data and irritation emotion data to the server.

[0257] 3. The server uses generative AI to search and collect information on the internet using keywords such as "online shop vendor reviews," taking into account emotional data.

[0258] 4. The server analyzes the collected information and presents a list of providers such as "Vendor X," "Vendor Y," and "Vendor Z," providing a quick and simple selection process for frustrated users.

[0259] 5. The device displays detailed information about the provider to the user along with suggestions based on emotional data (e.g., "Here are the vendors who can develop the product in the shortest time possible").

[0260] 6. The user selects "Vendor X" and "Vendor Y."

[0261] 7. When the user enters specific feature requirements (e.g., "Add filtering to product search" or "Support credit cards and PayPal for payments"), the emotion engine analyzes emotions again and displays appropriate advice based on the input.

[0262] 8. The device sends detailed requirements and emotion data to the server.

[0263] 9. The server uses generative AI to generate a requirements specification document and presents it to the frustrated user via their device in a format that is easy to understand.

[0264] By combining this system with an emotion engine, it is possible to take user emotions into consideration and provide more user-friendly and efficient system development support.

[0265] The processing flow will be explained below.

[0266] Step 1:

[0267] The user uses a terminal to input requirements for system development (e.g., "Development of an e-commerce site"), and the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data.

[0268] Step 2:

[0269] The terminal transmits the input requirements and emotion data to the server.

[0270] Step 3:

[0271] The server analyzes the received requirements and instructs the generative AI to collect web information, along with emotional data.

[0272] Step 4:

[0273] The server's generative AI performs an internet search based on specified keywords (e.g., "e-commerce site development vendor reviews"), taking into account emotional data and prioritizing the collection of information that best meets the user's needs.

[0274] Step 5:

[0275] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[0276] Step 6:

[0277] The server organizes and classifies the collected data, analyzes it based on vendor evaluation information and past project history, and takes into account sentiment data to create a list of the most suitable providers.

[0278] Step 7:

[0279] The device displays a list of providers on the user's screen and provides detailed information about each provider (e.g., ratings, past project history, specialized technologies, etc.), as well as advice and suggestions based on sentiment data (e.g., "Here are vendors who can respond immediately").

[0280] Step 8:

[0281] The user selects an appropriate provider from the provider list and transmits the selection result to the server via the terminal.

[0282] Step 9:

[0283] The user inputs specific functional requirements (e.g., "user registration function," "product search function," "cart function," "payment function") into the device in detail. The emotion engine re-recognizes and analyzes the emotions being input.

[0284] Step 10:

[0285] The device sends the detailed functional requirements and emotion data to the server.

[0286] Step 11:

[0287] The server uses generative AI to analyze detailed requirements and emotional data, automatically generating an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[0288] Step 12:

[0289] The device presents the initial requirements specification document to the user and also provides advice based on emotional data (e.g., "It seems you're unsure about this part. We recommend you check it out in more detail").

[0290] Step 13:

[0291] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[0292] Step 14:

[0293] The device sends the corrections and additional requirements and emotion data to the server.

[0294] Step 15:

[0295] The server reflects the modified and added data and generates the final requirements specification document. The final document is also provided in a format that takes user feelings into consideration.

[0296] Step 16:

[0297] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[0298] As described above, by combining emotion engines, it is possible to take into consideration the user's emotions and provide more user-friendly and efficient system development support.

[0299] Example 2

[0300] 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."

[0301] In modern system development, it is necessary to accurately and quickly grasp user requirements, select appropriate providers, and generate efficient requirements definition documents. It is also important to provide more user-friendly services that take into account the user's emotional state. The purpose of this invention is to solve these problems and provide an optimal system based on the user's requirements and emotions.

[0302] 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.

[0303] In this invention, the server includes means for receiving requirements and emotion data input by a user and collecting web information based on the requirements and emotion data, means for analyzing the collected web information and emotion data and listing providers that fit the requirements, means for selecting the most suitable provider from the list of providers and emotion data, and means for automatically generating a requirements definition document based on the data and emotion data input by the user. This makes it possible to reliably and efficiently support system development while taking user emotions into consideration.

[0304] A "user" is an entity that uses the system to input requirements and request the selection of a provider and the generation of a requirements definition document.

[0305] "Requirements" refer to the functions, specifications, and conditions that users require in system development, and information is collected and providers are selected based on these.

[0306] "Emotion data" is data that indicates the user's emotional state, and is generated by an engine that analyzes emotions such as excitement, irritation, and anxiety.

[0307] "Web information" refers to information related to system development that exists on the Internet, such as vendor evaluations, technical documents, project histories, etc.

[0308] "Provider" refers to the company or vendor that provides the products and services necessary for system development.

[0309] "Listing" means listing multiple providers that meet the conditions based on the collected information.

[0310] A "requirements definition document" is a document that organizes and analyzes user requirements and documents them as specific system specifications.

[0311] "Means" refers to methods, tools, or equipment for performing a specific function or process.

[0312] "Server" refers to the central computer system that processes data entered by users, collects and analyzes information, and automatically generates requirements definition documents.

[0313] "Device" refers to a device such as a computer or smartphone that a user uses to enter requirements or to review and modify the generated requirements specification document.

[0314] A "generative AI model" refers to an artificial intelligence technology that collects and analyzes web information based on user requirements and emotional data, and generates requirements definition documents.

[0315] "Automatic generation" means mechanically creating documents or lists based on given data and conditions, minimizing manual intervention.

[0316] This invention is a system that collects web information based on requirements entered by the user, selects appropriate providers, and automatically generates requirements definition documents. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more user-friendly development support.

[0317] System Overview

[0318] This system mainly consists of a server, terminals, and users. The server is a central computer system that collects web information, selects providers, and automatically generates requirements definition documents. The terminals are devices that users use to input requirements and to check and modify the generated requirements definition documents. The emotion engine recognizes the user's emotional state and uses it as data for analysis.

[0319] What the program does

[0320] 1. The user enters the requirements

[0321] Users input requirements for system development through a terminal, and the emotion engine analyzes the user's emotions in real time.

[0322] Hardware / software used: Device, emotion engine

[0323] Examples:

[0324] Building a small online shop

[0325] Budget: 1 million yen

[0326] Required features: product search, cart, payment

[0327] 2. The device sends data

[0328] The terminal transmits the input requirements and emotion data to the server.

[0329] 3. The server issues a command to collect information

[0330] The server uses a generative AI model to instruct the collection of web information based on requirements and emotional data.

[0331] Hardware / software used: Server, generative AI model

[0332] Example prompt:

[0333] Regarding the construction of a small online shop, please collect web information on the following items.

[0334] Products: Online Shop

[0335] Budget: 1 million yen

[0336] Required features: product search, cart, payment

[0337] Emotion: Frustration (wanting a quick and simple solution)

[0338] 4. The server collects and stores information

[0339] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[0340] 5. The server lists the sources

[0341] The server analyzes the collected web information and emotional data and lists providers that fit the requirements.

[0342] 6. The server organizes the details

[0343] The server organizes detailed information from the providers and sets priorities based on emotional data.

[0344] 7. The device presents the information to the user

[0345] The device displays a list of providers on the user's screen and provides advice and suggestions based on the emotion data.

[0346] 8. Users choose the provider

[0347] The user selects an appropriate provider from the provider list and sends the result to the server via the terminal.

[0348] 9. User inputs specific requirements

[0349] The user inputs specific functional requirements into the device in detail, and the emotion engine recognizes and analyzes the user's emotions again.

[0350] 10. The device sends data

[0351] The device sends detailed functional requirements and emotional data to the server.

[0352] 11. The server generates the requirements specification document

[0353] The server uses a generative AI model to analyze detailed requirements and emotional data to automatically generate an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[0354] 12. The device presents the document

[0355] The device presents the initial requirements definition document to the user and also provides advice based on emotional data.

[0356] 13. The user checks and modifies the document.

[0357] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[0358] 14. The device sends the correction data

[0359] The device sends the corrections and additional requirements and emotion data to the server.

[0360] 15. The server generates the final document

[0361] The server reflects the modified and added requirements and generates the final requirements specification document.

[0362] 16. The terminal presents the final document

[0363] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[0364] This system enables efficient system development support that takes user emotions into consideration. For example, if a user is feeling frustrated, a quick and simple selection process is presented and emotional advice is provided, providing a user-friendly experience.

[0365] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0366] Step 1:

[0367] User enters requirements

[0368] Input: The user inputs specific requirements for system development (e.g., building a small online shop, budget of 1 million yen, required functions: product search, cart, payment) into the terminal.

[0369] Data processing: The emotion engine analyzes the emotion (e.g., frustration) of the user's input in real time.

[0370] Output: The terminal generates requirement data and emotion data and sends them to the server.

[0371] Specific behavior: The user inputs requirements into the device through a keyboard or touch input, and the emotion engine captures the emotional state during that time.

[0372] Step 2:

[0373] The device sends data

[0374] Input: User-entered requirement and sentiment data.

[0375] Data processing: None.

[0376] Output: The terminal sends the requirement data and emotion data to the server.

[0377] Specific operation: The terminal sends the collected data to the server as a data packet.

[0378] Step 3:

[0379] The server instructs the collection of information

[0380] Input: Requirement data and emotion data sent from the terminal.

[0381] Data processing: The server instructs the generative AI model to collect web information using prompt statements (e.g., "Build a small online shop," "Budget: 1 million yen," "Required functions: product search, cart, payment," "Emotion: irritation").

[0382] Output: Web information collected by the generative AI model.

[0383] Specific operation: The server sends a prompt to the generative AI model and collects relevant information from the Internet.

[0384] Step 4:

[0385] The server collects and stores information

[0386] Input: Web information collected by a generative AI model.

[0387] Data processing: The server classifies and organizes the collected information and stores it in a database.

[0388] Output: Organized web information is stored in a database.

[0389] Specific operation: The server organizes information obtained from websites and databases based on emotional data and stores it in storage.

[0390] Step 5:

[0391] The server lists the providers

[0392] Input: Organized web information and emotion data.

[0393] Data processing: The server analyzes the information and lists providers that fit the requirements.

[0394] Output: A list of matching sources.

[0395] Specific operation: The server uses an information analysis algorithm to analyze the reputation and project history of providers and extract suitable providers.

[0396] Step 6:

[0397] The server organizes the details

[0398] Input: Listed provider details (ratings, past project history, specialized technologies, etc.) and sentiment data.

[0399] Data processing: The server organizes detailed information from the source and sets priorities based on emotion data.

[0400] Output: A prioritized list of providers.

[0401] Specific operation: The server prioritizes the rating data provided by the source and obtains feedback based on the user's emotional data.

[0402] Step 7:

[0403] The device presents the information to the user

[0404] Input: A prioritized list of sources and suggestions sent by the server.

[0405] Data processing: None.

[0406] Output: The user is presented with a list of sources and suggestions based on the sentiment data.

[0407] Specific operation: The terminal displays a list of providers and suggestions (e.g., "Here are the vendors who can develop in the shortest time possible") on the user's screen.

[0408] Step 8:

[0409] The user selects the provider

[0410] Input: Source list and proposal.

[0411] Data processing: The user selects the provider.

[0412] Output: The selection results are sent to the server via the terminal.

[0413] Specific operation: The user operates the terminal to select the provider (e.g., "Vendor X" or "Vendor Y") and send the data.

[0414] Step 9:

[0415] The user inputs specific requirements

[0416] Input: After selecting a provider, the user inputs specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payment").

[0417] Data processing: The emotion engine recognizes and analyzes the user's emotions again.

[0418] Output: Detailed functional requirement data and re-analyzed sentiment data are generated.

[0419] Specific behavior: When the user inputs specific requirements into the terminal, the emotion engine captures the emotional state during that time and transmits it back to the server.

[0420] Step 10:

[0421] The device sends data

[0422] Input: Detailed functional requirement data and re-analyzed sentiment data.

[0423] Data processing: None.

[0424] Output: Detailed functional requirement data and emotion data are sent to the server.

[0425] Specific operation: The terminal sends data to the server in packet format.

[0426] Step 11:

[0427] The server generates a requirements specification document.

[0428] Input: Detailed functional requirement data and re-analyzed sentiment data.

[0429] Data processing: The server uses a generative AI model to analyze detailed requirements and emotional data, and automatically generates an initial requirements specification document.

[0430] Output: A requirements document customized with tone and content that matches the user's emotions.

[0431] Specific operation: The server analyzes detailed functional requirements and emotion data and generates a matching requirements specification document.

[0432] Step 12:

[0433] The device presents the document

[0434] Input: Initial requirements document and advice based on sentiment data.

[0435] Data processing: None.

[0436] Output: A requirements specification document and advice is presented to the user.

[0437] Specific behavior: The device displays the document to the user and provides advice such as, "It seems you are concerned about this part. We recommend that you check it in more detail."

[0438] Step 13:

[0439] The user checks and modifies the document

[0440] Input: Initial requirements document and advice, modifications and additional requirements.

[0441] Data processing: The user checks the details of the requirements definition document and enters any deficiencies or additional requirements.

[0442] Output: Corrected and additional requirements data.

[0443] Specific operation: The user reviews the document and enters comments and corrections into the terminal.

[0444] Step 14:

[0445] The device sends correction data

[0446] Input: Correction / additional requirement data and sentiment data.

[0447] Data processing: None.

[0448] Output: Corrected and added requirement data and emotion data are sent to the server.

[0449] Specific operation: The terminal sends the correction data to the server.

[0450] Step 15:

[0451] The server generates the final document

[0452] Input: Correction / additional requirement data and sentiment data.

[0453] Data processing: The server reflects the modified and added requirements and generates the final requirements specification document.

[0454] Output: Final requirements document.

[0455] Specific operation: The server performs a final check on the requirements definition document and generates it in a format that takes emotional data into consideration.

[0456] Step 16:

[0457] The device presents the final document

[0458] Input: Final requirements document.

[0459] Data processing: None.

[0460] Output: The final requirements specification document is presented to the user.

[0461] Specific operation: The terminal displays the final requirements definition document to the user and obtains final confirmation and approval.

[0462] (Application example 2)

[0463] 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."

[0464] Modern system development support often involves a complex process: users input their requirements, then web information is collected and analyzed based on those requirements, and providers are listed and selected. Furthermore, the process ignores the user's mental state and emotions, resulting in a poor user experience and difficulty in providing efficient support. In particular, support that reflects the user's emotions is required when users need something urgent, such as in a food delivery app, or when satisfaction needs to be increased.

[0465] The specification process 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 means for receiving requirements input by a user and collecting web information based on the requirements, means for analyzing the collected web information and listing providers that fit the requirements, means for combining an emotion engine to select and list the most suitable providers based on the user's input data and emotion data, and means for automatically generating a requirements definition document based on the user's input data and emotion data. This makes it possible to collect web information and select providers quickly and effectively while taking the user's emotions into consideration, thereby improving the user experience.

[0466] "Requirements" refer to specific functions or conditions that users expect from a system.

[0467] "WEB information" refers to all data and documents accessible on the Internet, and is information collected in response to specific requests.

[0468] "Provider" refers to a vendor or company that supplies a particular service or product.

[0469] An "emotion engine" is a software or hardware system that analyzes a user's mental state and emotions and adjusts the behavior of an application based on the results.

[0470] "User experience" refers to the overall satisfaction and ease of use that a user feels when using a particular system or service.

[0471] A "requirements definition document" is a document that organizes and describes the specific requirements and conditions for a system or project.

[0472] A "server" is a computer system that receives user input data and performs various data processing, information collection, and document generation.

[0473] This invention automates the processes of user input, emotion analysis, web information collection, provider selection, and requirement definition document generation, thereby supporting system development that takes user emotions into consideration and optimizing food delivery. Specific embodiments are described below.

[0474] Overall system configuration

[0475] The system includes an emotion engine, a server, and a terminal as its main components.

[0476] Emotion Engine

[0477] The emotion engine receives user input data and analyzes the emotions (excitement, irritation, anxiety, etc.) in the input. The emotion engine uses natural language processing techniques and machine learning algorithms to detect emotions from the user's text.

[0478] server

[0479] The server implements several functions:

[0480] Receives requirements entered by the user and collects necessary web information.

[0481] Analyze the collected web information and create a list of providers that fit your requirements.

[0482] The optimal provider is selected based on the emotional data provided by the emotion engine.

[0483] A requirements definition document is generated based on the user's input data and emotion data.

[0484] Terminal

[0485] The terminal provides an interface for users to input requirements and communicates with the server. The analysis results of the emotion engine are also displayed on the terminal, helping users select providers and review requirements definition documents.

[0486] Data processing and calculations

[0487] The server processes the data in the following steps:

[0488] 1. Receive requirements and emotional data entered by the user and use generative AI to collect the necessary web information.

[0489] 2. Classify and organize the collected web information and create a list of providers.

[0490] 3. Based on the emotion data, the best providers are presented to the user in order of priority.

[0491] 4. Generate the final requirements document and customize the tone and content based on the sentiment data.

[0492] Specific examples

[0493] For example, if a user is on their lunch break and inputs, "I want pasta, but it needs to arrive within 30 minutes," and feels frustrated, the system will prioritize highly rated pasta restaurants that can deliver quickly. The emotion engine detects frustration and provides advice based on that.

[0494] Prompt Sentence Examples

[0495] User entered dish: Pasta

[0496] Budget: 2000 yen

[0497] Delivery time: within 30 minutes

[0498] User Emotion: Annoyance

[0499] In this way, this system can quickly and effectively collect web information and select providers while taking into consideration the user's feelings, thereby improving the user experience.

[0500] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0501] Step 1:

[0502] The user inputs their requirements into the device. For example, during their lunch break, the user might input, "I want to eat pasta, but it needs to arrive within 30 minutes." This input data, along with other requirements such as the type of food, budget, and delivery time, is saved on the device.

[0503] Input: User requirements (type of food, budget, delivery time)

[0504] Output: Input data on the terminal

[0505] Step 2:

[0506] The device sends the input data to the emotion engine, which then analyzes the emotion of the user as they type. For example, if someone types, "I want to eat pasta, but it needs to arrive within 30 minutes," the engine can detect the emotion of irritation.

[0507] Input: User requirements

[0508] Output: User emotion data (irritation)

[0509] Step 3:

[0510] The device sends user requirements and emotion data to the server, which receives it and starts various processes.

[0511] Input: User requirements, user emotion data

[0512] Output: Send data to the server

[0513] Step 4:

[0514] The server collects web information based on the received requirements. To do this, the server uses a generative AI model to search and collect information on the internet using keywords such as "food delivery pasta reviews."

[0515] Input: User requirements

[0516] Output: Collected web information

[0517] Step 5:

[0518] The server analyzes the collected web information, which is then categorized and organized according to user requirements, such as delivery time and ratings.

[0519] Input: Collected web information

[0520] Output: Categorized and organized web information

[0521] Step 6:

[0522] The server selects a provider (restaurant) from the collected web information based on the emotion data. For frustrated users, it prioritizes a list of highly rated providers who can deliver quickly.

[0523] Input: Categorized and organized web information, user emotion data

[0524] Output: List of providers

[0525] Step 7:

[0526] The device receives the list of providers from the server and presents it to the user. At the same time, it displays advice and suggestions based on the emotion data. For example, "Here are restaurants that can deliver in the shortest time."

[0527] Input: Source list, emotion data

[0528] Output: Display a list of providers and advice to the user

[0529] Step 8:

[0530] The user makes a specific selection using the device, for example, selecting "Restaurant A" and "Restaurant B," and then sends the result from the device to the server.

[0531] Input: User selection

[0532] Output: Send selection result data to the server

[0533] Step 9:

[0534] The user inputs specific functional requirements into the device in detail, such as "add a filtering function to the product search function" or "support credit cards and PayPal for payment." The emotion engine analyzes the user's emotions and displays appropriate advice.

[0535] Input: Detailed functional requirements

[0536] Output: Detailed functional requirements input data

[0537] Step 10:

[0538] The device sends detailed functional requirements and emotional data to the server, which then analyzes the detailed requirements and emotional data using a generative AI model to automatically generate an initial requirements definition document.

[0539] Input: Detailed functional requirements, sentiment data

[0540] Output: Initial requirements specification document

[0541] Step 11:

[0542] The initial requirements definition document generated by the server is presented to the user via the terminal, and after a confirmation and revision process, the final requirements definition document is generated. The tone and content are also customized based on the emotional data.

[0543] Input: Initial requirements definition document, user modified requirements

[0544] Output: Final requirements specification document

[0545] In this way, it is possible to quickly and effectively collect web information and select providers while taking into consideration the user's feelings, thereby improving the user experience.

[0546] 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.

[0547] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0548] 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.

[0549] [Second embodiment]

[0550] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0551] 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.

[0552] 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).

[0553] 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.

[0554] 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.

[0555] 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).

[0556] 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.

[0557] 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.

[0558] 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.

[0559] 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.

[0560] 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.

[0561] 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."

[0562] The system of the present invention collects information based on requirements entered by a user, selects appropriate providers, and automatically generates a requirements definition document, and includes the following main functions. Specific embodiments of the system are described below.

[0563] Collecting web information

[0564] The user inputs requirements for system development (e.g., "Development of an e-commerce site") through a terminal.

[0565] The terminal receives the input requirements and transmits them to the server.

[0566] The server passes the received requirements to a generative AI, which searches for information on the internet using specific keywords (e.g., "e-commerce site development vendor reviews").

[0567] The server collects relevant web information and stores it in a database, where it is categorized and organized for analysis.

[0568] Vendor Selection

[0569] The server analyzes the collected web information and lists providers (vendors) that meet the requirements.

[0570] The server generates a list of providers and organizes information such as each provider's reputation and past project history.

[0571] A list of providers from which the terminal was generated is displayed on the user's screen.

[0572] The user selects the most suitable provider from the displayed providers.

[0573] Automating requirements definition

[0574] The user inputs the specific requirements for the system (e.g., "user registration function," "product search function," "cart function," "payment function," etc.) into the terminal.

[0575] The terminal sends these detailed input data to the server.

[0576] The generative AI on the server analyzes the input data and automatically generates an initial requirements definition document.

[0577] The terminal presents the generated requirements definition document to the user.

[0578] When the user checks the requirements definition document and enters any missing points or additional requirements, the terminal sends it to the server.

[0579] The server reflects the added and modified requirements and generates the final requirements specification document.

[0580] The terminal presents the final requirements definition document to the user and requests final confirmation and approval.

[0581] Specific examples

[0582] For example, a specific example will be given in which a user requests "construction of a small online shop."

[0583] 1. The user enters the following into the terminal: "Building a small online shop," "Budget: 1 million yen," and "Required functions: product search, cart, payment."

[0584] 2. The device sends the input data to the server.

[0585] 3. The server uses generative AI to search and collect information on the Internet using keywords such as "online shop vendor reviews."

[0586] 4. The server analyzes the collected information and lists the providers, such as "Vendor X," "Vendor Y," and "Vendor Z."

[0587] 5. The device displays the details of the provider to the user.

[0588] 6. The user selects "Vendor X" and "Vendor Y."

[0589] 7. The user enters specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payment").

[0590] 8. The device sends detailed requirements to the server.

[0591] 9. The server generates a requirements definition document using generative AI and presents it to the user via their terminal for confirmation.

[0592] This system enables users to efficiently and quickly select appropriate providers and create requirements definition documents without any hassle, which is expected to improve the quality of system development projects.

[0593] The processing flow will be explained below.

[0594] Step 1:

[0595] A user uses a terminal to input requirements related to system development (e.g., "Development of an e-commerce site").

[0596] Step 2:

[0597] The terminal receives the input requirements and transmits them to the server.

[0598] Step 3:

[0599] The server analyzes the requirements it receives and instructs the generative AI to collect web information.

[0600] Step 4:

[0601] The generative AI on the server performs an internet search based on specified keywords (e.g., "e-commerce site development vendor reviews").

[0602] Step 5:

[0603] The server collects the information from the relevant websites and databases, converts it into an appropriate format and stores it in the database.

[0604] Step 6:

[0605] The server organizes and classifies the collected data and analyzes it based on the provider's (vendor's) evaluation information and past project history.

[0606] Step 7:

[0607] The server generates a list of providers that meet the requirements based on the analysis results.

[0608] Step 8:

[0609] The device displays a list of providers on the user's screen and provides detailed information about each provider (e.g., ratings, past project history, specialized technologies, etc.).

[0610] Step 9:

[0611] The user selects an appropriate provider from the displayed list of providers and transmits the selection result to the server via the terminal.

[0612] Step 10:

[0613] The user enters detailed functional requirements (e.g., "user registration function," "product search function," "cart function," "payment function") into the terminal.

[0614] Step 11:

[0615] The terminal sends the detailed functional requirements to the server.

[0616] Step 12:

[0617] The server uses generative AI to analyze the detailed requirements sent and automatically generate an initial requirements definition document.

[0618] Step 13:

[0619] The terminal presents the generated initial requirements definition document to the user for confirmation.

[0620] Step 14:

[0621] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[0622] Step 15:

[0623] The device sends the modified and additional requirements to the server.

[0624] Step 16:

[0625] The server reflects the added and modified data and generates the final requirements specification document.

[0626] Step 17:

[0627] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[0628] As a result, the entire process proceeds automatically and efficiently, significantly reducing the user's workload and improving the quality of system development.

[0629] Example 1

[0630] 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."

[0631] In conventional system development projects, the process of users entering requirements, collecting appropriate information, and generating a requirements definition document required a great deal of time and effort. Furthermore, selecting the optimal provider and generating the requirements definition document were often done manually, resulting in issues with efficiency and accuracy. This resulted in problems with the quality and speed of system development projects.

[0632] 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.

[0633] In this invention, the server includes means for receiving requirements entered by a user and collecting information on the Internet based on the requirements, means for classifying and organizing the collected information and listing providers that meet the requirements, means for selecting the most suitable provider based on the provider's evaluation and past project history, etc., and means for automatically generating a requirements definition document based on detailed functional requirements from the user. This allows the user to efficiently and quickly select an appropriate provider without hassle and generate a highly accurate requirements definition document.

[0634] A "user" is a user who uses the system to input requirements and request the selection of the most suitable provider and the generation of a requirements definition document.

[0635] "Requirements" are information that expresses the functions and conditions that users require when developing a system.

[0636] "Information gathering means" is a function that searches for and acquires related information on the Internet based on requirements entered by the user.

[0637] "Classification and organization means" is a function that systematically organizes collected information and stores it in a database for later analysis and selection.

[0638] A "provider" is a business or organization that develops systems or provides services, selected based on the user's requirements.

[0639] The "listing method" is a function that generates a list of providers that meet the requirements based on classified and organized information.

[0640] "Evaluation" refers to the criteria for judging reliability and suitability based on the provider's service quality and past project history.

[0641] The "selection method" is a function for selecting the most suitable provider from the listed providers.

[0642] "Detailed functional requirements" are information that details the system functions and conditions that users specifically require.

[0643] A "requirements definition document" is a specification document required for system development that is automatically generated based on detailed functional requirements entered by the user.

[0644] The "automatic generation means" is a function that analyzes the information entered by the user and automatically creates a requirements definition document.

[0645] The system of the present invention collects information based on requirements entered by a user, selects appropriate providers, and automatically generates a requirements definition document. This system includes a server, a terminal, and a generative AI model. Specific embodiments of the system are described in detail below.

[0646] Collecting web information

[0647] A user uses a terminal to input requirements for system development (e.g., "Build a small online shop," "Budget: 1 million yen," "Required functions: product search, cart, payment"). The terminal formats this requirements data and sends it to a server. The server passes the received requirements data to a generative AI model (e.g., GPT-3) and calls an internet search engine API to search for information on the internet using specific keywords (e.g., "online shop vendor reviews"). The collected information is stored in a database on the server and systematically categorized and organized.

[0648] Vendor Selection

[0649] The server analyzes the information stored in the database and lists providers (vendors) that meet the user's requirements. During this process, generative AI analyzes the vendors' ratings and past project history to select reliable providers. The device receives the list of providers from the server and displays it on the user's screen. This list includes detailed information such as each vendor's rating, project history, and services provided.

[0650] Automating requirements definition

[0651] After the user reviews the list of providers and selects the most suitable provider, they enter specific functional requirements into the device. Examples of input include "add a filtering function to the product search function" and "support credit cards and PayPal for payment." The device formats the detailed requirements data and sends it back to the server. A generative AI model on the server analyzes this requirements data and automatically generates an initial requirements specification document. The requirements specification document contains detailed descriptions of the specific requirements entered by the user.

[0652] Review, revise and approve requirements definition documents

[0653] The generated requirements definition document is presented to the user via the terminal. The user reviews the document and inputs any deficiencies or corrections that need to be made. The terminal sends this to the server, which then regenerates the revised requirements definition document using a generative AI model. The final generated requirements definition document is then presented to the user via the terminal, who makes a final review and approves the document. At this stage, the final requirements definition document is finalized and serves as the basis for the system development project to proceed.

[0654] This system allows users to efficiently and quickly select appropriate providers without hassle and generate highly accurate requirements definition documents. Specific examples of prompt sentences are shown below.

[0655] Prompt Sentence Examples

[0656] "Building a small online shop"

[0657] "Online Shop Vendor Evaluation"

[0658] "Added filtering function to product search function"

[0659] Supports credit card and PayPal payments

[0660] As described above, this system allows users to efficiently carry out each step of system development, which is expected to improve the overall project quality.

[0661] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0662] Step 1:

[0663] The user inputs the requirements for system development into the terminal. As an example, we use "Building a small online shop," "Budget 1 million yen," and "Required functions: product search, cart, payment." Once the user has completed the input, the terminal sends it to the server.

[0664] Input: User-entered requirements information

[0665] Output: Formatted requirements data sent to the server

[0666] Step 2:

[0667] The server passes the received requirements data to the generative AI model, which then collects information on the Internet using specific keywords (e.g., "online shop vendor evaluation"). The server then calls the Internet search engine API to retrieve the information and stores it in a database.

[0668] Input: Requirement data received by the server

[0669] Output: Collected information stored in a database

[0670] Step 3:

[0671] The server analyzes the information stored in the database and uses a generative AI model to list providers (vendors) that meet the user's requirements. The server analyzes provider ratings and past project history to select reliable providers.

[0672] Input: Collected information stored in a database

[0673] Output: A list of matching sources

[0674] Step 4:

[0675] The terminal receives a list of providers from the server and displays it on the user's screen. This list includes detailed information such as each provider's rating, project history, and services provided, allowing the user to review and rate the list.

[0676] Input: A list of providers sent from the server

[0677] Output: A list of providers displayed to the user.

[0678] Step 5:

[0679] The user selects the most suitable provider from the displayed providers. The information of the provider selected by the user is entered into the terminal, and the terminal sends it to the server.

[0680] Input: User-selected provider

[0681] Output: Send the selected provider information to the server

[0682] Step 6:

[0683] The user enters specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payments") into the terminal. The user's detailed requirements data is formatted by the terminal and sent to the server.

[0684] Input: Detailed functional requirements entered by the user

[0685] Output: Send formatted requirements data to the server

[0686] Step 7:

[0687] The server uses a generative AI model to analyze the user's detailed requirements data and automatically generate an initial requirements specification document, which is then sent to the device.

[0688] Input: Detailed functional requirements data

[0689] Output: Generated initial requirements document

[0690] Step 8:

[0691] The device presents the generated requirements specification document to the user. The user checks the document and re-enters any missing or necessary corrections into the device. This is sent to the server, and the generative AI model regenerates the requirements specification document reflecting the corrections.

[0692] Input: Changes and corrections requirements from users

[0693] Output: Modified requirements document

[0694] Step 9:

[0695] The terminal presents the final requirements definition document to the user, who then confirms and approves it. The server then finalizes the requirements definition document, which becomes the basis for starting the system development project.

[0696] Input: Finalized and approved requirements document

[0697] Output: Final requirements document

[0698] Through the above processing steps, the user can efficiently and quickly select an appropriate provider without much effort and generate a highly accurate requirements definition document.

[0699] (Application example 1)

[0700] 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."

[0701] In recent years, as the introduction of robots has progressed in industrial sites such as factories and warehouses, efficient robot deployment plans and the selection of appropriate providers have become important issues. Until now, it was necessary to collect and analyze information from each provider individually and create deployment plans manually, which was time-consuming and labor-intensive, making it difficult to quickly formulate optimal deployment plans. Furthermore, because the evaluation criteria for providers were vague, there was a risk that the selected robot would not perform as expected. In this situation, there is a need to develop a system that can solve these issues.

[0702] 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.

[0703] In this invention, the server includes means for receiving requirements entered by a user and collecting web information based on the requirements, means for analyzing the collected web information and listing providers that fit the requirements, means for selecting the optimal provider from the list of providers, means for automatically generating a requirements definition document based on data entered by the user, means for presenting the generated requirements definition document to the user, acquiring revised requirements, and generating a final document, means for creating an efficient layout plan for industrial equipment, means for collecting and analyzing information for the layout plan from the Internet, and means for evaluating and comparing industrial equipment providers based on the collected information. This allows users to efficiently and quickly select an appropriate provider and formulate an optimal robot layout plan without hassle.

[0704] A "user" is a person or organization that inputs requests or data into the system.

[0705] "Requirements" are a list of conditions or capabilities that must be met by a system or project.

[0706] "Web information" refers to various types of information that are publicly available on the Internet.

[0707] "Collection" refers to gathering information for a specific purpose.

[0708] "Analysis" is the process of analyzing collected information and finding meaning and patterns.

[0709] A "provider" is a company or organization that offers a particular product or service.

[0710] "Listing" refers to the act of creating a list of items selected based on specific criteria.

[0711] "Selection" is the process of choosing the right thing from a large number of options.

[0712] A "requirements definition document" is a document that clearly states the requirements and conditions of a system or project.

[0713] "Auto-generated" refers to content that is automatically created by a system without human intervention.

[0714] "Industrial equipment" is a general term for machines and equipment used in industrial sites such as factories and warehouses.

[0715] A "layout plan" is a document for efficiently allocating industrial equipment and resources.

[0716] "Evaluation" refers to the act of judging the value and performance of the provider and selected items based on collected information.

[0717] "Comparison" refers to the act of comparing multiple selection items and checking their different features and performance.

[0718] This invention is a system that collects information based on requirements entered by the user, selects appropriate providers, and automatically generates an optimal layout plan. This system can collect web information, select providers, automatically generate requirements definition documents, create layout plans for industrial equipment, and evaluate and compare providers.

[0719] The main components of the system are as follows:

[0720] 1. Collecting web information

[0721] A user accesses the system and inputs requirements for industrial equipment (e.g., "Deployment plan for a new factory robot"). The terminal receives the input requirements and sends them to the server. The server uses the requirements to search for information on the Internet using specific keywords. This search uses the requests module and BeautifulSoup to retrieve information from web pages. The collected information is stored in the server's database for later analysis.

[0722] 2. Selection of provider

[0723] The server analyzes the collected web information and lists providers that meet the requirements. This analysis uses natural language processing technology to analyze the collected information. Sample links and page content are evaluated, and a list of appropriate providers is generated. For the generated providers, information such as each provider's evaluation and past project history is organized. The device displays this list on the user's screen, allowing the user to select the most suitable provider.

[0724] 3. Automatic generation of requirements definition documents

[0725] When the user inputs specific functional requirements and work content, the device sends this to the server. The server uses generative AI (e.g., OpenAI's text-davinci-003) to analyze the input data and automatically generate a requirements definition document. This generated requirements definition document is presented to the user via the device, and the user can review and modify the content.

[0726] 4. Creation of industrial equipment layout plans

[0727] The server generates an optimal industrial equipment layout plan based on the requirements entered by the user. This uses a generative AI model and prompts the user with the requirements. The generated layout plan is presented to the user, who can then make modifications as needed.

[0728] For example, if a user requests a "layout plan for a new factory robot," the procedure would be as follows:

[0729] 1. The user inputs requirements into the terminal, such as "Plan for the placement of a new factory robot," "Budget: 1 million yen," and "Required functions: object recognition, precision operation."

[0730] 2. The device sends the input data to the server.

[0731] 3. The server uses generative AI to collect information using keywords such as "factory robot provider evaluation" and lists appropriate providers.

[0732] 4. The device presents a list of providers to the user, and the user selects the most suitable provider.

[0733] 5. The user enters detailed requirements, which the server parses and generates a requirements specification document.

[0734] 6. Present the generated requirements specification document to the user, who then makes modifications and generates the final document.

[0735] 7. Based on the final document, a generative AI model is used to create an optimal robot placement plan.

[0736] By automating this entire process, users can efficiently create layout plans for industrial equipment without any hassle, which is expected to improve the quality of system development projects.

[0737] Example prompt sentence:

[0738] "User requirements input: New factory robot placement plan, budget 1 million yen, required functions: object recognition, precision operation"

[0739] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0740] Step 1:

[0741] The user inputs requirements into the terminal. For example, detailed requirements such as "Deployment plan for a new factory robot," "Budget: 1 million yen," and "Required functions: object recognition, precision operation" are input into the terminal. This input data is sent from the terminal to the server.

[0742] Step 2:

[0743] The server collects web information based on the received requirements. Specifically, it retrieves information on the Internet using specific keywords (e.g., "factory robot supplier reviews") using the requests module and BeautifulSoup. This collected information is stored in the server's database.

[0744] Step 3:

[0745] The server analyzes the web information stored in the database. During this process, it uses natural language processing technology to analyze the collected information and generate a list of providers that match the user's requirements. This list is organized based on the requested attributes (e.g., technical features, ratings, past project history).

[0746] Step 4:

[0747] The terminal displays the list provided by the server on the user's screen. The user looks at the list of providers and selects the provider that they think is most suitable. This selected information is then sent back to the server from the terminal.

[0748] Step 5:

[0749] The user inputs specific functional requirements and work content into the terminal. For example, when the user inputs specific requirements such as "object recognition" or "precise operation," this detailed input data is also sent from the terminal to the server.

[0750] Step 6:

[0751] The server analyzes the input data using generative AI (e.g., OpenAI's text-davinci-003) and automatically generates a requirements specification document. The generated requirements specification document is displayed to the user via their terminal.

[0752] Step 7:

[0753] The user checks and modifies the generated requirements definition document. When the user inputs the modified requirements into the terminal, the terminal sends them to the server, and the final requirements definition document is generated.

[0754] Step 8:

[0755] Based on the final requirements specification document, the server uses a generative AI model to create an optimal industrial equipment layout plan, which is also presented to the user for modification as needed.

[0756] Step 9:

[0757] After all the information is confirmed, an optimal industrial equipment layout plan is presented to the user, which includes the specific layout and operating parameters of the industrial equipment, allowing the user to efficiently and quickly implement robot layout.

[0758] 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.

[0759] The system of the present invention collects web information based on requirements entered by the user, selects appropriate providers, and automatically generates requirements definition documents. By combining it with an emotion engine that recognizes the user's emotions, it provides more user-friendly development support. Specific embodiments of this system are described below.

[0760] Web information collection and emotion recognition

[0761] The user inputs requirements for system development through a terminal, and the emotion engine analyzes the emotions (e.g., excitement, irritation, anxiety, etc.) that the user is expressing during the input.

[0762] The terminal transmits the input requirements and emotion data to the server.

[0763] The server instructs the generative AI to collect web information based on requirements, and collects information taking into account emotional data.

[0764] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[0765] Vendor Selection

[0766] The server analyzes the collected web information and lists providers (vendors) that meet the requirements, taking into account the user's emotional state.

[0767] The server organizes detailed information about the providers (e.g., ratings, past project history, specialized technologies, etc.) and sets priorities based on sentiment data.

[0768] The device displays a list of providers on the user's screen and provides advice and suggestions based on the emotion data.

[0769] The user selects an appropriate provider from the provider list and sends the result to the server via the terminal.

[0770] Automating requirements definition

[0771] The user inputs specific functional requirements into the device in detail, and the emotion engine re-recognizes and analyzes the emotions being input.

[0772] The device sends the detailed functional requirements and emotion data to the server.

[0773] The server uses generative AI to analyze detailed requirements and emotional data, automatically generating an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[0774] The device presents the initial requirements specification document to the user and also provides advice based on emotional data (e.g., "It seems you are unsure about this part. We recommend that you check it in more detail").

[0775] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[0776] The device sends the corrections and additional requirements and emotion data to the server.

[0777] The server reflects the revised and added requirements and generates the final requirements specification document. The final document is also provided in a format that takes user feelings into consideration.

[0778] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[0779] Specific examples

[0780] For example, a specific example will be given in which a user requests "construction of a small online shop" and feels frustrated while inputting information.

[0781] 1. When a user enters "Building a small online shop," "Budget: 1 million yen," and "Required functions: product search, cart, payment" into a terminal, the emotion engine detects irritation.

[0782] 2. The device sends the input data and irritation emotion data to the server.

[0783] 3. The server uses generative AI to search and collect information on the internet using keywords such as "online shop vendor reviews," taking into account emotional data.

[0784] 4. The server analyzes the collected information and presents a list of providers such as "Vendor X," "Vendor Y," and "Vendor Z," providing a quick and simple selection process for frustrated users.

[0785] 5. The device displays detailed information about the provider to the user along with suggestions based on emotional data (e.g., "Here are the vendors who can develop the product in the shortest time possible").

[0786] 6. The user selects "Vendor X" and "Vendor Y."

[0787] 7. When the user enters specific feature requirements (e.g., "Add filtering to product search" or "Support credit cards and PayPal for payments"), the emotion engine analyzes emotions again and displays appropriate advice based on the input.

[0788] 8. The device sends detailed requirements and emotion data to the server.

[0789] 9. The server uses generative AI to generate a requirements specification document and presents it to the frustrated user via their device in a format that is easy to understand.

[0790] By combining this system with an emotion engine, it is possible to take user emotions into consideration and provide more user-friendly and efficient system development support.

[0791] The processing flow will be explained below.

[0792] Step 1:

[0793] The user uses a terminal to input requirements for system development (e.g., "Development of an e-commerce site"), and the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data.

[0794] Step 2:

[0795] The terminal transmits the input requirements and emotion data to the server.

[0796] Step 3:

[0797] The server analyzes the received requirements and instructs the generative AI to collect web information, along with emotional data.

[0798] Step 4:

[0799] The server's generative AI performs an internet search based on specified keywords (e.g., "e-commerce site development vendor reviews"), taking into account emotional data and prioritizing the collection of information that best meets the user's needs.

[0800] Step 5:

[0801] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[0802] Step 6:

[0803] The server organizes and classifies the collected data, analyzes it based on vendor evaluation information and past project history, and takes into account sentiment data to create a list of the most suitable providers.

[0804] Step 7:

[0805] The device displays a list of providers on the user's screen and provides detailed information about each provider (e.g., ratings, past project history, specialized technologies, etc.), as well as advice and suggestions based on sentiment data (e.g., "Here are vendors who can respond immediately").

[0806] Step 8:

[0807] The user selects an appropriate provider from the provider list and transmits the selection result to the server via the terminal.

[0808] Step 9:

[0809] The user inputs specific functional requirements (e.g., "user registration function," "product search function," "cart function," "payment function") into the device in detail. The emotion engine re-recognizes and analyzes the emotions being input.

[0810] Step 10:

[0811] The device sends the detailed functional requirements and emotion data to the server.

[0812] Step 11:

[0813] The server uses generative AI to analyze detailed requirements and emotional data, automatically generating an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[0814] Step 12:

[0815] The device presents the initial requirements specification document to the user and also provides advice based on emotional data (e.g., "It seems you're unsure about this part. We recommend you check it out in more detail").

[0816] Step 13:

[0817] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[0818] Step 14:

[0819] The device sends the corrections and additional requirements and emotion data to the server.

[0820] Step 15:

[0821] The server reflects the modified and added data and generates the final requirements specification document. The final document is also provided in a format that takes user feelings into consideration.

[0822] Step 16:

[0823] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[0824] As described above, by combining emotion engines, it is possible to take into consideration the user's emotions and provide more user-friendly and efficient system development support.

[0825] Example 2

[0826] 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."

[0827] In modern system development, it is necessary to accurately and quickly grasp user requirements, select appropriate providers, and generate efficient requirements definition documents. It is also important to provide more user-friendly services that take into account the user's emotional state. The purpose of this invention is to solve these problems and provide an optimal system based on the user's requirements and emotions.

[0828] 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.

[0829] In this invention, the server includes means for receiving requirements and emotion data input by a user and collecting web information based on the requirements and emotion data, means for analyzing the collected web information and emotion data and listing providers that fit the requirements, means for selecting the most suitable provider from the list of providers and emotion data, and means for automatically generating a requirements definition document based on the data and emotion data input by the user. This makes it possible to reliably and efficiently support system development while taking user emotions into consideration.

[0830] A "user" is an entity that uses the system to input requirements and request the selection of a provider and the generation of a requirements definition document.

[0831] "Requirements" refer to the functions, specifications, and conditions that users require in system development, and information is collected and providers are selected based on these.

[0832] "Emotion data" is data that indicates the user's emotional state, and is generated by an engine that analyzes emotions such as excitement, irritation, and anxiety.

[0833] "Web information" refers to information related to system development that exists on the Internet, such as vendor evaluations, technical documents, project histories, etc.

[0834] "Provider" refers to the company or vendor that provides the products and services necessary for system development.

[0835] "Listing" means listing multiple providers that meet the conditions based on the collected information.

[0836] A "requirements definition document" is a document that organizes and analyzes user requirements and documents them as specific system specifications.

[0837] "Means" refers to methods, tools, or equipment for performing a specific function or process.

[0838] "Server" refers to the central computer system that processes data entered by users, collects and analyzes information, and automatically generates requirements definition documents.

[0839] "Device" refers to a device such as a computer or smartphone that a user uses to enter requirements or to review and modify the generated requirements specification document.

[0840] A "generative AI model" refers to an artificial intelligence technology that collects and analyzes web information based on user requirements and emotional data, and generates requirements definition documents.

[0841] "Automatic generation" means mechanically creating documents or lists based on given data and conditions, minimizing manual intervention.

[0842] This invention is a system that collects web information based on requirements entered by the user, selects appropriate providers, and automatically generates requirements definition documents. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more user-friendly development support.

[0843] System Overview

[0844] This system mainly consists of a server, terminals, and users. The server is a central computer system that collects web information, selects providers, and automatically generates requirements definition documents. The terminals are devices that users use to input requirements and to check and modify the generated requirements definition documents. The emotion engine recognizes the user's emotional state and uses it as data for analysis.

[0845] What the program does

[0846] 1. The user enters the requirements

[0847] Users input requirements for system development through a terminal, and the emotion engine analyzes the user's emotions in real time.

[0848] Hardware / software used: Device, emotion engine

[0849] Examples:

[0850] Building a small online shop

[0851] Budget: 1 million yen

[0852] Required features: product search, cart, payment

[0853] 2. The device sends data

[0854] The terminal transmits the input requirements and emotion data to the server.

[0855] 3. The server issues a command to collect information

[0856] The server uses a generative AI model to instruct the collection of web information based on requirements and emotional data.

[0857] Hardware / software used: Server, generative AI model

[0858] Example prompt:

[0859] Regarding the construction of a small online shop, please collect web information on the following items.

[0860] Products: Online Shop

[0861] Budget: 1 million yen

[0862] Required features: product search, cart, payment

[0863] Emotion: Frustration (wanting a quick and simple solution)

[0864] 4. The server collects and stores information

[0865] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[0866] 5. The server lists the sources

[0867] The server analyzes the collected web information and emotional data and lists providers that fit the requirements.

[0868] 6. The server organizes the details

[0869] The server organizes detailed information from the providers and sets priorities based on emotional data.

[0870] 7. The device presents the information to the user

[0871] The device displays a list of providers on the user's screen and provides advice and suggestions based on the emotion data.

[0872] 8. Users choose the provider

[0873] The user selects an appropriate provider from the provider list and sends the result to the server via the terminal.

[0874] 9. User inputs specific requirements

[0875] The user inputs specific functional requirements into the device in detail, and the emotion engine recognizes and analyzes the user's emotions again.

[0876] 10. The device sends data

[0877] The device sends detailed functional requirements and emotional data to the server.

[0878] 11. The server generates the requirements specification document

[0879] The server uses a generative AI model to analyze detailed requirements and emotional data to automatically generate an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[0880] 12. The device presents the document

[0881] The device presents the initial requirements definition document to the user and also provides advice based on emotional data.

[0882] 13. The user checks and modifies the document.

[0883] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[0884] 14. The device sends the correction data

[0885] The device sends the corrections and additional requirements and emotion data to the server.

[0886] 15. The server generates the final document

[0887] The server reflects the modified and added requirements and generates the final requirements specification document.

[0888] 16. The terminal presents the final document

[0889] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[0890] This system enables efficient system development support that takes user emotions into consideration. For example, if a user is feeling frustrated, a quick and simple selection process is presented and emotional advice is provided, providing a user-friendly experience.

[0891] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0892] Step 1:

[0893] User enters requirements

[0894] Input: The user inputs specific requirements for system development (e.g., building a small online shop, budget of 1 million yen, required functions: product search, cart, payment) into the terminal.

[0895] Data processing: The emotion engine analyzes the emotion (e.g., frustration) of the user's input in real time.

[0896] Output: The terminal generates requirement data and emotion data and sends them to the server.

[0897] Specific behavior: The user inputs requirements into the device through a keyboard or touch input, and the emotion engine captures the emotional state during that time.

[0898] Step 2:

[0899] The device sends data

[0900] Input: User-entered requirement and sentiment data.

[0901] Data processing: None.

[0902] Output: The terminal sends the requirement data and emotion data to the server.

[0903] Specific operation: The terminal sends the collected data to the server as a data packet.

[0904] Step 3:

[0905] The server instructs the collection of information

[0906] Input: Requirement data and emotion data sent from the terminal.

[0907] Data processing: The server instructs the generative AI model to collect web information using prompt statements (e.g., "Build a small online shop," "Budget: 1 million yen," "Required functions: product search, cart, payment," "Emotion: irritation").

[0908] Output: Web information collected by the generative AI model.

[0909] Specific operation: The server sends a prompt to the generative AI model and collects relevant information from the Internet.

[0910] Step 4:

[0911] The server collects and stores information

[0912] Input: Web information collected by a generative AI model.

[0913] Data processing: The server classifies and organizes the collected information and stores it in a database.

[0914] Output: Organized web information is stored in a database.

[0915] Specific operation: The server organizes information obtained from websites and databases based on emotional data and stores it in storage.

[0916] Step 5:

[0917] The server lists the providers

[0918] Input: Organized web information and emotion data.

[0919] Data processing: The server analyzes the information and lists providers that fit the requirements.

[0920] Output: A list of matching sources.

[0921] Specific operation: The server uses an information analysis algorithm to analyze the reputation and project history of providers and extract suitable providers.

[0922] Step 6:

[0923] The server organizes the details

[0924] Input: Listed provider details (ratings, past project history, specialized technologies, etc.) and sentiment data.

[0925] Data processing: The server organizes detailed information from the source and sets priorities based on emotion data.

[0926] Output: A prioritized list of providers.

[0927] Specific operation: The server prioritizes the rating data provided by the source and obtains feedback based on the user's emotional data.

[0928] Step 7:

[0929] The device presents the information to the user

[0930] Input: A prioritized list of sources and suggestions sent by the server.

[0931] Data processing: None.

[0932] Output: The user is presented with a list of sources and suggestions based on the sentiment data.

[0933] Specific operation: The terminal displays a list of providers and suggestions (e.g., "Here are the vendors who can develop in the shortest time possible") on the user's screen.

[0934] Step 8:

[0935] The user selects the provider

[0936] Input: Source list and proposal.

[0937] Data processing: The user selects the provider.

[0938] Output: The selection results are sent to the server via the terminal.

[0939] Specific operation: The user operates the terminal to select the provider (e.g., "Vendor X" or "Vendor Y") and send the data.

[0940] Step 9:

[0941] The user inputs specific requirements

[0942] Input: After selecting a provider, the user inputs specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payment").

[0943] Data processing: The emotion engine recognizes and analyzes the user's emotions again.

[0944] Output: Detailed functional requirement data and re-analyzed sentiment data are generated.

[0945] Specific behavior: When the user inputs specific requirements into the terminal, the emotion engine captures the emotional state during that time and transmits it back to the server.

[0946] Step 10:

[0947] The device sends data

[0948] Input: Detailed functional requirement data and re-analyzed sentiment data.

[0949] Data processing: None.

[0950] Output: Detailed functional requirement data and emotion data are sent to the server.

[0951] Specific operation: The terminal sends data to the server in packet format.

[0952] Step 11:

[0953] The server generates a requirements specification document.

[0954] Input: Detailed functional requirement data and re-analyzed sentiment data.

[0955] Data processing: The server uses a generative AI model to analyze detailed requirements and emotional data, and automatically generates an initial requirements specification document.

[0956] Output: A requirements document customized with tone and content that matches the user's emotions.

[0957] Specific operation: The server analyzes detailed functional requirements and emotion data and generates a matching requirements specification document.

[0958] Step 12:

[0959] The device presents the document

[0960] Input: Initial requirements document and advice based on sentiment data.

[0961] Data processing: None.

[0962] Output: A requirements specification document and advice is presented to the user.

[0963] Specific behavior: The device displays the document to the user and provides advice such as, "It seems you are concerned about this part. We recommend that you check it in more detail."

[0964] Step 13:

[0965] The user checks and modifies the document

[0966] Input: Initial requirements document and advice, modifications and additional requirements.

[0967] Data processing: The user checks the details of the requirements definition document and enters any deficiencies or additional requirements.

[0968] Output: Corrected and additional requirements data.

[0969] Specific operation: The user reviews the document and enters comments and corrections into the terminal.

[0970] Step 14:

[0971] The device sends correction data

[0972] Input: Correction / additional requirement data and sentiment data.

[0973] Data processing: None.

[0974] Output: Corrected and added requirement data and emotion data are sent to the server.

[0975] Specific operation: The terminal sends the correction data to the server.

[0976] Step 15:

[0977] The server generates the final document

[0978] Input: Correction / additional requirement data and sentiment data.

[0979] Data processing: The server reflects the modified and added requirements and generates the final requirements specification document.

[0980] Output: Final requirements document.

[0981] Specific operation: The server performs a final check on the requirements definition document and generates it in a format that takes emotional data into consideration.

[0982] Step 16:

[0983] The device presents the final document

[0984] Input: Final requirements document.

[0985] Data processing: None.

[0986] Output: The final requirements specification document is presented to the user.

[0987] Specific operation: The terminal displays the final requirements definition document to the user and obtains final confirmation and approval.

[0988] (Application example 2)

[0989] 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."

[0990] Modern system development support often involves a complex process: users input their requirements, then web information is collected and analyzed based on those requirements, and providers are listed and selected. Furthermore, the process ignores the user's mental state and emotions, resulting in a poor user experience and difficulty in providing efficient support. In particular, support that reflects the user's emotions is required when users need something urgent, such as in a food delivery app, or when satisfaction needs to be increased.

[0991] The specification process 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 means for receiving requirements input by a user and collecting web information based on the requirements, means for analyzing the collected web information and listing providers that fit the requirements, means for combining an emotion engine to select and list the most suitable providers based on the user's input data and emotion data, and means for automatically generating a requirements definition document based on the user's input data and emotion data. This makes it possible to collect web information and select providers quickly and effectively while taking the user's emotions into consideration, thereby improving the user experience.

[0992] "Requirements" refer to specific functions or conditions that users expect from a system.

[0993] "WEB information" refers to all data and documents accessible on the Internet, and is information collected in response to specific requests.

[0994] "Provider" refers to a vendor or company that supplies a particular service or product.

[0995] An "emotion engine" is a software or hardware system that analyzes a user's mental state and emotions and adjusts the behavior of an application based on the results.

[0996] "User experience" refers to the overall satisfaction and ease of use that a user feels when using a particular system or service.

[0997] A "requirements definition document" is a document that organizes and describes the specific requirements and conditions for a system or project.

[0998] A "server" is a computer system that receives user input data and performs various data processing, information collection, and document generation.

[0999] This invention automates the processes of user input, emotion analysis, web information collection, provider selection, and requirement definition document generation, thereby supporting system development that takes user emotions into consideration and optimizing food delivery. Specific embodiments are described below.

[1000] Overall system configuration

[1001] The system includes an emotion engine, a server, and a terminal as its main components.

[1002] Emotion Engine

[1003] The emotion engine receives user input data and analyzes the emotions (excitement, irritation, anxiety, etc.) in the input. The emotion engine uses natural language processing techniques and machine learning algorithms to detect emotions from the user's text.

[1004] server

[1005] The server implements several functions:

[1006] Receives requirements entered by the user and collects necessary web information.

[1007] Analyze the collected web information and create a list of providers that fit your requirements.

[1008] The optimal provider is selected based on the emotional data provided by the emotion engine.

[1009] A requirements definition document is generated based on the user's input data and emotion data.

[1010] Terminal

[1011] The terminal provides an interface for users to input requirements and communicates with the server. The analysis results of the emotion engine are also displayed on the terminal, helping users select providers and review requirements definition documents.

[1012] Data processing and calculations

[1013] The server processes the data in the following steps:

[1014] 1. Receive requirements and emotional data entered by the user and use generative AI to collect the necessary web information.

[1015] 2. Classify and organize the collected web information and create a list of providers.

[1016] 3. Based on the emotion data, the best providers are presented to the user in order of priority.

[1017] 4. Generate the final requirements document and customize the tone and content based on the sentiment data.

[1018] Specific examples

[1019] For example, if a user is on their lunch break and inputs, "I want pasta, but it needs to arrive within 30 minutes," and feels frustrated, the system will prioritize highly rated pasta restaurants that can deliver quickly. The emotion engine detects frustration and provides advice based on that.

[1020] Prompt Sentence Examples

[1021] User entered dish: Pasta

[1022] Budget: 2000 yen

[1023] Delivery time: within 30 minutes

[1024] User Emotion: Annoyance

[1025] In this way, this system can quickly and effectively collect web information and select providers while taking into consideration the user's feelings, thereby improving the user experience.

[1026] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1027] Step 1:

[1028] The user inputs their requirements into the device. For example, during their lunch break, the user might input, "I want to eat pasta, but it needs to arrive within 30 minutes." This input data, along with other requirements such as the type of food, budget, and delivery time, is saved on the device.

[1029] Input: User requirements (type of food, budget, delivery time)

[1030] Output: Input data on the terminal

[1031] Step 2:

[1032] The device sends the input data to the emotion engine, which then analyzes the emotion of the user as they type. For example, if someone types, "I want to eat pasta, but it needs to arrive within 30 minutes," the engine can detect the emotion of irritation.

[1033] Input: User requirements

[1034] Output: User emotion data (irritation)

[1035] Step 3:

[1036] The device sends user requirements and emotion data to the server, which receives it and starts various processes.

[1037] Input: User requirements, user emotion data

[1038] Output: Send data to the server

[1039] Step 4:

[1040] The server collects web information based on the received requirements. To do this, the server uses a generative AI model to search and collect information on the internet using keywords such as "food delivery pasta reviews."

[1041] Input: User requirements

[1042] Output: Collected web information

[1043] Step 5:

[1044] The server analyzes the collected web information, which is then categorized and organized according to user requirements, such as delivery time and ratings.

[1045] Input: Collected web information

[1046] Output: Categorized and organized web information

[1047] Step 6:

[1048] The server selects a provider (restaurant) from the collected web information based on the emotion data. For frustrated users, it prioritizes a list of highly rated providers who can deliver quickly.

[1049] Input: Categorized and organized web information, user emotion data

[1050] Output: List of providers

[1051] Step 7:

[1052] The device receives the list of providers from the server and presents it to the user. At the same time, it displays advice and suggestions based on the emotion data. For example, "Here are restaurants that can deliver in the shortest time."

[1053] Input: Source list, emotion data

[1054] Output: Display a list of providers and advice to the user

[1055] Step 8:

[1056] The user makes a specific selection using the device, for example, selecting "Restaurant A" and "Restaurant B," and then sends the result from the device to the server.

[1057] Input: User selection

[1058] Output: Send selection result data to the server

[1059] Step 9:

[1060] The user inputs specific functional requirements into the device in detail, such as "add a filtering function to the product search function" or "support credit cards and PayPal for payment." The emotion engine analyzes the user's emotions and displays appropriate advice.

[1061] Input: Detailed functional requirements

[1062] Output: Detailed functional requirements input data

[1063] Step 10:

[1064] The device sends detailed functional requirements and emotional data to the server, which then analyzes the detailed requirements and emotional data using a generative AI model to automatically generate an initial requirements definition document.

[1065] Input: Detailed functional requirements, sentiment data

[1066] Output: Initial requirements specification document

[1067] Step 11:

[1068] The initial requirements definition document generated by the server is presented to the user via the terminal, and after a confirmation and revision process, the final requirements definition document is generated. The tone and content are also customized based on the emotional data.

[1069] Input: Initial requirements definition document, user modified requirements

[1070] Output: Final requirements specification document

[1071] In this way, it is possible to quickly and effectively collect web information and select providers while taking into consideration the user's feelings, thereby improving the user experience.

[1072] 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.

[1073] 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.

[1074] 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.

[1075] [Third embodiment]

[1076] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1077] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1078] 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).

[1079] 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.

[1080] 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.

[1081] 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).

[1082] 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.

[1083] 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.

[1084] 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.

[1085] 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.

[1086] 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.

[1087] 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."

[1088] The system of the present invention collects information based on requirements entered by a user, selects appropriate providers, and automatically generates a requirements definition document, and includes the following main functions. Specific embodiments of the system are described below.

[1089] Collecting web information

[1090] The user inputs requirements for system development (e.g., "Development of an e-commerce site") through a terminal.

[1091] The terminal receives the input requirements and transmits them to the server.

[1092] The server passes the received requirements to a generative AI, which searches for information on the internet using specific keywords (e.g., "e-commerce site development vendor reviews").

[1093] The server collects relevant web information and stores it in a database, where it is categorized and organized for analysis.

[1094] Vendor Selection

[1095] The server analyzes the collected web information and lists providers (vendors) that meet the requirements.

[1096] The server generates a list of providers and organizes information such as each provider's reputation and past project history.

[1097] A list of providers from which the terminal was generated is displayed on the user's screen.

[1098] The user selects the most suitable provider from the displayed providers.

[1099] Automating requirements definition

[1100] The user inputs the specific requirements for the system (e.g., "user registration function," "product search function," "cart function," "payment function," etc.) into the terminal.

[1101] The terminal sends these detailed input data to the server.

[1102] The generative AI on the server analyzes the input data and automatically generates an initial requirements definition document.

[1103] The terminal presents the generated requirements definition document to the user.

[1104] When the user checks the requirements definition document and enters any missing points or additional requirements, the terminal sends it to the server.

[1105] The server reflects the added and modified requirements and generates the final requirements specification document.

[1106] The terminal presents the final requirements definition document to the user and requests final confirmation and approval.

[1107] Specific examples

[1108] For example, a specific example will be given in which a user requests "construction of a small online shop."

[1109] 1. The user enters the following into the terminal: "Building a small online shop," "Budget: 1 million yen," and "Required functions: product search, cart, payment."

[1110] 2. The device sends the input data to the server.

[1111] 3. The server uses generative AI to search and collect information on the Internet using keywords such as "online shop vendor reviews."

[1112] 4. The server analyzes the collected information and lists the providers, such as "Vendor X," "Vendor Y," and "Vendor Z."

[1113] 5. The device displays the details of the provider to the user.

[1114] 6. The user selects "Vendor X" and "Vendor Y."

[1115] 7. The user enters specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payment").

[1116] 8. The device sends detailed requirements to the server.

[1117] 9. The server generates a requirements definition document using generative AI and presents it to the user via their terminal for confirmation.

[1118] This system enables users to efficiently and quickly select appropriate providers and create requirements definition documents without any hassle, which is expected to improve the quality of system development projects.

[1119] The processing flow will be explained below.

[1120] Step 1:

[1121] A user uses a terminal to input requirements related to system development (e.g., "Development of an e-commerce site").

[1122] Step 2:

[1123] The terminal receives the input requirements and transmits them to the server.

[1124] Step 3:

[1125] The server analyzes the requirements it receives and instructs the generative AI to collect web information.

[1126] Step 4:

[1127] The generative AI on the server performs an internet search based on specified keywords (e.g., "e-commerce site development vendor reviews").

[1128] Step 5:

[1129] The server collects the information from the relevant websites and databases, converts it into an appropriate format and stores it in the database.

[1130] Step 6:

[1131] The server organizes and classifies the collected data and analyzes it based on the provider's (vendor's) evaluation information and past project history.

[1132] Step 7:

[1133] The server generates a list of providers that meet the requirements based on the analysis results.

[1134] Step 8:

[1135] The device displays a list of providers on the user's screen and provides detailed information about each provider (e.g., ratings, past project history, specialized technologies, etc.).

[1136] Step 9:

[1137] The user selects an appropriate provider from the displayed list of providers and transmits the selection result to the server via the terminal.

[1138] Step 10:

[1139] The user enters detailed functional requirements (e.g., "user registration function," "product search function," "cart function," "payment function") into the terminal.

[1140] Step 11:

[1141] The terminal sends the detailed functional requirements to the server.

[1142] Step 12:

[1143] The server uses generative AI to analyze the detailed requirements sent and automatically generate an initial requirements definition document.

[1144] Step 13:

[1145] The terminal presents the generated initial requirements definition document to the user for confirmation.

[1146] Step 14:

[1147] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[1148] Step 15:

[1149] The device sends the modified and additional requirements to the server.

[1150] Step 16:

[1151] The server reflects the added and modified data and generates the final requirements specification document.

[1152] Step 17:

[1153] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[1154] As a result, the entire process proceeds automatically and efficiently, significantly reducing the user's workload and improving the quality of system development.

[1155] Example 1

[1156] 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."

[1157] In conventional system development projects, the process of users entering requirements, collecting appropriate information, and generating a requirements definition document required a great deal of time and effort. Furthermore, selecting the optimal provider and generating the requirements definition document were often done manually, resulting in issues with efficiency and accuracy. This resulted in problems with the quality and speed of system development projects.

[1158] 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.

[1159] In this invention, the server includes means for receiving requirements entered by a user and collecting information on the Internet based on the requirements, means for classifying and organizing the collected information and listing providers that meet the requirements, means for selecting the most suitable provider based on the provider's evaluation and past project history, etc., and means for automatically generating a requirements definition document based on detailed functional requirements from the user. This allows the user to efficiently and quickly select an appropriate provider without hassle and generate a highly accurate requirements definition document.

[1160] A "user" is a user who uses the system to input requirements and request the selection of the most suitable provider and the generation of a requirements definition document.

[1161] "Requirements" are information that expresses the functions and conditions that users require when developing a system.

[1162] "Information gathering means" is a function that searches for and acquires related information on the Internet based on requirements entered by the user.

[1163] "Classification and organization means" is a function that systematically organizes collected information and stores it in a database for later analysis and selection.

[1164] A "provider" is a business or organization that develops systems or provides services, selected based on the user's requirements.

[1165] The "listing method" is a function that generates a list of providers that meet the requirements based on classified and organized information.

[1166] "Evaluation" refers to the criteria for judging reliability and suitability based on the provider's service quality and past project history.

[1167] The "selection method" is a function for selecting the most suitable provider from the listed providers.

[1168] "Detailed functional requirements" are information that details the system functions and conditions that users specifically require.

[1169] A "requirements definition document" is a specification document required for system development that is automatically generated based on detailed functional requirements entered by the user.

[1170] The "automatic generation means" is a function that analyzes the information entered by the user and automatically creates a requirements definition document.

[1171] The system of the present invention collects information based on requirements entered by a user, selects appropriate providers, and automatically generates a requirements definition document. This system includes a server, a terminal, and a generative AI model. Specific embodiments of the system are described in detail below.

[1172] Collecting web information

[1173] A user uses a terminal to input requirements for system development (e.g., "Build a small online shop," "Budget: 1 million yen," "Required functions: product search, cart, payment"). The terminal formats this requirements data and sends it to a server. The server passes the received requirements data to a generative AI model (e.g., GPT-3) and calls an internet search engine API to search for information on the internet using specific keywords (e.g., "online shop vendor reviews"). The collected information is stored in a database on the server and systematically categorized and organized.

[1174] Vendor Selection

[1175] The server analyzes the information stored in the database and lists providers (vendors) that meet the user's requirements. During this process, generative AI analyzes the vendors' ratings and past project history to select reliable providers. The device receives the list of providers from the server and displays it on the user's screen. This list includes detailed information such as each vendor's rating, project history, and services provided.

[1176] Automating requirements definition

[1177] After the user reviews the list of providers and selects the most suitable provider, they enter specific functional requirements into the device. Examples of input include "add a filtering function to the product search function" and "support credit cards and PayPal for payment." The device formats the detailed requirements data and sends it back to the server. A generative AI model on the server analyzes this requirements data and automatically generates an initial requirements specification document. The requirements specification document contains detailed descriptions of the specific requirements entered by the user.

[1178] Review, revise and approve requirements definition documents

[1179] The generated requirements definition document is presented to the user via the terminal. The user reviews the document and inputs any deficiencies or corrections that need to be made. The terminal sends this to the server, which then regenerates the revised requirements definition document using a generative AI model. The final generated requirements definition document is then presented to the user via the terminal, who makes a final review and approves the document. At this stage, the final requirements definition document is finalized and serves as the basis for the system development project to proceed.

[1180] This system allows users to efficiently and quickly select appropriate providers without hassle and generate highly accurate requirements definition documents. Specific examples of prompt sentences are shown below.

[1181] Prompt Sentence Examples

[1182] "Building a small online shop"

[1183] "Online Shop Vendor Evaluation"

[1184] "Added filtering function to product search function"

[1185] Supports credit card and PayPal payments

[1186] As described above, this system allows users to efficiently carry out each step of system development, which is expected to improve the overall project quality.

[1187] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1188] Step 1:

[1189] The user inputs the requirements for system development into the terminal. As an example, we use "Building a small online shop," "Budget 1 million yen," and "Required functions: product search, cart, payment." Once the user has completed the input, the terminal sends it to the server.

[1190] Input: User-entered requirements information

[1191] Output: Formatted requirements data sent to the server

[1192] Step 2:

[1193] The server passes the received requirements data to the generative AI model, which then collects information on the Internet using specific keywords (e.g., "online shop vendor evaluation"). The server then calls the Internet search engine API to retrieve the information and stores it in a database.

[1194] Input: Requirement data received by the server

[1195] Output: Collected information stored in a database

[1196] Step 3:

[1197] The server analyzes the information stored in the database and uses a generative AI model to list providers (vendors) that meet the user's requirements. The server analyzes provider ratings and past project history to select reliable providers.

[1198] Input: Collected information stored in a database

[1199] Output: A list of matching sources

[1200] Step 4:

[1201] The terminal receives a list of providers from the server and displays it on the user's screen. This list includes detailed information such as each provider's rating, project history, and services provided, allowing the user to review and rate the list.

[1202] Input: A list of providers sent from the server

[1203] Output: A list of providers displayed to the user.

[1204] Step 5:

[1205] The user selects the most suitable provider from the displayed providers. The information of the provider selected by the user is entered into the terminal, and the terminal sends it to the server.

[1206] Input: User-selected provider

[1207] Output: Send the selected provider information to the server

[1208] Step 6:

[1209] The user enters specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payments") into the terminal. The user's detailed requirements data is formatted by the terminal and sent to the server.

[1210] Input: Detailed functional requirements entered by the user

[1211] Output: Send formatted requirements data to the server

[1212] Step 7:

[1213] The server uses a generative AI model to analyze the user's detailed requirements data and automatically generate an initial requirements specification document, which is then sent to the device.

[1214] Input: Detailed functional requirements data

[1215] Output: Generated initial requirements document

[1216] Step 8:

[1217] The device presents the generated requirements specification document to the user. The user checks the document and re-enters any missing or necessary corrections into the device. This is sent to the server, and the generative AI model regenerates the requirements specification document reflecting the corrections.

[1218] Input: Changes and corrections requirements from users

[1219] Output: Modified requirements document

[1220] Step 9:

[1221] The terminal presents the final requirements definition document to the user, who then confirms and approves it. The server then finalizes the requirements definition document, which becomes the basis for starting the system development project.

[1222] Input: Finalized and approved requirements document

[1223] Output: Final requirements document

[1224] Through the above processing steps, the user can efficiently and quickly select an appropriate provider without much effort and generate a highly accurate requirements definition document.

[1225] (Application example 1)

[1226] 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."

[1227] In recent years, as the introduction of robots has progressed in industrial sites such as factories and warehouses, efficient robot deployment plans and the selection of appropriate providers have become important issues. Until now, it was necessary to collect and analyze information from each provider individually and create deployment plans manually, which was time-consuming and labor-intensive, making it difficult to quickly formulate optimal deployment plans. Furthermore, because the evaluation criteria for providers were vague, there was a risk that the selected robot would not perform as expected. In this situation, there is a need to develop a system that can solve these issues.

[1228] 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.

[1229] In this invention, the server includes means for receiving requirements entered by a user and collecting web information based on the requirements, means for analyzing the collected web information and listing providers that fit the requirements, means for selecting the optimal provider from the list of providers, means for automatically generating a requirements definition document based on data entered by the user, means for presenting the generated requirements definition document to the user, acquiring revised requirements, and generating a final document, means for creating an efficient layout plan for industrial equipment, means for collecting and analyzing information for the layout plan from the Internet, and means for evaluating and comparing industrial equipment providers based on the collected information. This allows users to efficiently and quickly select an appropriate provider and formulate an optimal robot layout plan without hassle.

[1230] A "user" is a person or organization that inputs requests or data into the system.

[1231] "Requirements" are a list of conditions or capabilities that must be met by a system or project.

[1232] "Web information" refers to various types of information that are publicly available on the Internet.

[1233] "Collection" refers to gathering information for a specific purpose.

[1234] "Analysis" is the process of analyzing collected information and finding meaning and patterns.

[1235] A "provider" is a company or organization that offers a particular product or service.

[1236] "Listing" refers to the act of creating a list of items selected based on specific criteria.

[1237] "Selection" is the process of choosing the right thing from a large number of options.

[1238] A "requirements definition document" is a document that clearly states the requirements and conditions of a system or project.

[1239] "Auto-generated" refers to content that is automatically created by a system without human intervention.

[1240] "Industrial equipment" is a general term for machines and equipment used in industrial sites such as factories and warehouses.

[1241] A "layout plan" is a document for efficiently allocating industrial equipment and resources.

[1242] "Evaluation" refers to the act of judging the value and performance of the provider and selected items based on collected information.

[1243] "Comparison" refers to the act of comparing multiple selection items and checking their different features and performance.

[1244] This invention is a system that collects information based on requirements entered by the user, selects appropriate providers, and automatically generates an optimal layout plan. This system can collect web information, select providers, automatically generate requirements definition documents, create layout plans for industrial equipment, and evaluate and compare providers.

[1245] The main components of the system are as follows:

[1246] 1. Collecting web information

[1247] A user accesses the system and inputs requirements for industrial equipment (e.g., "Deployment plan for a new factory robot"). The terminal receives the input requirements and sends them to the server. The server uses the requirements to search for information on the Internet using specific keywords. This search uses the requests module and BeautifulSoup to retrieve information from web pages. The collected information is stored in the server's database for later analysis.

[1248] 2. Selection of provider

[1249] The server analyzes the collected web information and lists providers that meet the requirements. This analysis uses natural language processing technology to analyze the collected information. Sample links and page content are evaluated, and a list of appropriate providers is generated. For the generated providers, information such as each provider's evaluation and past project history is organized. The device displays this list on the user's screen, allowing the user to select the most suitable provider.

[1250] 3. Automatic generation of requirements definition documents

[1251] When the user inputs specific functional requirements and work content, the device sends this to the server. The server uses generative AI (e.g., OpenAI's text-davinci-003) to analyze the input data and automatically generate a requirements definition document. This generated requirements definition document is presented to the user via the device, and the user can review and modify the content.

[1252] 4. Creation of industrial equipment layout plans

[1253] The server generates an optimal industrial equipment layout plan based on the requirements entered by the user. This uses a generative AI model and prompts the user with the requirements. The generated layout plan is presented to the user, who can then make modifications as needed.

[1254] For example, if a user requests a "layout plan for a new factory robot," the procedure would be as follows:

[1255] 1. The user inputs requirements into the terminal, such as "Plan for the placement of a new factory robot," "Budget: 1 million yen," and "Required functions: object recognition, precision operation."

[1256] 2. The device sends the input data to the server.

[1257] 3. The server uses generative AI to collect information using keywords such as "factory robot provider evaluation" and lists appropriate providers.

[1258] 4. The device presents a list of providers to the user, and the user selects the most suitable provider.

[1259] 5. The user enters detailed requirements, which the server parses and generates a requirements specification document.

[1260] 6. Present the generated requirements specification document to the user, who then makes modifications and generates the final document.

[1261] 7. Based on the final document, a generative AI model is used to create an optimal robot placement plan.

[1262] By automating this entire process, users can efficiently create layout plans for industrial equipment without any hassle, which is expected to improve the quality of system development projects.

[1263] Example prompt sentence:

[1264] "User requirements input: New factory robot placement plan, budget 1 million yen, required functions: object recognition, precision operation"

[1265] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1266] Step 1:

[1267] The user inputs requirements into the terminal. For example, detailed requirements such as "Deployment plan for a new factory robot," "Budget: 1 million yen," and "Required functions: object recognition, precision operation" are input into the terminal. This input data is sent from the terminal to the server.

[1268] Step 2:

[1269] The server collects web information based on the received requirements. Specifically, it retrieves information on the Internet using specific keywords (e.g., "factory robot supplier reviews") using the requests module and BeautifulSoup. This collected information is stored in the server's database.

[1270] Step 3:

[1271] The server analyzes the web information stored in the database. During this process, it uses natural language processing technology to analyze the collected information and generate a list of providers that match the user's requirements. This list is organized based on the requested attributes (e.g., technical features, ratings, past project history).

[1272] Step 4:

[1273] The terminal displays the list provided by the server on the user's screen. The user looks at the list of providers and selects the provider that they think is most suitable. This selected information is then sent back to the server from the terminal.

[1274] Step 5:

[1275] The user inputs specific functional requirements and work content into the terminal. For example, when the user inputs specific requirements such as "object recognition" or "precise operation," this detailed input data is also sent from the terminal to the server.

[1276] Step 6:

[1277] The server analyzes the input data using generative AI (e.g., OpenAI's text-davinci-003) and automatically generates a requirements specification document. The generated requirements specification document is displayed to the user via their terminal.

[1278] Step 7:

[1279] The user checks and modifies the generated requirements definition document. When the user inputs the modified requirements into the terminal, the terminal sends them to the server, and the final requirements definition document is generated.

[1280] Step 8:

[1281] Based on the final requirements specification document, the server uses a generative AI model to create an optimal industrial equipment layout plan, which is also presented to the user for modification as needed.

[1282] Step 9:

[1283] After all the information is confirmed, an optimal industrial equipment layout plan is presented to the user, which includes the specific layout and operating parameters of the industrial equipment, allowing the user to efficiently and quickly implement robot layout.

[1284] 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.

[1285] The system of the present invention collects web information based on requirements entered by the user, selects appropriate providers, and automatically generates requirements definition documents. By combining it with an emotion engine that recognizes the user's emotions, it provides more user-friendly development support. Specific embodiments of this system are described below.

[1286] Web information collection and emotion recognition

[1287] The user inputs requirements for system development through a terminal, and the emotion engine analyzes the emotions (e.g., excitement, irritation, anxiety, etc.) that the user is expressing during the input.

[1288] The terminal transmits the input requirements and emotion data to the server.

[1289] The server instructs the generative AI to collect web information based on requirements, and collects information taking into account emotional data.

[1290] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[1291] Vendor Selection

[1292] The server analyzes the collected web information and lists providers (vendors) that meet the requirements, taking into account the user's emotional state.

[1293] The server organizes detailed information about the providers (e.g., ratings, past project history, specialized technologies, etc.) and sets priorities based on sentiment data.

[1294] The device displays a list of providers on the user's screen and provides advice and suggestions based on the emotion data.

[1295] The user selects an appropriate provider from the provider list and sends the result to the server via the terminal.

[1296] Automating requirements definition

[1297] The user inputs specific functional requirements into the device in detail, and the emotion engine re-recognizes and analyzes the emotions being input.

[1298] The device sends the detailed functional requirements and emotion data to the server.

[1299] The server uses generative AI to analyze detailed requirements and emotional data, automatically generating an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[1300] The device presents the initial requirements specification document to the user and also provides advice based on emotional data (e.g., "It seems you are unsure about this part. We recommend that you check it in more detail").

[1301] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[1302] The device sends the corrections and additional requirements and emotion data to the server.

[1303] The server reflects the revised and added requirements and generates the final requirements specification document. The final document is also provided in a format that takes user feelings into consideration.

[1304] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[1305] Specific examples

[1306] For example, a specific example will be given in which a user requests "construction of a small online shop" and feels frustrated while inputting information.

[1307] 1. When a user enters "Building a small online shop," "Budget: 1 million yen," and "Required functions: product search, cart, payment" into a terminal, the emotion engine detects irritation.

[1308] 2. The device sends the input data and irritation emotion data to the server.

[1309] 3. The server uses generative AI to search and collect information on the internet using keywords such as "online shop vendor reviews," taking into account emotional data.

[1310] 4. The server analyzes the collected information and presents a list of providers such as "Vendor X," "Vendor Y," and "Vendor Z," providing a quick and simple selection process for frustrated users.

[1311] 5. The device displays detailed information about the provider to the user along with suggestions based on emotional data (e.g., "Here are the vendors who can develop the product in the shortest time possible").

[1312] 6. The user selects "Vendor X" and "Vendor Y."

[1313] 7. When the user enters specific feature requirements (e.g., "Add filtering to product search" or "Support credit cards and PayPal for payments"), the emotion engine analyzes emotions again and displays appropriate advice based on the input.

[1314] 8. The device sends detailed requirements and emotion data to the server.

[1315] 9. The server uses generative AI to generate a requirements specification document and presents it to the frustrated user via their device in a format that is easy to understand.

[1316] By combining this system with an emotion engine, it is possible to take user emotions into consideration and provide more user-friendly and efficient system development support.

[1317] The processing flow will be explained below.

[1318] Step 1:

[1319] The user uses a terminal to input requirements for system development (e.g., "Development of an e-commerce site"), and the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data.

[1320] Step 2:

[1321] The terminal transmits the input requirements and emotion data to the server.

[1322] Step 3:

[1323] The server analyzes the received requirements and instructs the generative AI to collect web information, along with emotional data.

[1324] Step 4:

[1325] The server's generative AI performs an internet search based on specified keywords (e.g., "e-commerce site development vendor reviews"), taking into account emotional data and prioritizing the collection of information that best meets the user's needs.

[1326] Step 5:

[1327] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[1328] Step 6:

[1329] The server organizes and classifies the collected data, analyzes it based on vendor evaluation information and past project history, and takes into account sentiment data to create a list of the most suitable providers.

[1330] Step 7:

[1331] The device displays a list of providers on the user's screen and provides detailed information about each provider (e.g., ratings, past project history, specialized technologies, etc.), as well as advice and suggestions based on sentiment data (e.g., "Here are vendors who can respond immediately").

[1332] Step 8:

[1333] The user selects an appropriate provider from the provider list and transmits the selection result to the server via the terminal.

[1334] Step 9:

[1335] The user inputs specific functional requirements (e.g., "user registration function," "product search function," "cart function," "payment function") into the device in detail. The emotion engine re-recognizes and analyzes the emotions being input.

[1336] Step 10:

[1337] The device sends the detailed functional requirements and emotion data to the server.

[1338] Step 11:

[1339] The server uses generative AI to analyze detailed requirements and emotional data, automatically generating an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[1340] Step 12:

[1341] The device presents the initial requirements specification document to the user and also provides advice based on emotional data (e.g., "It seems you're unsure about this part. We recommend you check it out in more detail").

[1342] Step 13:

[1343] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[1344] Step 14:

[1345] The device sends the corrections and additional requirements and emotion data to the server.

[1346] Step 15:

[1347] The server reflects the modified and added data and generates the final requirements specification document. The final document is also provided in a format that takes user feelings into consideration.

[1348] Step 16:

[1349] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[1350] As described above, by combining emotion engines, it is possible to take into consideration the user's emotions and provide more user-friendly and efficient system development support.

[1351] Example 2

[1352] 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."

[1353] In modern system development, it is necessary to accurately and quickly grasp user requirements, select appropriate providers, and generate efficient requirements definition documents. It is also important to provide more user-friendly services that take into account the user's emotional state. The purpose of this invention is to solve these problems and provide an optimal system based on the user's requirements and emotions.

[1354] 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.

[1355] In this invention, the server includes means for receiving requirements and emotion data input by a user and collecting web information based on the requirements and emotion data, means for analyzing the collected web information and emotion data and listing providers that fit the requirements, means for selecting the most suitable provider from the list of providers and emotion data, and means for automatically generating a requirements definition document based on the data and emotion data input by the user. This makes it possible to reliably and efficiently support system development while taking user emotions into consideration.

[1356] A "user" is an entity that uses the system to input requirements and request the selection of a provider and the generation of a requirements definition document.

[1357] "Requirements" refer to the functions, specifications, and conditions that users require in system development, and information is collected and providers are selected based on these.

[1358] "Emotion data" is data that indicates the user's emotional state, and is generated by an engine that analyzes emotions such as excitement, irritation, and anxiety.

[1359] "Web information" refers to information related to system development that exists on the Internet, such as vendor evaluations, technical documents, project histories, etc.

[1360] "Provider" refers to the company or vendor that provides the products and services necessary for system development.

[1361] "Listing" means listing multiple providers that meet the conditions based on the collected information.

[1362] A "requirements definition document" is a document that organizes and analyzes user requirements and documents them as specific system specifications.

[1363] "Means" refers to methods, tools, or equipment for performing a specific function or process.

[1364] "Server" refers to the central computer system that processes data entered by users, collects and analyzes information, and automatically generates requirements definition documents.

[1365] "Device" refers to a device such as a computer or smartphone that a user uses to enter requirements or to review and modify the generated requirements specification document.

[1366] A "generative AI model" refers to an artificial intelligence technology that collects and analyzes web information based on user requirements and emotional data, and generates requirements definition documents.

[1367] "Automatic generation" means mechanically creating documents or lists based on given data and conditions, minimizing manual intervention.

[1368] This invention is a system that collects web information based on requirements entered by the user, selects appropriate providers, and automatically generates requirements definition documents. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more user-friendly development support.

[1369] System Overview

[1370] This system mainly consists of a server, terminals, and users. The server is a central computer system that collects web information, selects providers, and automatically generates requirements definition documents. The terminals are devices that users use to input requirements and to check and modify the generated requirements definition documents. The emotion engine recognizes the user's emotional state and uses it as data for analysis.

[1371] What the program does

[1372] 1. The user enters the requirements

[1373] Users input requirements for system development through a terminal, and the emotion engine analyzes the user's emotions in real time.

[1374] Hardware / software used: Device, emotion engine

[1375] Examples:

[1376] Building a small online shop

[1377] Budget: 1 million yen

[1378] Required features: product search, cart, payment

[1379] 2. The device sends data

[1380] The terminal transmits the input requirements and emotion data to the server.

[1381] 3. The server issues a command to collect information

[1382] The server uses a generative AI model to instruct the collection of web information based on requirements and emotional data.

[1383] Hardware / software used: Server, generative AI model

[1384] Example prompt:

[1385] Regarding the construction of a small online shop, please collect web information on the following items.

[1386] Products: Online Shop

[1387] Budget: 1 million yen

[1388] Required features: product search, cart, payment

[1389] Emotion: Frustration (wanting a quick and simple solution)

[1390] 4. The server collects and stores information

[1391] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[1392] 5. The server lists the sources

[1393] The server analyzes the collected web information and emotional data and lists providers that fit the requirements.

[1394] 6. The server organizes the details

[1395] The server organizes detailed information from the providers and sets priorities based on emotional data.

[1396] 7. The device presents the information to the user

[1397] The device displays a list of providers on the user's screen and provides advice and suggestions based on the emotion data.

[1398] 8. Users choose the provider

[1399] The user selects an appropriate provider from the provider list and sends the result to the server via the terminal.

[1400] 9. User inputs specific requirements

[1401] The user inputs specific functional requirements into the device in detail, and the emotion engine recognizes and analyzes the user's emotions again.

[1402] 10. The device sends data

[1403] The device sends detailed functional requirements and emotional data to the server.

[1404] 11. The server generates the requirements specification document

[1405] The server uses a generative AI model to analyze detailed requirements and emotional data to automatically generate an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[1406] 12. The device presents the document

[1407] The device presents the initial requirements definition document to the user and also provides advice based on emotional data.

[1408] 13. The user checks and modifies the document.

[1409] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[1410] 14. The device sends the correction data

[1411] The device sends the corrections and additional requirements and emotion data to the server.

[1412] 15. The server generates the final document

[1413] The server reflects the modified and added requirements and generates the final requirements specification document.

[1414] 16. The terminal presents the final document

[1415] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[1416] This system enables efficient system development support that takes user emotions into consideration. For example, if a user is feeling frustrated, a quick and simple selection process is presented and emotional advice is provided, providing a user-friendly experience.

[1417] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1418] Step 1:

[1419] User enters requirements

[1420] Input: The user inputs specific requirements for system development (e.g., building a small online shop, budget of 1 million yen, required functions: product search, cart, payment) into the terminal.

[1421] Data processing: The emotion engine analyzes the emotion (e.g., frustration) of the user's input in real time.

[1422] Output: The terminal generates requirement data and emotion data and sends them to the server.

[1423] Specific behavior: The user inputs requirements into the device through a keyboard or touch input, and the emotion engine captures the emotional state during that time.

[1424] Step 2:

[1425] The device sends data

[1426] Input: User-entered requirement and sentiment data.

[1427] Data processing: None.

[1428] Output: The terminal sends the requirement data and emotion data to the server.

[1429] Specific operation: The terminal sends the collected data to the server as a data packet.

[1430] Step 3:

[1431] The server instructs the collection of information

[1432] Input: Requirement data and emotion data sent from the terminal.

[1433] Data processing: The server instructs the generative AI model to collect web information using prompt statements (e.g., "Build a small online shop," "Budget: 1 million yen," "Required functions: product search, cart, payment," "Emotion: irritation").

[1434] Output: Web information collected by the generative AI model.

[1435] Specific operation: The server sends a prompt to the generative AI model and collects relevant information from the Internet.

[1436] Step 4:

[1437] The server collects and stores information

[1438] Input: Web information collected by a generative AI model.

[1439] Data processing: The server classifies and organizes the collected information and stores it in a database.

[1440] Output: Organized web information is stored in a database.

[1441] Specific operation: The server organizes information obtained from websites and databases based on emotional data and stores it in storage.

[1442] Step 5:

[1443] The server lists the providers

[1444] Input: Organized web information and emotion data.

[1445] Data processing: The server analyzes the information and lists providers that fit the requirements.

[1446] Output: A list of matching sources.

[1447] Specific operation: The server uses an information analysis algorithm to analyze the reputation and project history of providers and extract suitable providers.

[1448] Step 6:

[1449] The server organizes the details

[1450] Input: Listed provider details (ratings, past project history, specialized technologies, etc.) and sentiment data.

[1451] Data processing: The server organizes detailed information from the source and sets priorities based on emotion data.

[1452] Output: A prioritized list of providers.

[1453] Specific operation: The server prioritizes the rating data provided by the source and obtains feedback based on the user's emotional data.

[1454] Step 7:

[1455] The device presents the information to the user

[1456] Input: A prioritized list of sources and suggestions sent by the server.

[1457] Data processing: None.

[1458] Output: The user is presented with a list of sources and suggestions based on the sentiment data.

[1459] Specific operation: The terminal displays a list of providers and suggestions (e.g., "Here are the vendors who can develop in the shortest time possible") on the user's screen.

[1460] Step 8:

[1461] The user selects the provider

[1462] Input: Source list and proposal.

[1463] Data processing: The user selects the provider.

[1464] Output: The selection results are sent to the server via the terminal.

[1465] Specific operation: The user operates the terminal to select the provider (e.g., "Vendor X" or "Vendor Y") and send the data.

[1466] Step 9:

[1467] The user inputs specific requirements

[1468] Input: After selecting a provider, the user inputs specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payment").

[1469] Data processing: The emotion engine recognizes and analyzes the user's emotions again.

[1470] Output: Detailed functional requirement data and re-analyzed sentiment data are generated.

[1471] Specific behavior: When the user inputs specific requirements into the terminal, the emotion engine captures the emotional state during that time and transmits it back to the server.

[1472] Step 10:

[1473] The device sends data

[1474] Input: Detailed functional requirement data and re-analyzed sentiment data.

[1475] Data processing: None.

[1476] Output: Detailed functional requirement data and emotion data are sent to the server.

[1477] Specific operation: The terminal sends data to the server in packet format.

[1478] Step 11:

[1479] The server generates a requirements specification document.

[1480] Input: Detailed functional requirement data and re-analyzed sentiment data.

[1481] Data processing: The server uses a generative AI model to analyze detailed requirements and emotional data, and automatically generates an initial requirements specification document.

[1482] Output: A requirements document customized with tone and content that matches the user's emotions.

[1483] Specific operation: The server analyzes detailed functional requirements and emotion data and generates a matching requirements specification document.

[1484] Step 12:

[1485] The device presents the document

[1486] Input: Initial requirements document and advice based on sentiment data.

[1487] Data processing: None.

[1488] Output: A requirements specification document and advice is presented to the user.

[1489] Specific behavior: The device displays the document to the user and provides advice such as, "It seems you are concerned about this part. We recommend that you check it in more detail."

[1490] Step 13:

[1491] The user checks and modifies the document

[1492] Input: Initial requirements document and advice, modifications and additional requirements.

[1493] Data processing: The user checks the details of the requirements definition document and enters any deficiencies or additional requirements.

[1494] Output: Corrected and additional requirements data.

[1495] Specific operation: The user reviews the document and enters comments and corrections into the terminal.

[1496] Step 14:

[1497] The device sends correction data

[1498] Input: Correction / additional requirement data and sentiment data.

[1499] Data processing: None.

[1500] Output: Corrected and added requirement data and emotion data are sent to the server.

[1501] Specific operation: The terminal sends the correction data to the server.

[1502] Step 15:

[1503] The server generates the final document

[1504] Input: Correction / additional requirement data and sentiment data.

[1505] Data processing: The server reflects the modified and added requirements and generates the final requirements specification document.

[1506] Output: Final requirements document.

[1507] Specific operation: The server performs a final check on the requirements definition document and generates it in a format that takes emotional data into consideration.

[1508] Step 16:

[1509] The device presents the final document

[1510] Input: Final requirements document.

[1511] Data processing: None.

[1512] Output: The final requirements specification document is presented to the user.

[1513] Specific operation: The terminal displays the final requirements definition document to the user and obtains final confirmation and approval.

[1514] (Application example 2)

[1515] 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."

[1516] Modern system development support often involves a complex process: users input their requirements, then web information is collected and analyzed based on those requirements, and providers are listed and selected. Furthermore, the process ignores the user's mental state and emotions, resulting in a poor user experience and difficulty in providing efficient support. In particular, support that reflects the user's emotions is required when users need something urgent, such as in a food delivery app, or when satisfaction needs to be increased.

[1517] The specification process 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 means for receiving requirements input by a user and collecting web information based on the requirements, means for analyzing the collected web information and listing providers that fit the requirements, means for combining an emotion engine to select and list the most suitable providers based on the user's input data and emotion data, and means for automatically generating a requirements definition document based on the user's input data and emotion data. This makes it possible to collect web information and select providers quickly and effectively while taking the user's emotions into consideration, thereby improving the user experience.

[1518] "Requirements" refer to specific functions or conditions that users expect from a system.

[1519] "WEB information" refers to all data and documents accessible on the Internet, and is information collected in response to specific requests.

[1520] "Provider" refers to a vendor or company that supplies a particular service or product.

[1521] An "emotion engine" is a software or hardware system that analyzes a user's mental state and emotions and adjusts the behavior of an application based on the results.

[1522] "User experience" refers to the overall satisfaction and ease of use that a user feels when using a particular system or service.

[1523] A "requirements definition document" is a document that organizes and describes the specific requirements and conditions for a system or project.

[1524] A "server" is a computer system that receives user input data and performs various data processing, information collection, and document generation.

[1525] This invention automates the processes of user input, emotion analysis, web information collection, provider selection, and requirement definition document generation, thereby supporting system development that takes user emotions into consideration and optimizing food delivery. Specific embodiments are described below.

[1526] Overall system configuration

[1527] The system includes an emotion engine, a server, and a terminal as its main components.

[1528] Emotion Engine

[1529] The emotion engine receives user input data and analyzes the emotions (excitement, irritation, anxiety, etc.) in the input. The emotion engine uses natural language processing techniques and machine learning algorithms to detect emotions from the user's text.

[1530] server

[1531] The server implements several functions:

[1532] Receives requirements entered by the user and collects necessary web information.

[1533] Analyze the collected web information and create a list of providers that fit your requirements.

[1534] The optimal provider is selected based on the emotional data provided by the emotion engine.

[1535] A requirements definition document is generated based on the user's input data and emotion data.

[1536] Terminal

[1537] The terminal provides an interface for users to input requirements and communicates with the server. The analysis results of the emotion engine are also displayed on the terminal, helping users select providers and review requirements definition documents.

[1538] Data processing and calculations

[1539] The server processes the data in the following steps:

[1540] 1. Receive requirements and emotional data entered by the user and use generative AI to collect the necessary web information.

[1541] 2. Classify and organize the collected web information and create a list of providers.

[1542] 3. Based on the emotion data, the best providers are presented to the user in order of priority.

[1543] 4. Generate the final requirements document and customize the tone and content based on the sentiment data.

[1544] Specific examples

[1545] For example, if a user is on their lunch break and inputs, "I want pasta, but it needs to arrive within 30 minutes," and feels frustrated, the system will prioritize highly rated pasta restaurants that can deliver quickly. The emotion engine detects frustration and provides advice based on that.

[1546] Prompt Sentence Examples

[1547] User entered dish: Pasta

[1548] Budget: 2000 yen

[1549] Delivery time: within 30 minutes

[1550] User Emotion: Annoyance

[1551] In this way, this system can quickly and effectively collect web information and select providers while taking into consideration the user's feelings, thereby improving the user experience.

[1552] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1553] Step 1:

[1554] The user inputs their requirements into the device. For example, during their lunch break, the user might input, "I want to eat pasta, but it needs to arrive within 30 minutes." This input data, along with other requirements such as the type of food, budget, and delivery time, is saved on the device.

[1555] Input: User requirements (type of food, budget, delivery time)

[1556] Output: Input data on the terminal

[1557] Step 2:

[1558] The device sends the input data to the emotion engine, which then analyzes the emotion of the user as they type. For example, if someone types, "I want to eat pasta, but it needs to arrive within 30 minutes," the engine can detect the emotion of irritation.

[1559] Input: User requirements

[1560] Output: User emotion data (irritation)

[1561] Step 3:

[1562] The device sends user requirements and emotion data to the server, which receives it and starts various processes.

[1563] Input: User requirements, user emotion data

[1564] Output: Send data to the server

[1565] Step 4:

[1566] The server collects web information based on the received requirements. To do this, the server uses a generative AI model to search and collect information on the internet using keywords such as "food delivery pasta reviews."

[1567] Input: User requirements

[1568] Output: Collected web information

[1569] Step 5:

[1570] The server analyzes the collected web information, which is then categorized and organized according to user requirements, such as delivery time and ratings.

[1571] Input: Collected web information

[1572] Output: Categorized and organized web information

[1573] Step 6:

[1574] The server selects a provider (restaurant) from the collected web information based on the emotion data. For frustrated users, it prioritizes a list of highly rated providers who can deliver quickly.

[1575] Input: Categorized and organized web information, user emotion data

[1576] Output: List of providers

[1577] Step 7:

[1578] The device receives the list of providers from the server and presents it to the user. At the same time, it displays advice and suggestions based on the emotion data. For example, "Here are restaurants that can deliver in the shortest time."

[1579] Input: Source list, emotion data

[1580] Output: Display a list of providers and advice to the user

[1581] Step 8:

[1582] The user makes a specific selection using the device, for example, selecting "Restaurant A" and "Restaurant B," and then sends the result from the device to the server.

[1583] Input: User selection

[1584] Output: Send selection result data to the server

[1585] Step 9:

[1586] The user inputs specific functional requirements into the device in detail, such as "add a filtering function to the product search function" or "support credit cards and PayPal for payment." The emotion engine analyzes the user's emotions and displays appropriate advice.

[1587] Input: Detailed functional requirements

[1588] Output: Detailed functional requirements input data

[1589] Step 10:

[1590] The device sends detailed functional requirements and emotional data to the server, which then analyzes the detailed requirements and emotional data using a generative AI model to automatically generate an initial requirements definition document.

[1591] Input: Detailed functional requirements, sentiment data

[1592] Output: Initial requirements specification document

[1593] Step 11:

[1594] The initial requirements definition document generated by the server is presented to the user via the terminal, and after a confirmation and revision process, the final requirements definition document is generated. The tone and content are also customized based on the emotional data.

[1595] Input: Initial requirements definition document, user modified requirements

[1596] Output: Final requirements specification document

[1597] In this way, it is possible to quickly and effectively collect web information and select providers while taking into consideration the user's feelings, thereby improving the user experience.

[1598] 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.

[1599] 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.

[1600] 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.

[1601] [Fourth embodiment]

[1602] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1603] 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.

[1604] 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).

[1605] 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.

[1606] 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.

[1607] 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).

[1608] 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.

[1609] 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.

[1610] 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.

[1611] 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.

[1612] 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.

[1613] 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.

[1614] 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."

[1615] The system of the present invention collects information based on requirements entered by a user, selects appropriate providers, and automatically generates a requirements definition document, and includes the following main functions. Specific embodiments of the system are described below.

[1616] Collecting web information

[1617] The user inputs requirements for system development (e.g., "Development of an e-commerce site") through a terminal.

[1618] The terminal receives the input requirements and transmits them to the server.

[1619] The server passes the received requirements to a generative AI, which searches for information on the internet using specific keywords (e.g., "e-commerce site development vendor reviews").

[1620] The server collects relevant web information and stores it in a database, where it is categorized and organized for analysis.

[1621] Vendor Selection

[1622] The server analyzes the collected web information and lists providers (vendors) that meet the requirements.

[1623] The server generates a list of providers and organizes information such as each provider's reputation and past project history.

[1624] A list of providers from which the terminal was generated is displayed on the user's screen.

[1625] The user selects the most suitable provider from the displayed providers.

[1626] Automating requirements definition

[1627] The user inputs the specific requirements for the system (e.g., "user registration function," "product search function," "cart function," "payment function," etc.) into the terminal.

[1628] The terminal sends these detailed input data to the server.

[1629] The generative AI on the server analyzes the input data and automatically generates an initial requirements definition document.

[1630] The terminal presents the generated requirements definition document to the user.

[1631] When the user checks the requirements definition document and enters any missing points or additional requirements, the terminal sends it to the server.

[1632] The server reflects the added and modified requirements and generates the final requirements specification document.

[1633] The terminal presents the final requirements definition document to the user and requests final confirmation and approval.

[1634] Specific examples

[1635] For example, a specific example will be given in which a user requests "construction of a small online shop."

[1636] 1. The user enters the following into the terminal: "Building a small online shop," "Budget: 1 million yen," and "Required functions: product search, cart, payment."

[1637] 2. The device sends the input data to the server.

[1638] 3. The server uses generative AI to search and collect information on the Internet using keywords such as "online shop vendor reviews."

[1639] 4. The server analyzes the collected information and lists the providers, such as "Vendor X," "Vendor Y," and "Vendor Z."

[1640] 5. The device displays the details of the provider to the user.

[1641] 6. The user selects "Vendor X" and "Vendor Y."

[1642] 7. The user enters specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payment").

[1643] 8. The device sends detailed requirements to the server.

[1644] 9. The server generates a requirements definition document using generative AI and presents it to the user via their terminal for confirmation.

[1645] This system enables users to efficiently and quickly select appropriate providers and create requirements definition documents without any hassle, which is expected to improve the quality of system development projects.

[1646] The processing flow will be explained below.

[1647] Step 1:

[1648] A user uses a terminal to input requirements related to system development (e.g., "Development of an e-commerce site").

[1649] Step 2:

[1650] The terminal receives the input requirements and transmits them to the server.

[1651] Step 3:

[1652] The server analyzes the requirements it receives and instructs the generative AI to collect web information.

[1653] Step 4:

[1654] The generative AI on the server performs an internet search based on specified keywords (e.g., "e-commerce site development vendor reviews").

[1655] Step 5:

[1656] The server collects the information from the relevant websites and databases, converts it into an appropriate format and stores it in the database.

[1657] Step 6:

[1658] The server organizes and classifies the collected data and analyzes it based on the provider's (vendor's) evaluation information and past project history.

[1659] Step 7:

[1660] The server generates a list of providers that meet the requirements based on the analysis results.

[1661] Step 8:

[1662] The device displays a list of providers on the user's screen and provides detailed information about each provider (e.g., ratings, past project history, specialized technologies, etc.).

[1663] Step 9:

[1664] The user selects an appropriate provider from the displayed list of providers and transmits the selection result to the server via the terminal.

[1665] Step 10:

[1666] The user enters detailed functional requirements (e.g., "user registration function," "product search function," "cart function," "payment function") into the terminal.

[1667] Step 11:

[1668] The terminal sends the detailed functional requirements to the server.

[1669] Step 12:

[1670] The server uses generative AI to analyze the detailed requirements sent and automatically generate an initial requirements definition document.

[1671] Step 13:

[1672] The terminal presents the generated initial requirements definition document to the user for confirmation.

[1673] Step 14:

[1674] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[1675] Step 15:

[1676] The device sends the modified and additional requirements to the server.

[1677] Step 16:

[1678] The server reflects the added and modified data and generates the final requirements specification document.

[1679] Step 17:

[1680] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[1681] As a result, the entire process proceeds automatically and efficiently, significantly reducing the user's workload and improving the quality of system development.

[1682] Example 1

[1683] 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."

[1684] In conventional system development projects, the process of users entering requirements, collecting appropriate information, and generating a requirements definition document required a great deal of time and effort. Furthermore, selecting the optimal provider and generating the requirements definition document were often done manually, resulting in issues with efficiency and accuracy. This resulted in problems with the quality and speed of system development projects.

[1685] 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.

[1686] In this invention, the server includes means for receiving requirements entered by a user and collecting information on the Internet based on the requirements, means for classifying and organizing the collected information and listing providers that meet the requirements, means for selecting the most suitable provider based on the provider's evaluation and past project history, etc., and means for automatically generating a requirements definition document based on detailed functional requirements from the user. This allows the user to efficiently and quickly select an appropriate provider without hassle and generate a highly accurate requirements definition document.

[1687] A "user" is a user who uses the system to input requirements and request the selection of the most suitable provider and the generation of a requirements definition document.

[1688] "Requirements" are information that expresses the functions and conditions that users require when developing a system.

[1689] "Information gathering means" is a function that searches for and acquires related information on the Internet based on requirements entered by the user.

[1690] "Classification and organization means" is a function that systematically organizes collected information and stores it in a database for later analysis and selection.

[1691] A "provider" is a business or organization that develops systems or provides services, selected based on the user's requirements.

[1692] The "listing method" is a function that generates a list of providers that meet the requirements based on classified and organized information.

[1693] "Evaluation" refers to the criteria for judging reliability and suitability based on the provider's service quality and past project history.

[1694] The "selection method" is a function for selecting the most suitable provider from the listed providers.

[1695] "Detailed functional requirements" are information that details the system functions and conditions that users specifically require.

[1696] A "requirements definition document" is a specification document required for system development that is automatically generated based on detailed functional requirements entered by the user.

[1697] The "automatic generation means" is a function that analyzes the information entered by the user and automatically creates a requirements definition document.

[1698] The system of the present invention collects information based on requirements entered by a user, selects appropriate providers, and automatically generates a requirements definition document. This system includes a server, a terminal, and a generative AI model. Specific embodiments of the system are described in detail below.

[1699] Collecting web information

[1700] A user uses a terminal to input requirements for system development (e.g., "Build a small online shop," "Budget: 1 million yen," "Required functions: product search, cart, payment"). The terminal formats this requirements data and sends it to a server. The server passes the received requirements data to a generative AI model (e.g., GPT-3) and calls an internet search engine API to search for information on the internet using specific keywords (e.g., "online shop vendor reviews"). The collected information is stored in a database on the server and systematically categorized and organized.

[1701] Vendor Selection

[1702] The server analyzes the information stored in the database and lists providers (vendors) that meet the user's requirements. During this process, generative AI analyzes the vendors' ratings and past project history to select reliable providers. The device receives the list of providers from the server and displays it on the user's screen. This list includes detailed information such as each vendor's rating, project history, and services provided.

[1703] Automating requirements definition

[1704] After the user reviews the list of providers and selects the most suitable provider, they enter specific functional requirements into the device. Examples of input include "add a filtering function to the product search function" and "support credit cards and PayPal for payment." The device formats the detailed requirements data and sends it back to the server. A generative AI model on the server analyzes this requirements data and automatically generates an initial requirements specification document. The requirements specification document contains detailed descriptions of the specific requirements entered by the user.

[1705] Review, revise and approve requirements definition documents

[1706] The generated requirements definition document is presented to the user via the terminal. The user reviews the document and inputs any deficiencies or corrections that need to be made. The terminal sends this to the server, which then regenerates the revised requirements definition document using a generative AI model. The final generated requirements definition document is then presented to the user via the terminal, who makes a final review and approves the document. At this stage, the final requirements definition document is finalized and serves as the basis for the system development project to proceed.

[1707] This system allows users to efficiently and quickly select appropriate providers without hassle and generate highly accurate requirements definition documents. Specific examples of prompt sentences are shown below.

[1708] Prompt Sentence Examples

[1709] "Building a small online shop"

[1710] "Online Shop Vendor Evaluation"

[1711] "Added filtering function to product search function"

[1712] Supports credit card and PayPal payments

[1713] As described above, this system allows users to efficiently carry out each step of system development, which is expected to improve the overall project quality.

[1714] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1715] Step 1:

[1716] The user inputs the requirements for system development into the terminal. As an example, we use "Building a small online shop," "Budget 1 million yen," and "Required functions: product search, cart, payment." Once the user has completed the input, the terminal sends it to the server.

[1717] Input: User-entered requirements information

[1718] Output: Formatted requirements data sent to the server

[1719] Step 2:

[1720] The server passes the received requirements data to the generative AI model, which then collects information on the Internet using specific keywords (e.g., "online shop vendor evaluation"). The server then calls the Internet search engine API to retrieve the information and stores it in a database.

[1721] Input: Requirement data received by the server

[1722] Output: Collected information stored in a database

[1723] Step 3:

[1724] The server analyzes the information stored in the database and uses a generative AI model to list providers (vendors) that meet the user's requirements. The server analyzes provider ratings and past project history to select reliable providers.

[1725] Input: Collected information stored in a database

[1726] Output: A list of matching sources

[1727] Step 4:

[1728] The terminal receives a list of providers from the server and displays it on the user's screen. This list includes detailed information such as each provider's rating, project history, and services provided, allowing the user to review and rate the list.

[1729] Input: A list of providers sent from the server

[1730] Output: A list of providers displayed to the user.

[1731] Step 5:

[1732] The user selects the most suitable provider from the displayed providers. The information of the provider selected by the user is entered into the terminal, and the terminal sends it to the server.

[1733] Input: User-selected provider

[1734] Output: Send the selected provider information to the server

[1735] Step 6:

[1736] The user enters specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payments") into the terminal. The user's detailed requirements data is formatted by the terminal and sent to the server.

[1737] Input: Detailed functional requirements entered by the user

[1738] Output: Send formatted requirements data to the server

[1739] Step 7:

[1740] The server uses a generative AI model to analyze the user's detailed requirements data and automatically generate an initial requirements specification document, which is then sent to the device.

[1741] Input: Detailed functional requirements data

[1742] Output: Generated initial requirements document

[1743] Step 8:

[1744] The device presents the generated requirements specification document to the user. The user checks the document and re-enters any missing or necessary corrections into the device. This is sent to the server, and the generative AI model regenerates the requirements specification document reflecting the corrections.

[1745] Input: Changes and corrections requirements from users

[1746] Output: Modified requirements document

[1747] Step 9:

[1748] The terminal presents the final requirements definition document to the user, who then confirms and approves it. The server then finalizes the requirements definition document, which becomes the basis for starting the system development project.

[1749] Input: Finalized and approved requirements document

[1750] Output: Final requirements document

[1751] Through the above processing steps, the user can efficiently and quickly select an appropriate provider without much effort and generate a highly accurate requirements definition document.

[1752] (Application example 1)

[1753] 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."

[1754] In recent years, as the introduction of robots has progressed in industrial sites such as factories and warehouses, efficient robot deployment plans and the selection of appropriate providers have become important issues. Until now, it was necessary to collect and analyze information from each provider individually and create deployment plans manually, which was time-consuming and labor-intensive, making it difficult to quickly formulate optimal deployment plans. Furthermore, because the evaluation criteria for providers were vague, there was a risk that the selected robot would not perform as expected. In this situation, there is a need to develop a system that can solve these issues.

[1755] 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.

[1756] In this invention, the server includes means for receiving requirements entered by a user and collecting web information based on the requirements, means for analyzing the collected web information and listing providers that fit the requirements, means for selecting the optimal provider from the list of providers, means for automatically generating a requirements definition document based on data entered by the user, means for presenting the generated requirements definition document to the user, acquiring revised requirements, and generating a final document, means for creating an efficient layout plan for industrial equipment, means for collecting and analyzing information for the layout plan from the Internet, and means for evaluating and comparing industrial equipment providers based on the collected information. This allows users to efficiently and quickly select an appropriate provider and formulate an optimal robot layout plan without hassle.

[1757] A "user" is a person or organization that inputs requests or data into the system.

[1758] "Requirements" are a list of conditions or capabilities that must be met by a system or project.

[1759] "Web information" refers to various types of information that are publicly available on the Internet.

[1760] "Collection" refers to gathering information for a specific purpose.

[1761] "Analysis" is the process of analyzing collected information and finding meaning and patterns.

[1762] A "provider" is a company or organization that offers a particular product or service.

[1763] "Listing" refers to the act of creating a list of items selected based on specific criteria.

[1764] "Selection" is the process of choosing the right thing from a large number of options.

[1765] A "requirements definition document" is a document that clearly states the requirements and conditions of a system or project.

[1766] "Auto-generated" refers to content that is automatically created by a system without human intervention.

[1767] "Industrial equipment" is a general term for machines and equipment used in industrial sites such as factories and warehouses.

[1768] A "layout plan" is a document for efficiently allocating industrial equipment and resources.

[1769] "Evaluation" refers to the act of judging the value and performance of the provider and selected items based on collected information.

[1770] "Comparison" refers to the act of comparing multiple selection items and checking their different features and performance.

[1771] This invention is a system that collects information based on requirements entered by the user, selects appropriate providers, and automatically generates an optimal layout plan. This system can collect web information, select providers, automatically generate requirements definition documents, create layout plans for industrial equipment, and evaluate and compare providers.

[1772] The main components of the system are as follows:

[1773] 1. Collecting web information

[1774] A user accesses the system and inputs requirements for industrial equipment (e.g., "Deployment plan for a new factory robot"). The terminal receives the input requirements and sends them to the server. The server uses the requirements to search for information on the Internet using specific keywords. This search uses the requests module and BeautifulSoup to retrieve information from web pages. The collected information is stored in the server's database for later analysis.

[1775] 2. Selection of provider

[1776] The server analyzes the collected web information and lists providers that meet the requirements. This analysis uses natural language processing technology to analyze the collected information. Sample links and page content are evaluated, and a list of appropriate providers is generated. For the generated providers, information such as each provider's evaluation and past project history is organized. The device displays this list on the user's screen, allowing the user to select the most suitable provider.

[1777] 3. Automatic generation of requirements definition documents

[1778] When the user inputs specific functional requirements and work content, the device sends this to the server. The server uses generative AI (e.g., OpenAI's text-davinci-003) to analyze the input data and automatically generate a requirements definition document. This generated requirements definition document is presented to the user via the device, and the user can review and modify the content.

[1779] 4. Creation of industrial equipment layout plans

[1780] The server generates an optimal industrial equipment layout plan based on the requirements entered by the user. This uses a generative AI model and prompts the user with the requirements. The generated layout plan is presented to the user, who can then make modifications as needed.

[1781] For example, if a user requests a "layout plan for a new factory robot," the procedure would be as follows:

[1782] 1. The user inputs requirements into the terminal, such as "Plan for the placement of a new factory robot," "Budget: 1 million yen," and "Required functions: object recognition, precision operation."

[1783] 2. The device sends the input data to the server.

[1784] 3. The server uses generative AI to collect information using keywords such as "factory robot provider evaluation" and lists appropriate providers.

[1785] 4. The device presents a list of providers to the user, and the user selects the most suitable provider.

[1786] 5. The user enters detailed requirements, which the server parses and generates a requirements specification document.

[1787] 6. Present the generated requirements specification document to the user, who then makes modifications and generates the final document.

[1788] 7. Based on the final document, a generative AI model is used to create an optimal robot placement plan.

[1789] By automating this entire process, users can efficiently create layout plans for industrial equipment without any hassle, which is expected to improve the quality of system development projects.

[1790] Example prompt sentence:

[1791] "User requirements input: New factory robot placement plan, budget 1 million yen, required functions: object recognition, precision operation"

[1792] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1793] Step 1:

[1794] The user inputs requirements into the terminal. For example, detailed requirements such as "Deployment plan for a new factory robot," "Budget: 1 million yen," and "Required functions: object recognition, precision operation" are input into the terminal. This input data is sent from the terminal to the server.

[1795] Step 2:

[1796] The server collects web information based on the received requirements. Specifically, it retrieves information on the Internet using specific keywords (e.g., "factory robot supplier reviews") using the requests module and BeautifulSoup. This collected information is stored in the server's database.

[1797] Step 3:

[1798] The server analyzes the web information stored in the database. During this process, it uses natural language processing technology to analyze the collected information and generate a list of providers that match the user's requirements. This list is organized based on the requested attributes (e.g., technical features, ratings, past project history).

[1799] Step 4:

[1800] The terminal displays the list provided by the server on the user's screen. The user looks at the list of providers and selects the provider that they think is most suitable. This selected information is then sent back to the server from the terminal.

[1801] Step 5:

[1802] The user inputs specific functional requirements and work content into the terminal. For example, when the user inputs specific requirements such as "object recognition" or "precise operation," this detailed input data is also sent from the terminal to the server.

[1803] Step 6:

[1804] The server analyzes the input data using generative AI (e.g., OpenAI's text-davinci-003) and automatically generates a requirements specification document. The generated requirements specification document is displayed to the user via their terminal.

[1805] Step 7:

[1806] The user checks and modifies the generated requirements definition document. When the user inputs the modified requirements into the terminal, the terminal sends them to the server, and the final requirements definition document is generated.

[1807] Step 8:

[1808] Based on the final requirements specification document, the server uses a generative AI model to create an optimal industrial equipment layout plan, which is also presented to the user for modification as needed.

[1809] Step 9:

[1810] After all the information is confirmed, an optimal industrial equipment layout plan is presented to the user, which includes the specific layout and operating parameters of the industrial equipment, allowing the user to efficiently and quickly implement robot layout.

[1811] 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.

[1812] The system of the present invention collects web information based on requirements entered by the user, selects appropriate providers, and automatically generates requirements definition documents. By combining it with an emotion engine that recognizes the user's emotions, it provides more user-friendly development support. Specific embodiments of this system are described below.

[1813] Web information collection and emotion recognition

[1814] The user inputs requirements for system development through a terminal, and the emotion engine analyzes the emotions (e.g., excitement, irritation, anxiety, etc.) that the user is expressing during the input.

[1815] The terminal transmits the input requirements and emotion data to the server.

[1816] The server instructs the generative AI to collect web information based on requirements, and collects information taking into account emotional data.

[1817] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[1818] Vendor Selection

[1819] The server analyzes the collected web information and lists providers (vendors) that meet the requirements, taking into account the user's emotional state.

[1820] The server organizes detailed information about the providers (e.g., ratings, past project history, specialized technologies, etc.) and sets priorities based on sentiment data.

[1821] The device displays a list of providers on the user's screen and provides advice and suggestions based on the emotion data.

[1822] The user selects an appropriate provider from the provider list and sends the result to the server via the terminal.

[1823] Automating requirements definition

[1824] The user inputs specific functional requirements into the device in detail, and the emotion engine re-recognizes and analyzes the emotions being input.

[1825] The device sends the detailed functional requirements and emotion data to the server.

[1826] The server uses generative AI to analyze detailed requirements and emotional data, automatically generating an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[1827] The device presents the initial requirements specification document to the user and also provides advice based on emotional data (e.g., "It seems you are unsure about this part. We recommend that you check it in more detail").

[1828] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[1829] The device sends the corrections and additional requirements and emotion data to the server.

[1830] The server reflects the revised and added requirements and generates the final requirements specification document. The final document is also provided in a format that takes user feelings into consideration.

[1831] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[1832] Specific examples

[1833] For example, a specific example will be given in which a user requests "construction of a small online shop" and feels frustrated while inputting information.

[1834] 1. When a user enters "Building a small online shop," "Budget: 1 million yen," and "Required functions: product search, cart, payment" into a terminal, the emotion engine detects irritation.

[1835] 2. The device sends the input data and irritation emotion data to the server.

[1836] 3. The server uses generative AI to search and collect information on the internet using keywords such as "online shop vendor reviews," taking into account emotional data.

[1837] 4. The server analyzes the collected information and presents a list of providers such as "Vendor X," "Vendor Y," and "Vendor Z," providing a quick and simple selection process for frustrated users.

[1838] 5. The device displays detailed information about the provider to the user along with suggestions based on emotional data (e.g., "Here are the vendors who can develop the product in the shortest time possible").

[1839] 6. The user selects "Vendor X" and "Vendor Y."

[1840] 7. When the user enters specific feature requirements (e.g., "Add filtering to product search" or "Support credit cards and PayPal for payments"), the emotion engine analyzes emotions again and displays appropriate advice based on the input.

[1841] 8. The device sends detailed requirements and emotion data to the server.

[1842] 9. The server uses generative AI to generate a requirements specification document and presents it to the frustrated user via their device in a format that is easy to understand.

[1843] By combining this system with an emotion engine, it is possible to take user emotions into consideration and provide more user-friendly and efficient system development support.

[1844] The processing flow will be explained below.

[1845] Step 1:

[1846] The user uses a terminal to input requirements for system development (e.g., "Development of an e-commerce site"), and the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data.

[1847] Step 2:

[1848] The terminal transmits the input requirements and emotion data to the server.

[1849] Step 3:

[1850] The server analyzes the received requirements and instructs the generative AI to collect web information, along with emotional data.

[1851] Step 4:

[1852] The server's generative AI performs an internet search based on specified keywords (e.g., "e-commerce site development vendor reviews"), taking into account emotional data and prioritizing the collection of information that best meets the user's needs.

[1853] Step 5:

[1854] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[1855] Step 6:

[1856] The server organizes and classifies the collected data, analyzes it based on vendor evaluation information and past project history, and takes into account sentiment data to create a list of the most suitable providers.

[1857] Step 7:

[1858] The device displays a list of providers on the user's screen and provides detailed information about each provider (e.g., ratings, past project history, specialized technologies, etc.), as well as advice and suggestions based on sentiment data (e.g., "Here are vendors who can respond immediately").

[1859] Step 8:

[1860] The user selects an appropriate provider from the provider list and transmits the selection result to the server via the terminal.

[1861] Step 9:

[1862] The user inputs specific functional requirements (e.g., "user registration function," "product search function," "cart function," "payment function") into the device in detail. The emotion engine re-recognizes and analyzes the emotions being input.

[1863] Step 10:

[1864] The device sends the detailed functional requirements and emotion data to the server.

[1865] Step 11:

[1866] The server uses generative AI to analyze detailed requirements and emotional data, automatically generating an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[1867] Step 12:

[1868] The device presents the initial requirements specification document to the user and also provides advice based on emotional data (e.g., "It seems you're unsure about this part. We recommend you check it out in more detail").

[1869] Step 13:

[1870] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[1871] Step 14:

[1872] The device sends the corrections and additional requirements and emotion data to the server.

[1873] Step 15:

[1874] The server reflects the modified and added data and generates the final requirements specification document. The final document is also provided in a format that takes user feelings into consideration.

[1875] Step 16:

[1876] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[1877] As described above, by combining emotion engines, it is possible to take into consideration the user's emotions and provide more user-friendly and efficient system development support.

[1878] Example 2

[1879] 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."

[1880] In modern system development, it is necessary to accurately and quickly grasp user requirements, select appropriate providers, and generate efficient requirements definition documents. It is also important to provide more user-friendly services that take into account the user's emotional state. The purpose of this invention is to solve these problems and provide an optimal system based on the user's requirements and emotions.

[1881] 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.

[1882] In this invention, the server includes means for receiving requirements and emotion data input by a user and collecting web information based on the requirements and emotion data, means for analyzing the collected web information and emotion data and listing providers that fit the requirements, means for selecting the most suitable provider from the list of providers and emotion data, and means for automatically generating a requirements definition document based on the data and emotion data input by the user. This makes it possible to reliably and efficiently support system development while taking user emotions into consideration.

[1883] A "user" is an entity that uses the system to input requirements and request the selection of a provider and the generation of a requirements definition document.

[1884] "Requirements" refer to the functions, specifications, and conditions that users require in system development, and information is collected and providers are selected based on these.

[1885] "Emotion data" is data that indicates the user's emotional state, and is generated by an engine that analyzes emotions such as excitement, irritation, and anxiety.

[1886] "Web information" refers to information related to system development that exists on the Internet, such as vendor evaluations, technical documents, project histories, etc.

[1887] "Provider" refers to the company or vendor that provides the products and services necessary for system development.

[1888] "Listing" means listing multiple providers that meet the conditions based on the collected information.

[1889] A "requirements definition document" is a document that organizes and analyzes user requirements and documents them as specific system specifications.

[1890] "Means" refers to methods, tools, or equipment for performing a specific function or process.

[1891] "Server" refers to the central computer system that processes data entered by users, collects and analyzes information, and automatically generates requirements definition documents.

[1892] "Device" refers to a device such as a computer or smartphone that a user uses to enter requirements or to review and modify the generated requirements specification document.

[1893] A "generative AI model" refers to an artificial intelligence technology that collects and analyzes web information based on user requirements and emotional data, and generates requirements definition documents.

[1894] "Automatic generation" means mechanically creating documents or lists based on given data and conditions, minimizing manual intervention.

[1895] This invention is a system that collects web information based on requirements entered by the user, selects appropriate providers, and automatically generates requirements definition documents. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more user-friendly development support.

[1896] System Overview

[1897] This system mainly consists of a server, terminals, and users. The server is a central computer system that collects web information, selects providers, and automatically generates requirements definition documents. The terminals are devices that users use to input requirements and to check and modify the generated requirements definition documents. The emotion engine recognizes the user's emotional state and uses it as data for analysis.

[1898] What the program does

[1899] 1. The user enters the requirements

[1900] Users input requirements for system development through a terminal, and the emotion engine analyzes the user's emotions in real time.

[1901] Hardware / software used: Device, emotion engine

[1902] Examples:

[1903] Building a small online shop

[1904] Budget: 1 million yen

[1905] Required features: product search, cart, payment

[1906] 2. The device sends data

[1907] The terminal transmits the input requirements and emotion data to the server.

[1908] 3. The server issues a command to collect information

[1909] The server uses a generative AI model to instruct the collection of web information based on requirements and emotional data.

[1910] Hardware / software used: Server, generative AI model

[1911] Example prompt:

[1912] Regarding the construction of a small online shop, please collect web information on the following items.

[1913] Products: Online Shop

[1914] Budget: 1 million yen

[1915] Required features: product search, cart, payment

[1916] Emotion: Frustration (wanting a quick and simple solution)

[1917] 4. The server collects and stores information

[1918] The server collects information from related websites and databases and stores it in a database. The collected information is categorized and organized based on emotion data.

[1919] 5. The server lists the sources

[1920] The server analyzes the collected web information and emotional data and lists providers that fit the requirements.

[1921] 6. The server organizes the details

[1922] The server organizes detailed information from the providers and sets priorities based on emotional data.

[1923] 7. The device presents the information to the user

[1924] The device displays a list of providers on the user's screen and provides advice and suggestions based on the emotion data.

[1925] 8. Users choose the provider

[1926] The user selects an appropriate provider from the provider list and sends the result to the server via the terminal.

[1927] 9. User inputs specific requirements

[1928] The user inputs specific functional requirements into the device in detail, and the emotion engine recognizes and analyzes the user's emotions again.

[1929] 10. The device sends data

[1930] The device sends detailed functional requirements and emotional data to the server.

[1931] 11. The server generates the requirements specification document

[1932] The server uses a generative AI model to analyze detailed requirements and emotional data to automatically generate an initial requirements specification document, which is customized with tone and content that reflects the user's emotions.

[1933] 12. The device presents the document

[1934] The device presents the initial requirements definition document to the user and also provides advice based on emotional data.

[1935] 13. The user checks and modifies the document.

[1936] The user checks the requirements specification document and enters any deficiencies or additional requirements.

[1937] 14. The device sends the correction data

[1938] The device sends the corrections and additional requirements and emotion data to the server.

[1939] 15. The server generates the final document

[1940] The server reflects the modified and added requirements and generates the final requirements specification document.

[1941] 16. The terminal presents the final document

[1942] The terminal presents the final requirements definition document to the user for final confirmation and approval.

[1943] This system enables efficient system development support that takes user emotions into consideration. For example, if a user is feeling frustrated, a quick and simple selection process is presented and emotional advice is provided, providing a user-friendly experience.

[1944] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1945] Step 1:

[1946] User enters requirements

[1947] Input: The user inputs specific requirements for system development (e.g., building a small online shop, budget of 1 million yen, required functions: product search, cart, payment) into the terminal.

[1948] Data processing: The emotion engine analyzes the emotion (e.g., frustration) of the user's input in real time.

[1949] Output: The terminal generates requirement data and emotion data and sends them to the server.

[1950] Specific behavior: The user inputs requirements into the device through a keyboard or touch input, and the emotion engine captures the emotional state during that time.

[1951] Step 2:

[1952] The device sends data

[1953] Input: User-entered requirement and sentiment data.

[1954] Data processing: None.

[1955] Output: The terminal sends the requirement data and emotion data to the server.

[1956] Specific operation: The terminal sends the collected data to the server as a data packet.

[1957] Step 3:

[1958] The server instructs the collection of information

[1959] Input: Requirement data and emotion data sent from the terminal.

[1960] Data processing: The server instructs the generative AI model to collect web information using prompt statements (e.g., "Build a small online shop," "Budget: 1 million yen," "Required functions: product search, cart, payment," "Emotion: irritation").

[1961] Output: Web information collected by the generative AI model.

[1962] Specific operation: The server sends a prompt to the generative AI model and collects relevant information from the Internet.

[1963] Step 4:

[1964] The server collects and stores information

[1965] Input: Web information collected by a generative AI model.

[1966] Data processing: The server classifies and organizes the collected information and stores it in a database.

[1967] Output: Organized web information is stored in a database.

[1968] Specific operation: The server organizes information obtained from websites and databases based on emotional data and stores it in storage.

[1969] Step 5:

[1970] The server lists the providers

[1971] Input: Organized web information and emotion data.

[1972] Data processing: The server analyzes the information and lists providers that fit the requirements.

[1973] Output: A list of matching sources.

[1974] Specific operation: The server uses an information analysis algorithm to analyze the reputation and project history of providers and extract suitable providers.

[1975] Step 6:

[1976] The server organizes the details

[1977] Input: Listed provider details (ratings, past project history, specialized technologies, etc.) and sentiment data.

[1978] Data processing: The server organizes detailed information from the source and sets priorities based on emotion data.

[1979] Output: A prioritized list of providers.

[1980] Specific operation: The server prioritizes the rating data provided by the source and obtains feedback based on the user's emotional data.

[1981] Step 7:

[1982] The device presents the information to the user

[1983] Input: A prioritized list of sources and suggestions sent by the server.

[1984] Data processing: None.

[1985] Output: The user is presented with a list of sources and suggestions based on the sentiment data.

[1986] Specific operation: The terminal displays a list of providers and suggestions (e.g., "Here are the vendors who can develop in the shortest time possible") on the user's screen.

[1987] Step 8:

[1988] The user selects the provider

[1989] Input: Source list and proposal.

[1990] Data processing: The user selects the provider.

[1991] Output: The selection results are sent to the server via the terminal.

[1992] Specific operation: The user operates the terminal to select the provider (e.g., "Vendor X" or "Vendor Y") and send the data.

[1993] Step 9:

[1994] The user inputs specific requirements

[1995] Input: After selecting a provider, the user inputs specific functional requirements (e.g., "Add a filtering function to the product search function" and "Support credit cards and PayPal for payment").

[1996] Data processing: The emotion engine recognizes and analyzes the user's emotions again.

[1997] Output: Detailed functional requirement data and re-analyzed sentiment data are generated.

[1998] Specific behavior: When the user inputs specific requirements into the terminal, the emotion engine captures the emotional state during that time and transmits it back to the server.

[1999] Step 10:

[2000] The device sends data

[2001] Input: Detailed functional requirement data and re-analyzed sentiment data.

[2002] Data processing: None.

[2003] Output: Detailed functional requirement data and emotion data are sent to the server.

[2004] Specific operation: The terminal sends data to the server in packet format.

[2005] Step 11:

[2006] The server generates a requirements specification document.

[2007] Input: Detailed functional requirement data and re-analyzed sentiment data.

[2008] Data processing: The server uses a generative AI model to analyze detailed requirements and emotional data, and automatically generates an initial requirements specification document.

[2009] Output: A requirements document customized with tone and content that matches the user's emotions.

[2010] Specific operation: The server analyzes detailed functional requirements and emotion data and generates a matching requirements specification document.

[2011] Step 12:

[2012] The device presents the document

[2013] Input: Initial requirements document and advice based on sentiment data.

[2014] Data processing: None.

[2015] Output: A requirements specification document and advice is presented to the user.

[2016] Specific behavior: The device displays the document to the user and provides advice such as, "It seems you are concerned about this part. We recommend that you check it in more detail."

[2017] Step 13:

[2018] The user checks and modifies the document

[2019] Input: Initial requirements document and advice, modifications and additional requirements.

[2020] Data processing: The user checks the details of the requirements definition document and enters any deficiencies or additional requirements.

[2021] Output: Corrected and additional requirements data.

[2022] Specific operation: The user reviews the document and enters comments and corrections into the terminal.

[2023] Step 14:

[2024] The device sends correction data

[2025] Input: Correction / additional requirement data and sentiment data.

[2026] Data processing: None.

[2027] Output: Corrected and added requirement data and emotion data are sent to the server.

[2028] Specific operation: The terminal sends the correction data to the server.

[2029] Step 15:

[2030] The server generates the final document

[2031] Input: Correction / additional requirement data and sentiment data.

[2032] Data processing: The server reflects the modified and added requirements and generates the final requirements specification document.

[2033] Output: Final requirements document.

[2034] Specific operation: The server performs a final check on the requirements definition document and generates it in a format that takes emotional data into consideration.

[2035] Step 16:

[2036] The device presents the final document

[2037] Input: Final requirements document.

[2038] Data processing: None.

[2039] Output: The final requirements specification document is presented to the user.

[2040] Specific operation: The terminal displays the final requirements definition document to the user and obtains final confirmation and approval.

[2041] (Application example 2)

[2042] 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."

[2043] Modern system development support often involves a complex process: users input their requirements, then web information is collected and analyzed based on those requirements, and providers are listed and selected. Furthermore, the process ignores the user's mental state and emotions, resulting in a poor user experience and difficulty in providing efficient support. In particular, support that reflects the user's emotions is required when users need something urgent, such as in a food delivery app, or when satisfaction needs to be increased.

[2044] The specification process 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 means for receiving requirements input by a user and collecting web information based on the requirements, means for analyzing the collected web information and listing providers that fit the requirements, means for combining an emotion engine to select and list the most suitable providers based on the user's input data and emotion data, and means for automatically generating a requirements definition document based on the user's input data and emotion data. This makes it possible to collect web information and select providers quickly and effectively while taking the user's emotions into consideration, thereby improving the user experience.

[2045] "Requirements" refer to specific functions or conditions that users expect from a system.

[2046] "WEB information" refers to all data and documents accessible on the Internet, and is information collected in response to specific requests.

[2047] "Provider" refers to a vendor or company that supplies a particular service or product.

[2048] An "emotion engine" is a software or hardware system that analyzes a user's mental state and emotions and adjusts the behavior of an application based on the results.

[2049] "User experience" refers to the overall satisfaction and ease of use that a user feels when using a particular system or service.

[2050] A "requirements definition document" is a document that organizes and describes the specific requirements and conditions for a system or project.

[2051] A "server" is a computer system that receives user input data and performs various data processing, information collection, and document generation.

[2052] This invention automates the processes of user input, emotion analysis, web information collection, provider selection, and requirement definition document generation, thereby supporting system development that takes user emotions into consideration and optimizing food delivery. Specific embodiments are described below.

[2053] Overall system configuration

[2054] The system includes an emotion engine, a server, and a terminal as its main components.

[2055] Emotion Engine

[2056] The emotion engine receives user input data and analyzes the emotions (excitement, irritation, anxiety, etc.) in the input. The emotion engine uses natural language processing techniques and machine learning algorithms to detect emotions from the user's text.

[2057] server

[2058] The server implements several functions:

[2059] Receives requirements entered by the user and collects necessary web information.

[2060] Analyze the collected web information and create a list of providers that fit your requirements.

[2061] The optimal provider is selected based on the emotional data provided by the emotion engine.

[2062] A requirements definition document is generated based on the user's input data and emotion data.

[2063] Terminal

[2064] The terminal provides an interface for users to input requirements and communicates with the server. The analysis results of the emotion engine are also displayed on the terminal, helping users select providers and review requirements definition documents.

[2065] Data processing and calculations

[2066] The server processes the data in the following steps:

[2067] 1. Receive requirements and emotional data entered by the user and use generative AI to collect the necessary web information.

[2068] 2. Classify and organize the collected web information and create a list of providers.

[2069] 3. Based on the emotion data, the best providers are presented to the user in order of priority.

[2070] 4. Generate the final requirements document and customize the tone and content based on the sentiment data.

[2071] Specific examples

[2072] For example, if a user is on their lunch break and inputs, "I want pasta, but it needs to arrive within 30 minutes," and feels frustrated, the system will prioritize highly rated pasta restaurants that can deliver quickly. The emotion engine detects frustration and provides advice based on that.

[2073] Prompt Sentence Examples

[2074] User entered dish: Pasta

[2075] Budget: 2000 yen

[2076] Delivery time: within 30 minutes

[2077] User Emotion: Annoyance

[2078] In this way, this system can quickly and effectively collect web information and select providers while taking into consideration the user's feelings, thereby improving the user experience.

[2079] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2080] Step 1:

[2081] The user inputs their requirements into the device. For example, during their lunch break, the user might input, "I want to eat pasta, but it needs to arrive within 30 minutes." This input data, along with other requirements such as the type of food, budget, and delivery time, is saved on the device.

[2082] Input: User requirements (type of food, budget, delivery time)

[2083] Output: Input data on the terminal

[2084] Step 2:

[2085] The device sends the input data to the emotion engine, which then analyzes the emotion of the user as they type. For example, if someone types, "I want to eat pasta, but it needs to arrive within 30 minutes," the engine can detect the emotion of irritation.

[2086] Input: User requirements

[2087] Output: User emotion data (irritation)

[2088] Step 3:

[2089] The device sends user requirements and emotion data to the server, which receives it and starts various processes.

[2090] Input: User requirements, user emotion data

[2091] Output: Send data to the server

[2092] Step 4:

[2093] The server collects web information based on the received requirements. To do this, the server uses a generative AI model to search and collect information on the internet using keywords such as "food delivery pasta reviews."

[2094] Input: User requirements

[2095] Output: Collected web information

[2096] Step 5:

[2097] The server analyzes the collected web information, which is then categorized and organized according to user requirements, such as delivery time and ratings.

[2098] Input: Collected web information

[2099] Output: Categorized and organized web information

[2100] Step 6:

[2101] The server selects a provider (restaurant) from the collected web information based on the emotion data. For frustrated users, it prioritizes a list of highly rated providers who can deliver quickly.

[2102] Input: Categorized and organized web information, user emotion data

[2103] Output: List of providers

[2104] Step 7:

[2105] The device receives the list of providers from the server and presents it to the user. At the same time, it displays advice and suggestions based on the emotion data. For example, "Here are restaurants that can deliver in the shortest time."

[2106] Input: Source list, emotion data

[2107] Output: Display a list of providers and advice to the user

[2108] Step 8:

[2109] The user makes a specific selection using the device, for example, selecting "Restaurant A" and "Restaurant B," and then sends the result from the device to the server.

[2110] Input: User selection

[2111] Output: Send selection result data to the server

[2112] Step 9:

[2113] The user inputs specific functional requirements into the device in detail, such as "add a filtering function to the product search function" or "support credit cards and PayPal for payment." The emotion engine analyzes the user's emotions and displays appropriate advice.

[2114] Input: Detailed functional requirements

[2115] Output: Detailed functional requirements input data

[2116] Step 10:

[2117] The device sends detailed functional requirements and emotional data to the server, which then analyzes the detailed requirements and emotional data using a generative AI model to automatically generate an initial requirements definition document.

[2118] Input: Detailed functional requirements, sentiment data

[2119] Output: Initial requirements specification document

[2120] Step 11:

[2121] The initial requirements definition document generated by the server is presented to the user via the terminal, and after a confirmation and revision process, the final requirements definition document is generated. The tone and content are also customized based on the emotional data.

[2122] Input: Initial requirements definition document, user modified requirements

[2123] Output: Final requirements specification document

[2124] In this way, it is possible to quickly and effectively collect web information and select providers while taking into consideration the user's feelings, thereby improving the user experience.

[2125] 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.

[2126] 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.

[2127] 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.

[2128] 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.

[2129] 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.

[2130] 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.

[2131] 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).

[2132] 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.

[2133] 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."

[2134] 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.

[2135] 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).

[2136] 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.

[2137] 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.

[2138] 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.

[2139] 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.

[2140] 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.

[2141] 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.

[2142] 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.

[2143] 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.

[2144] 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 technic...

Claims

1. A means for receiving requirements input by a user and collecting web information based on the requirements; A method for analyzing collected web information and listing providers that fit the requirements, a means for selecting the most suitable source from the list of sources; A means for automatically generating a requirements definition document based on input data from a user; A system including:

2. 2. The system according to claim 1, wherein the generated requirements definition document is presented to a user, and modified requirements are acquired to generate a final document.

3. 2. The system according to claim 1, wherein user requirement input, web information collection, provider selection, and requirement definition document generation are all automated.

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