system

Abstract

A system is provided.SOLUTION: This system includes a means for collecting business transfer information in an interactive form, a means for automatically generating a standardized transfer document on the basis of the collected business transfer information, and a means for quickly answering a question on the basis of the accumulated transfer information and an FAQ database.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The traditional process of handing over work was costly and time-consuming, and information updates were often delayed. Furthermore, the latest information was not shared sufficiently, making it difficult for new members to quickly adapt to the work. This problem reduced the company's work efficiency, leading to interruptions and inefficiencies. [Means for solving the problem]

[0005] The present invention solves the above problems with a system that includes a means for collecting task handover information interactively, a means for automatically generating standardized handover documents based on the collected task handover information, and a means for quickly answering questions based on accumulated handover information and an FAQ database. By using generative artificial intelligence to efficiently and consistently collect task handover information and generate documents, and by storing the collected information and making it accessible to other members, new members can quickly adapt to the tasks and improve the company's work efficiency.

[0006] "Dialogue" refers to a method in which the user directly inputs questions and answers into the system, resulting in two-way communication via generative artificial intelligence.

[0007] "Business handover information" is information necessary for handing over business, including details about the progress of the project, the next tasks to be done, and the tools and processes to be used.

[0008] A "standardized handover document" is a consistent, formatted document that is automatically generated based on collected business handover information.

[0009] "Auto-generation" is the process of using artificial intelligence or algorithms to create documents or answers without human intervention.

[0010] "Accumulated handover information" refers to handover information that has been collected in the past and stored in a database or record.

[0011] An "FAQ database" is a database of frequently asked questions and their answers that can be used to quickly answer questions about specific information or procedures.

[0012] "Generative AI" is an AI system that performs natural language processing and has the ability to generate appropriate answers and documents in response to user input. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] The "smart handover" system of the present invention is designed to streamline the process of job handover and enable new members to quickly adapt to the job. This system consists of the following main components:

[0035] 1. A method for collecting information on business handover in an interactive format

[0036] Provide an interface for users to enter handover information, for example, existing members answering specific questions such as "What is the current status of the project?"

[0037] The server uses generative artificial intelligence to generate and collect appropriate answers to user questions, interacting with the user using natural language processing to obtain important details about the business.

[0038] 2. A method for automatically generating standardized handover documents based on collected business handover information

[0039] The server consolidates the collected handover information and automatically generates handover documents in a standardized format.

[0040] This handover document is structured so that each member can easily understand it, and clearly states important points of the work and the next tasks to be performed.

[0041] 3. A means of quickly answering questions based on accumulated handover information and a FAQ database

[0042] The server searches the accumulated handover information and FAQ database to quickly answer the new member's questions. For example, if a new member asks, "How do I start the system?", the server will refer to the FAQ database and provide an answer.

[0043] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[0044] Specific examples

[0045] For example, if there is a project that requires handover, the system can be used in the following manner.

[0046] 1. User Procedure

[0047] A user (existing member) logs into the system and enters the question "What is the next task?" through the interface.

[0048] 2. Server Processing

[0049] The server uses generative artificial intelligence to check the progress of current projects from a collected database and respond by listing relevant tasks.

[0050] For example, the generated answer might be, "The next task is to review the design and get it approved by the client."

[0051] 3. Generate handover documents

[0052] Using the information collected interactively, the server automatically generates a comprehensive handover document that includes project status, next tasks, tools to be used, and contact information for everyone involved.

[0053] 4. Answering new member questions

[0054] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If it can't find one, it uses generative artificial intelligence to instantly generate a new answer and provide it.

[0055] By operating this system, new members can quickly adapt to the work, improving the company's work efficiency. In this way, the present invention can realize an effective and efficient work handover.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] A user accesses the interface and enters a question to begin collecting handover information, such as "What is the current project status?"

[0059] Step 2:

[0060] The server analyzes the question received from the user and instructs the generative AI to start a dialogue, sending the question content to the generative AI.

[0061] Step 3:

[0062] The server receives the answer received from the generative AI. For example, you can get an answer such as "The current ongoing project is at ~% progress."

[0063] Step 4:

[0064] The server collects these responses and stores them in a database as handover information. The collected information becomes the basis for handover documents.

[0065] Step 5:

[0066] Once the server has collected the answers to all the questions, it automatically generates a standardized handover document based on this information.

[0067] Step 6:

[0068] The server saves the created handover document as a file, and the saved file is set so that other members can access it.

[0069] Step 7:

[0070] The device (the new member's computer or smartphone) accesses the handover document and retrieves the necessary information.

[0071] Step 8:

[0072] A user (new member) inputs a question about the FAQ through the system interface, for example, "How do I start the system?"

[0073] Step 9:

[0074] The server consults the FAQ database to find an existing answer to the question, and if found, provides the answer to the user.

[0075] Step 10:

[0076] If the server does not have a corresponding answer in its FAQ database, it uses generative artificial intelligence to generate a new answer and provides it to the user.

[0077] Step 11:

[0078] Users can check the answers to the provided FAQs and obtain the information they need to do their jobs. This process allows new members to quickly adapt to the job.

[0079] Example 1

[0080] 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."

[0081] The traditional process for handing over work relied on manual information gathering and document creation, making it inefficient and difficult for new members to quickly adapt to the work. Furthermore, the accumulated handover information and FAQ database were not properly utilized, resulting in a disruptive workflow.

[0082] 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.

[0083] In this invention, the server includes a means for allowing a user to interactively collect task handover information through an interface, a means for automatically generating standardized handover documents using a generation AI model based on the collected task handover information, and a means for quickly answering user questions based on the accumulated handover information and FAQ database, thereby enabling efficient task handover and enabling new members to quickly adapt to the tasks.

[0084] A "user" is a person who accesses the system to collect task handover information and input questions.

[0085] An "interface" is a screen or input form that allows a user to interact with a system.

[0086] A "generative AI model" is an artificial intelligence that uses natural language processing technology to generate appropriate answers or documents based on input information.

[0087] A "standardized handover document" is a document created in a unified format based on collected business handover information.

[0088] An "FAQ database" is a database that stores frequently asked questions and their answers.

[0089] The "means for collecting" refers to a function that allows a user to input task handover information through an interface.

[0090] "Means for automatic generation" refers to the ability to create handover documents using a generative AI model based on collected information.

[0091] "Means for quick response" refers to the function of quickly providing answers to users' questions from the accumulated handover information and FAQ database.

[0092] The "smart handover" system of the present invention is designed to streamline the job handover process and allow new members to quickly adapt to the job. This system consists of the following main components:

[0093] 1. A means for users to collect task handover information interactively through an interface

[0094] Users log in to the system and enter task handover information through the interface. For example, an existing member enters a question such as, "What is the next task?"

[0095] The interface is a dashboard accessible through a web browser that allows users to easily enter business questions.

[0096] 2. A method for automatically generating standardized handover documents using a generative AI model based on collected business handover information

[0097] The server uses generative artificial intelligence (generative AI model) to process the collected handover information and automatically generate a handover document in a standardized format, which includes information such as the project's progress, next tasks, tools to be used, and contact information for the members involved.

[0098] As a specific example, a user might ask, "What is the next task?" and the generative AI model might respond, "The next task is to review the design and get it approved by the client," and this information would be reflected in the handover document.

[0099] 3. A means of quickly answering user questions based on accumulated handover information and a FAQ database

[0100] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If no answer is found, it uses a generative AI model to generate a new answer and provides it.

[0101] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[0102] Hardware and software used

[0103] Server: High-performance data processing server

[0104] Generative AI model: An AI model using natural language processing

[0105] User devices: PCs, smartphones, etc.

[0106] Interface: UI accessible through a web browser

[0107] Database: A database that stores business handover information and FAQ information

[0108] Specific examples of operation

[0109] 1. User steps: Log in and type "What's my next task?"

[0110] 2. Server processing: Using the generative AI model, generate an answer, such as "The next task is to review the design and submit it to the client for approval."

[0111] 3. Generate handover documents: Automatically document information collected interactively.

[0112] 4. Answering new member questions: Ask "How do I start the system?" and we'll search our FAQ database to provide an answer, or generate a new answer with our generative AI model.

[0113] In this way, the present invention realizes an efficient work handover, allowing new members to quickly adapt to the work.

[0114] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0115] Step 1: User Login

[0116] The user accesses the interface.

[0117] The user opens a web browser and accesses the URL of the "Smart Handover" system.

[0118] Input: Login URL

[0119] Output: Login screen displayed

[0120] The user enters their login information and logs into the system.

[0121] The user enters their username and password and clicks the "Login" button.

[0122] Input: Username, Password

[0123] Data processing: The server authenticates the entered information

[0124] Output: Authentication result (success or failure), displayed on the main dashboard if successful

[0125] Step 2: Enter and submit your question

[0126] The user types the question in the interface: "What is my next task?"

[0127] A user clicks the "Ask a Question" button from the main dashboard and types "What's my next task?" into the question input field.

[0128] Input: Question (What is the next task?)

[0129] Output: Destination (server) of the query

[0130] The user clicks the "Submit" button.

[0131] Click the "Submit" button to submit the entered question.

[0132] Input: Click on submit button

[0133] Output: Sends the question to the server

[0134] Step 3: Question processing and answer generation

[0135] The server receives a query from a user.

[0136] The server receives the question sent by the user and analyzes its contents.

[0137] Input: User's question

[0138] Data processing: Analysis of questions

[0139] Output: Analysis result (prompt statement)

[0140] The server sends a prompt to the generative AI model.

[0141] The server sends a prompt to the generative AI model: "What is the next task?"

[0142] Input: Analysis result (prompt statement)

[0143] Output: Input to the generative AI model

[0144] A generative AI model generates answers to questions.

[0145] A generative AI model generates an answer based on the prompt.

[0146] Input: prompt statement

[0147] Data Computing: Answer Generation Using Natural Language Processing

[0148] Output: Answer (The next task is to check the design and give it to the client for approval)

[0149] The server receives the generated answer and sends it to the user.

[0150] The answer received from the generative AI model is sent to the user.

[0151] Input: Generated answer

[0152] Output: Response sent to user

[0153] Step 4: Automatic generation of handover documents

[0154] The server organizes the collected dialogue information and generates standardized handover documents.

[0155] Handover documents are automatically generated in a standardized format based on information collected interactively.

[0156] Input: Information collected interactively

[0157] Data processing: organizing information and converting it into a format

[0158] Output: Handover document (project status, next tasks, tools used, contact information of involved people)

[0159] The server stores the generated handover document in a database.

[0160] Store handover documents in a database and make them accessible as needed.

[0161] Input: Handover document

[0162] Output: Save to database

[0163] Step 5: Answer new member questions

[0164] A new member asks from a terminal, "How do I start the system?"

[0165] New members type in their questions on their devices and submit them.

[0166] Input: Question (How do I start the system?)

[0167] Output: Sends the question to the server

[0168] The server searches the FAQ database and extracts existing answers.

[0169] Search our FAQ database to see if your question is answered.

[0170] Input: User's question

[0171] Data Calculation: Search the FAQ database

[0172] Output: Search results (existing answers)

[0173] The server creates a response and sends it to the new member's device.

[0174] It creates an answer based on the search results and sends it to the device, and if an answer is not found, it uses a generative AI model to generate a new answer.

[0175] Input: Search results or Fee burden

[0176] Output: Send the response to the new member

[0177] Through this series of processes, the "smart handover" system realizes efficient job handover and allows new members to quickly adapt to the job.

[0178] (Application example 1)

[0179] 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."

[0180] Traditionally, work handovers have mainly been conducted through face-to-face explanations or information sharing via email, which has resulted in insufficient handover information, making it difficult for new workers to quickly adapt to the work. Furthermore, in the work processes within the factory, if the handover is not carried out properly, problems such as reduced work efficiency can arise. Furthermore, when new workers have questions, they often cannot receive prompt and accurate answers, which often leads to work delays.

[0181] 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.

[0182] In this invention, the server includes means for collecting task handover information interactively, means for automatically generating standardized handover documents based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for converting voice input into text and means for analyzing the handover information using generative artificial intelligence, means for saving the generated handover documents and making them accessible to other members, and means for supporting work processes within the factory. This improves the efficiency of the task handover process, allowing new workers to quickly adapt to the work. Furthermore, efficient and accurate handovers of work processes within the factory are possible, improving work efficiency. Furthermore, when new workers have questions, they can receive prompt and accurate answers, preventing work delays.

[0183] The "means for collecting task handover information in an interactive manner" is a means for providing an interface for collecting task handover information through a dialogue with a user, and for organizing the information in an interactive manner.

[0184] "Means for automatically generating standardized handover documents based on collected business handover information" refers to means for analyzing collected handover information and automatically creating documents in a unified format.

[0185] "Means for quickly answering questions based on accumulated handover information and FAQ database" refers to a means for searching pre-accumulated handover information and FAQ database to quickly provide appropriate answers to questions from users.

[0186] The "means for converting speech input into text" refers to a means for converting information input by speech by a user into text data using natural language processing technology.

[0187] "Means for analyzing handover information using generative artificial intelligence" refers to means for analyzing handover information collected using generative artificial intelligence and extracting necessary information.

[0188] "Means for storing the generated handover documents and making them accessible to other members" means means for storing the automatically generated handover documents in a database so that other members can access, view, and use them at any time.

[0189] "Means to support work processes within the factory" refers to means for monitoring the progress of work within the factory in real time and improving work efficiency by providing appropriate information and work instructions.

[0190] This invention is a system for streamlining task handover in manufacturing sites, which collects task handover information interactively, automatically generates standardized handover documents, and provides quick answers to questions based on accumulated information and an FAQ database. It also includes a function to support work processes within the factory.

[0191] Hardware and software used

[0192] 1. Hardware:

[0193] Work robots: assist with work and collect information within the factory.

[0194] Voice input device: Collects voice information from workers.

[0195] Network connection: Data communication between the server, robot, and terminal.

[0196] 2. Software:

[0197] Python 3.8 or higher: Use as the primary programming language.

[0198] OpenAI GPT-3 model: Used to collect and analyze job handover information, generate handover documents, and answer questions.

[0199] Google Speech-to-Text: Converts voice input into text.

[0200] Process Overview

[0201] 1. Collect handover information:

[0202] The server works in conjunction with a device that converts voice input into text, converting the voice input from the worker into text data. The converted text data is analyzed by generative artificial intelligence (GPT-3) and collected as handover information.

[0203] 2. Generate handover documents:

[0204] The server automatically generates a unified handover document based on the collected handover information, which includes information such as the project status, next steps, tools to be used, and contact information for the people involved.

[0205] 3. Question answering function:

[0206] When a new worker asks a question, the server references the accumulated handover information and FAQ database to provide a quick answer. For questions not in the FAQ database, the server uses the GPT-3 model to generate an appropriate answer and add it to the database.

[0207] 4. Factory support:

[0208] The server monitors and supports the work process in the factory in real time based on the collected handover information, providing the necessary information for specific work steps and improving work efficiency.

[0209] Specific example demo

[0210] For example, imagine a situation where a project is underway in a factory and the next task needs to be handed over. The existing worker asks the robot, "What is the next task?" The voice input through the voice input device is converted into text via Google Speech-to-Text. The server uses generative artificial intelligence to answer this question, saying, "The next task is to check the quality of the parts and perform the assembly process."

[0211] In another scenario, consider a new worker asking, "How do I start the system?" The server searches the FAQ database to find and provide the appropriate answer. If the answer is not in the FAQ database, the server uses the GPT-3 model to generate an answer: "To start the system, power it on, log in, and select the start-up option from the main menu," which is immediately provided to the new worker.

[0212] Example prompt sentence:

[0213] Please tell me the current progress of the project.

[0214] "What's the next task?"

[0215] "How do I start the system?"

[0216] In this way, using this system makes the handover of work more efficient and enables new workers to quickly adapt to the work.

[0217] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0218] Step 1:

[0219] The user (existing worker) inputs handover information to the robot by voice. A voice input device is used for voice input. The input voice data is converted into text data using voice recognition technology (Google Speech-to-Text). This converts the voice data into text format, making it easier to handle in subsequent processes.

[0220] Input: Voice data (questions and information)

[0221] Output: Text data (questions and information)

[0222] Step 2:

[0223] The server sends the text data to a generative artificial intelligence (GPT-3 model) for analysis. The necessary handover information is extracted from the analyzed data. Here, the text data is parsed into a specific format and organized as handover information.

[0224] Input: Text data

[0225] Output: Parsed handover information

[0226] Step 3:

[0227] The server automatically generates standardized handover documents based on the analyzed handover information. Generative AI is used to create documents in a unified format. These documents include project progress, next steps, tools to be used, and contact information for the people involved.

[0228] Input: Parsed handover information

[0229] Output: Standardized handover documents

[0230] Step 4:

[0231] The server saves the generated handover document in a database so that other members can access it. The saved handover document can be accessed by a new worker whenever necessary. This makes it easy to share information between workers.

[0232] Input: Standardized handover documents

[0233] Output: Handover document stored in database

[0234] Step 5:

[0235] When a new worker asks a question, the terminal (robot or computer) sends the question to the server. The server searches the accumulated handover information and FAQ database to provide an appropriate answer. If the FAQ database does not contain a corresponding answer, a new answer is generated using generative artificial intelligence and added to the database.

[0236] Input: New worker question

[0237] Output: The appropriate answer from the server

[0238] Step 6:

[0239] The terminal receives the answer provided by the server and presents it to the new worker. This allows the worker's questions to be resolved quickly and prevents work delays. The answer is displayed in text format or played back aloud.

[0240] Input: Response from the server

[0241] Output: Presents the answer to the new worker

[0242] The above processing steps improve the efficiency of work handover within the factory and create an environment in which new workers can quickly adapt to their work.

[0243] 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.

[0244] The "smart handover" system of the present invention is designed to streamline the task handover process and allow new members to quickly adapt to the task. The present invention can be combined with an emotion engine that recognizes the user's emotions to further improve the user experience. The system consists of the following main components:

[0245] 1. A method for collecting information on business handover in an interactive format

[0246] Provide an interface for users to enter handover information, for example, existing members answering specific questions such as "What is the current status of the project?"

[0247] The server uses generative artificial intelligence to generate and collect appropriate answers to user questions, interacting with the user using natural language processing to obtain important details about the business.

[0248] 2. A method for automatically generating standardized handover documents based on collected business handover information

[0249] The server consolidates the collected handover information and automatically generates handover documents in a standardized format.

[0250] This handover document is structured so that each member can easily understand it, and clearly states important points of the work and the next tasks to be performed.

[0251] 3. A means of quickly answering questions based on accumulated handover information and a FAQ database

[0252] The server searches the accumulated handover information and FAQ database to quickly answer the new member's questions. For example, if a new member asks, "How do I start the system?", the server will refer to the FAQ database and provide an answer.

[0253] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[0254] 4. Emotion engine that recognizes user emotions

[0255] The terminal collects the user's emotional data (e.g., facial expressions and voice tone) through the interface.

[0256] The server uses an emotion engine to analyze the collected emotion data and recognize the user's emotional state, which is then used to adjust the tone of the interaction and provide appropriate responses.

[0257] Based on the analysis results of the emotion engine, the server or terminal will take adaptive measures, such as displaying a message encouraging relaxation if the user is feeling stressed.

[0258] Specific examples

[0259] For example, if there is a project that requires handover, the system can be used in the following manner.

[0260] 1. User Input

[0261] A user (existing member) logs in to the system and enters a question through the interface, such as, "What is the next task I should do?" At this time, the emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[0262] 2. Server Processing

[0263] The server uses generative artificial intelligence to check the current project progress from a collected database and respond with a list of related tasks, such as, "The next task is to review the design and get it approved by the client."

[0264] The emotion engine analyzes the user's emotional state and generates responses with appropriate tone and wording.

[0265] 3. Creating and saving handover documents

[0266] The server uses the information collected interactively to automatically generate a comprehensive handover document that includes project status, next tasks, tools to be used, and contact information for everyone involved.

[0267] Save the generated handover document as a file and set it up so that other members can access it.

[0268] 4. Answering questions from new members

[0269] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If no answer is found, it uses generative artificial intelligence to generate a new answer and provides it.

[0270] 5. Emotion Recognition and Adaptive Responses

[0271] The device will recognize the emotions of the new member from their facial expressions and voice, and if they are feeling stressed, for example, it will display a message saying, "Please relax and continue working."

[0272] By operating this system, new members can quickly adapt to the work, improving the company's work efficiency, and the system also provides a better user experience by enabling adaptive responses based on the user's emotions. In this way, the present invention can achieve effective and efficient work handover.

[0273] The processing flow will be explained below.

[0274] Step 1:

[0275] A user accesses the interface and enters a question to begin collecting handover information, such as "What is the current project status?"

[0276] Step 2:

[0277] The device captures the user's input and sends the collected questions along with the user's facial expressions and tone of voice to the emotion engine.

[0278] Step 3:

[0279] The emotion engine analyzes the user's emotion data and recognizes their emotional state, such as whether they are tense or relaxed.

[0280] Step 4:

[0281] The server sends the question received from the user to the generative AI and instructs it to start a dialogue. At that time, the server also sends the analysis results of the emotion engine along with the question content to the generative AI.

[0282] Step 5:

[0283] The server receives the answer from the generative AI. This answer is provided in an appropriate tone depending on the emotional situation. For example, you might get an answer like "The current ongoing project is at ~% progress."

[0284] Step 6:

[0285] The server collects these responses and stores them in a database as handover information. The collected information becomes the basis for handover documents.

[0286] Step 7:

[0287] Once the server has collected the answers to all the questions, it automatically generates a standardized handover document based on this information.

[0288] Step 8:

[0289] The server saves the created handover document as a file, and the saved file is set so that other members can access it.

[0290] Step 9:

[0291] The device (the new member's computer or smartphone) accesses the handover document and retrieves the necessary information.

[0292] Step 10:

[0293] A user (new member) inputs a question about the FAQ through the system interface, for example, "How do I start the system?"

[0294] Step 11:

[0295] The device sends the user's facial expressions and tone of voice to the emotion engine.

[0296] Step 12:

[0297] The emotion engine analyzes the user's emotion data and recognizes their current emotional state.

[0298] Step 13:

[0299] The server consults the FAQ database to find an existing answer to the question. If found, it provides the answer to the user. The answer is adjusted based on the analysis results from the emotion engine.

[0300] Step 14:

[0301] If the server does not have a corresponding answer in its FAQ database, it uses generative artificial intelligence to generate a new answer and provides it in a tone that corresponds to the analyzed emotional state.

[0302] Step 15:

[0303] Users can check the answers to the provided FAQs to obtain the information they need for their work. Also, if the user is feeling stressed, for example, the system will display a message encouraging relaxation.

[0304] In this way, the present invention not only efficiently collects task handover information and automatically generates standardized handover documents, but also improves the user experience by adaptively responding to the user's emotional state.

[0305] Example 2

[0306] 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."

[0307] The process of business handover presents a challenge for new members, making it difficult for them to quickly adapt to the new work. Furthermore, traditional handover processes often result in poor user experience and a lack of emotional support, which can lead to stress for new members and reduced work efficiency.

[0308] 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.

[0309] In this invention, the server includes means for collecting task handover information in an interactive manner, means for automatically generating a standardized handover document based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for collecting emotion data, and means for analyzing the emotion data and responding adaptively based on the user's emotional state. This not only enables new members to quickly adapt to the task and improves work efficiency, but also enables adaptive responses according to the user's emotions, making it possible to provide a better user experience.

[0310] The "means for collecting task handover information interactively" is a function that allows the user to input questions and answers through an interface and collect the necessary task handover information based on them.

[0311] "Means for automatically generating standardized handover documents based on collected business handover information" refers to a function in which the system organizes collected handover information and automatically creates documents related to business handover according to a specific format.

[0312] "Means for quickly answering questions based on accumulated handover information and FAQ database" refers to a function in which the system searches the handover information and FAQ database that have already been saved and provides immediate answers to questions from users.

[0313] "Means for collecting emotional data" means the ability to capture emotion-related data, such as a user's facial expressions or vocal tone, and enable the system to analyze that data.

[0314] "Means for analyzing emotional data and responding adaptively based on the user's emotional state" refers to a function that analyzes collected emotional data, determines the user's current emotional state, and generates appropriate dialogue and messages accordingly.

[0315] The "smart handover" system of the present invention is designed to streamline task handover and enable new members to adapt to the task in a short period of time. In particular, by incorporating an emotion engine that recognizes the user's emotions, the user experience can be improved. The system includes the following main components:

[0316] A means of collecting information on business handover in an interactive format

[0317] The user inputs task handover information using a dedicated interface. This is done using generative AI (e.g., OpenAI GPT-3) that utilizes natural language processing technology. For example, if the user inputs a question such as "What task should I do next?", the generative AI generates an appropriate answer. At this time, the device also collects emotional data such as the user's facial expressions and tone of voice.

[0318] A method for automatically generating standardized handover documents based on collected business handover information

[0319] The server analyzes the collected handover information and automatically generates handover documents in a standardized format. These documents include the project's progress, next tasks, tools to be used, and contact information for the members involved. The generated documents are saved in cloud storage (e.g., Google Drive or Dropbox) so users can access them at any time.

[0320] A means of quickly answering questions based on accumulated handover information and a FAQ database

[0321] When a new member types a question into the system (e.g., "How do I start the system?"), the server searches the accumulated FAQ database and provides an immediate answer. If necessary, new answers can be generated using generative artificial intelligence.

[0322] Means of collecting emotion data

[0323] The device collects the user's facial expressions and voice tone using a webcam and microphone.

[0324] A means of analyzing emotional data and adaptively responding based on the user's emotional state

[0325] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the collected emotion data. Based on the analysis results, the server or device responds adaptively. For example, if the user is feeling stressed, a message saying "Relax and continue working" is displayed.

[0326] Specific examples

[0327] For example, if there is a project that requires a handover, the system could be used in the following way. First, the user enters a question into the interface: "What is the next task?" The device collects facial expressions and voice tone. The server uses generative artificial intelligence to generate an answer to the question, replying, "The next task is to check the design and get it approved by the client." The emotion engine then analyzes the user's emotional state and adjusts the answer to an appropriate tone. The generated handover document is saved in cloud storage and set up so that other members can easily access it.

[0328] Prompt Sentence Examples

[0329] "What's the next task?"

[0330] Please tell me the progress of your current project.

[0331] "How do I start the system?"

[0332] By operating this system, new members can quickly adapt to the work, improving work efficiency, and it also enables adaptive responses based on user emotions, providing a better user experience, making the work handover process more effective and efficient.

[0333] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0334] Step 1:

[0335] A user logs in to the system.

[0336] Input: User ID and password

[0337] Action: User authentication occurs.

[0338] Output: Authentication successful message is displayed.

[0339] Step 2:

[0340] The user inputs questions about the business handover through the interface.

[0341] Input: Questions like "What's the next task?"

[0342] Action: The question text is sent to the server.

[0343] Output: The question is saved on the server.

[0344] Step 3:

[0345] The device collects the user's emotional data (facial expressions and vocal tone).

[0346] Input: Face image via webcam and voice via microphone

[0347] How it works: Emotion data is captured and sent to a server.

[0348] Output: Emotion data is stored on the server.

[0349] Step 4:

[0350] The server uses generative artificial intelligence (e.g., OpenAI GPT-3) to analyze the entered question and generate an appropriate answer.

[0351] Input: User question text

[0352] Data processing: Perform natural language processing of questions and database searches.

[0353] Output: Answer text: "The next task is to review the design and get it approved by the client."

[0354] Step 5:

[0355] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the collected emotion data.

[0356] Input: User emotion data

[0357] Data Computation: Performs sentiment analysis to determine the user's emotional state.

[0358] Output: The user's emotional state (e.g., feeling stressed) is determined.

[0359] Step 6:

[0360] The server responds adaptively based on the emotional state.

[0361] Input: User's emotional state and answer text

[0362] Data processing: Adjust the tone of the response text.

[0363] Output: Adjusted answer text: "Your next task is to review the design and get it approved by the client. Relax and get going."

[0364] Step 7:

[0365] The terminal displays the adjusted answer text to the user.

[0366] Input: Adjusted answer text

[0367] Behavior: Displays the answer text on the screen.

[0368] Output: The user can check the answer.

[0369] Step 8:

[0370] The server automatically generates standardized handover documents based on the information collected interactively.

[0371] Input: Collected business handover information

[0372] Data processing: Organizing information and generating documents in a specific format.

[0373] Output: Handover documents are generated (e.g., project status, next steps, tools used, contact information for involved people, etc.).

[0374] Step 9:

[0375] The server stores the handover document in cloud storage.

[0376] Input: Generated handover document

[0377] Action: Save file to cloud storage (e.g. Google Drive, Dropbox)

[0378] Output: The handover document is saved to cloud storage and a sharing link is generated.

[0379] Step 10:

[0380] A user (new member) enters a question into the system.

[0381] Input: Questions like "How do I boot my system?"

[0382] Action: The question text is sent to the server.

[0383] Output: The question is saved on the server.

[0384] Step 11:

[0385] The server searches a stored FAQ database and provides existing answers to the question.

[0386] Input: Question text

[0387] Data processing: Searching the FAQ database and extracting matching answers

[0388] Output: Answer text: "To start the system, first press the power button, then enter your ID and password on the login screen."

[0389] Step 12:

[0390] If the server cannot find an appropriate answer, it uses generative artificial intelligence to generate a new answer.

[0391] Input: Question text

[0392] Data processing: Answer generation using generative artificial intelligence

[0393] Output: New answer text (e.g., "To start your system, first press the power button, then enter your ID and password on the login screen.")

[0394] Step 13:

[0395] The device sends the new member's facial expressions and voice to the emotion engine for analysis.

[0396] Input: User emotion data

[0397] Data processing: Emotion data analysis

[0398] Output: User's emotional state

[0399] Step 14:

[0400] The server generates an adaptive message based on the analysis results.

[0401] Input: User's emotional state

[0402] Data processing: Message generation according to emotional state

[0403] Output: "Just relax and get working."

[0404] Step 15:

[0405] The terminal displays the generated message on the screen.

[0406] Input: Message text

[0407] Behavior: Displays a message on the screen.

[0408] Output: The user is helped to acknowledge the message and relax.

[0409] (Application example 2)

[0410] 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."

[0411] Conventional work handover processes have the challenge of making it difficult for new members to quickly adapt to the work. Managing robots in factories, in particular, requires efficient communication of information due to the many detailed operating procedures and precautions required. Furthermore, communication of information can be unclear or emotional stress can arise, leading to reduced productivity and mistakes. To address these issues, a system is needed that allows new members to quickly and effectively adapt to the work environment.

[0412] The specific processing by the specific 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 collecting task handover information in an interactive format, means for automatically generating a standardized handover document based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for analyzing the user's emotional state using an emotion engine, and means for providing an interface operated by the industrial machinery manager. This enables new members to quickly adapt to the work environment and reduces emotional stress.

[0413] The "interactive format" is a format in which the user and the system collect information by exchanging questions and answers.

[0414] "Business handover information" refers to information including the progress of a specific business, the next task to be performed, the tools to be used, and contact information of the members involved.

[0415] A "standardized handover document" is a document that is automatically generated in a consistent and easy-to-understand format based on collected business handover information.

[0416] An "FAQ database" is a database that stores frequently asked questions and their answers.

[0417] An "emotion engine" is software or a system that analyzes emotional data such as a user's facial expressions and tone of voice to recognize the user's emotional state.

[0418] "Industrial machinery" refers to devices such as automated machinery and robots that are primarily used in industrial environments such as factories.

[0419] The "interface operated by the administrator" refers to a graphical user interface (GUI) or command line interface (CLI) intended for use by an administrator of industrial machinery.

[0420] "Generative AI" is an AI technology that automatically generates appropriate answers to questions posed by users in natural language.

[0421] The "smart factory robot handover support system" of this invention is a system that streamlines the handover process for robots working in a factory and allows new members to quickly adapt to the work. The invention is composed of the following main components:

[0422] 1. Gathering information on business handover in an interactive format

[0423] The user (factory manager) inputs handover information through an interactive interface. For example, the factory manager may input a question such as, "How do I maintain a robot?" At this time, the generative AI automatically generates an appropriate answer to the user's question.

[0424] 2. Automatic generation of standardized handover documents based on collected information

[0425] The server processes the collected task handover information in a batch and automatically generates a handover document in a standardized format, which includes the work content, procedures, and important points.

[0426] 3. Quick answers based on accumulated information and FAQ database

[0427] The server refers to the accumulated handover information and FAQ database to quickly provide answers to questions from new members. For example, if a new member asks, "How do I start the system?", the server refers to the FAQ database and provides an answer based on that.

[0428] 4. Use of Emotion Engine

[0429] The terminal collects emotional data (facial expressions and voice tone) through the administrator's interface. The server analyzes this emotional data using an emotion engine to understand the user's emotional state. For example, if the user is feeling stressed, the system displays a message encouraging relaxation. In this way, adaptive responses are made according to the user's emotional state.

[0430] Specific examples

[0431] For example, the following is the flow when a factory manager asks, "How do I maintain a robot?"

[0432] 1. User Input

[0433] A factory manager logs into the interface and types a question such as, "How do I maintain the robot?" At this time, the emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[0434] 2. Server Processing

[0435] The server uses generative artificial intelligence to search the database for relevant handover information and generate an appropriate answer, such as, "The robot's scheduled maintenance is performed every Monday. This includes checking the battery, calibrating the sensors, and updating the navigation system."

[0436] The emotion engine also analyzes the user's emotional state and provides responses in an appropriate tone and language. If the user is feeling stressed, the message displayed will be, "Please relax. We will respond appropriately."

[0437] 3. Automatic generation and storage of handover documents

[0438] Based on the information collected interactively, the server automatically generates comprehensive handover documents, including robot maintenance methods, work procedures, and important points, and stores them in a format that can be accessed by other team members.

[0439] An example of a prompt is as follows:

[0440] Q: How do I maintain my robot?

[0441] Answer: Routine maintenance of the robot is performed every Monday, which includes checking the battery, calibrating the sensors, and updating the navigation system.

[0442] The above system allows new members to quickly adapt to the work environment and reduces emotional stress, enabling them to work more efficiently.

[0443] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0444] Step 1:

[0445] The user (factory manager) logs into the interface and enters interactive questions.

[0446] Input: The user types a question: "How do I maintain my robot?"

[0447] Data processing: The emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[0448] Output: The user's question and emotion data are sent to the system.

[0449] Step 2:

[0450] The server uses generative artificial intelligence to generate answers to questions.

[0451] Input: User questions, collected emotional data, and stored handover information.

[0452] Data Computing: Generative AI uses natural language processing to search for relevant information in a database and generate appropriate answers.

[0453] Output: The server generates an answer and sends it to the user.

[0454] Step 3:

[0455] An emotion engine analyzes the user's emotional state and provides adaptive answers.

[0456] Input: Server-generated answers and user emotional state data.

[0457] Data Calculation: The emotion engine analyzes the user's emotional state and adjusts the tone and content of the response.

[0458] Output: For example, if the user is feeling stressed, an additional message will be displayed: "Relax. We will respond appropriately."

[0459] Step 4:

[0460] Based on the information collected by the server, standardized handover documents are automatically generated.

[0461] Input: Business handover information collected interactively.

[0462] Data processing: The server organizes the collected information in a standardized format and automatically generates consistent handover documents.

[0463] Output: The generated handover document is saved as a file and set up so that other members can access it.

[0464] Step 5:

[0465] Providing quick answers to new members' questions.

[0466] Input: New member's question (e.g., "How do I start the system?").

[0467] Data processing: The server searches the FAQ database and provides an existing answer. If no answer is found, a new answer is generated using generative artificial intelligence.

[0468] Output: Provide an immediate answer to new members.

[0469] The specific actions of each step enable factory managers and new members to carry out their work more efficiently, improving the productivity of the entire system.

[0470] 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.

[0471] 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.

[0472] 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.

[0473] [Second embodiment]

[0474] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0475] 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.

[0476] 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).

[0477] 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.

[0478] 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.

[0479] 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).

[0480] 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.

[0481] 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.

[0482] 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.

[0483] 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.

[0484] 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.

[0485] 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."

[0486] The "smart handover" system of the present invention is designed to streamline the process of job handover and enable new members to quickly adapt to the job. This system consists of the following main components:

[0487] 1. A method for collecting information on business handover in an interactive format

[0488] Provide an interface for users to enter handover information, for example, existing members answering specific questions such as "What is the current status of the project?"

[0489] The server uses generative artificial intelligence to generate and collect appropriate answers to user questions, interacting with the user using natural language processing to obtain important details about the business.

[0490] 2. A method for automatically generating standardized handover documents based on collected business handover information

[0491] The server consolidates the collected handover information and automatically generates handover documents in a standardized format.

[0492] This handover document is structured so that each member can easily understand it, and clearly states important points of the work and the next tasks to be performed.

[0493] 3. A means of quickly answering questions based on accumulated handover information and a FAQ database

[0494] The server searches the accumulated handover information and FAQ database to quickly answer the new member's questions. For example, if a new member asks, "How do I start the system?", the server will refer to the FAQ database and provide an answer.

[0495] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[0496] Specific examples

[0497] For example, if there is a project that requires handover, the system can be used in the following manner.

[0498] 1. User Procedure

[0499] A user (existing member) logs into the system and enters the question "What is the next task?" through the interface.

[0500] 2. Server Processing

[0501] The server uses generative artificial intelligence to check the progress of current projects from a collected database and respond by listing relevant tasks.

[0502] For example, the generated answer might be, "The next task is to review the design and get it approved by the client."

[0503] 3. Generate handover documents

[0504] Using the information collected interactively, the server automatically generates a comprehensive handover document that includes project status, next tasks, tools to be used, and contact information for everyone involved.

[0505] 4. Answering new member questions

[0506] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If it can't find one, it uses generative artificial intelligence to instantly generate a new answer and provide it.

[0507] By operating this system, new members can quickly adapt to the work, improving the company's work efficiency. In this way, the present invention can realize an effective and efficient work handover.

[0508] The processing flow will be explained below.

[0509] Step 1:

[0510] A user accesses the interface and enters a question to begin collecting handover information, such as "What is the current project status?"

[0511] Step 2:

[0512] The server analyzes the question received from the user and instructs the generative AI to start a dialogue, sending the question content to the generative AI.

[0513] Step 3:

[0514] The server receives the answer received from the generative AI. For example, you can get an answer such as "The current ongoing project is at ~% progress."

[0515] Step 4:

[0516] The server collects these responses and stores them in a database as handover information. The collected information becomes the basis for handover documents.

[0517] Step 5:

[0518] Once the server has collected the answers to all the questions, it automatically generates a standardized handover document based on this information.

[0519] Step 6:

[0520] The server saves the created handover document as a file, and the saved file is set so that other members can access it.

[0521] Step 7:

[0522] The device (the new member's computer or smartphone) accesses the handover document and retrieves the necessary information.

[0523] Step 8:

[0524] A user (new member) inputs a question about the FAQ through the system interface, for example, "How do I start the system?"

[0525] Step 9:

[0526] The server consults the FAQ database to find an existing answer to the question, and if found, provides the answer to the user.

[0527] Step 10:

[0528] If the server does not have a corresponding answer in its FAQ database, it uses generative artificial intelligence to generate a new answer and provides it to the user.

[0529] Step 11:

[0530] Users can check the answers to the provided FAQs and obtain the information they need to do their jobs. This process allows new members to quickly adapt to the job.

[0531] Example 1

[0532] 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."

[0533] The traditional process for handing over work relied on manual information gathering and document creation, making it inefficient and difficult for new members to quickly adapt to the work. Furthermore, the accumulated handover information and FAQ database were not properly utilized, resulting in a disruptive workflow.

[0534] 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.

[0535] In this invention, the server includes a means for allowing a user to interactively collect task handover information through an interface, a means for automatically generating standardized handover documents using a generation AI model based on the collected task handover information, and a means for quickly answering user questions based on the accumulated handover information and FAQ database, thereby enabling efficient task handover and enabling new members to quickly adapt to the tasks.

[0536] A "user" is a person who accesses the system to collect task handover information and input questions.

[0537] An "interface" is a screen or input form that allows a user to interact with a system.

[0538] A "generative AI model" is an artificial intelligence that uses natural language processing technology to generate appropriate answers or documents based on input information.

[0539] A "standardized handover document" is a document created in a unified format based on collected business handover information.

[0540] An "FAQ database" is a database that stores frequently asked questions and their answers.

[0541] The "means for collecting" refers to a function that allows a user to input task handover information through an interface.

[0542] "Means for automatic generation" refers to the ability to create handover documents using a generative AI model based on collected information.

[0543] "Means for quick response" refers to the function of quickly providing answers to users' questions from the accumulated handover information and FAQ database.

[0544] The "smart handover" system of the present invention is designed to streamline the job handover process and allow new members to quickly adapt to the job. This system consists of the following main components:

[0545] 1. A means for users to collect task handover information interactively through an interface

[0546] Users log in to the system and enter task handover information through the interface. For example, an existing member enters a question such as, "What is the next task?"

[0547] The interface is a dashboard accessible through a web browser that allows users to easily enter business questions.

[0548] 2. A method for automatically generating standardized handover documents using a generative AI model based on collected business handover information

[0549] The server uses generative artificial intelligence (generative AI model) to process the collected handover information and automatically generate a handover document in a standardized format, which includes information such as the project's progress, next tasks, tools to be used, and contact information for the members involved.

[0550] As a specific example, a user might ask, "What is the next task?" and the generative AI model might respond, "The next task is to review the design and get it approved by the client," and this information would be reflected in the handover document.

[0551] 3. A means of quickly answering user questions based on accumulated handover information and a FAQ database

[0552] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If no answer is found, it uses a generative AI model to generate a new answer and provides it.

[0553] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[0554] Hardware and software used

[0555] Server: High-performance data processing server

[0556] Generative AI model: An AI model using natural language processing

[0557] User devices: PCs, smartphones, etc.

[0558] Interface: UI accessible through a web browser

[0559] Database: A database that stores business handover information and FAQ information

[0560] Specific examples of operation

[0561] 1. User steps: Log in and type "What's my next task?"

[0562] 2. Server processing: Using the generative AI model, generate an answer, such as "The next task is to review the design and submit it to the client for approval."

[0563] 3. Generate handover documents: Automatically document information collected interactively.

[0564] 4. Answering new member questions: Ask "How do I start the system?" and we'll search our FAQ database to provide an answer, or generate a new answer with our generative AI model.

[0565] In this way, the present invention realizes an efficient work handover, allowing new members to quickly adapt to the work.

[0566] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0567] Step 1: User Login

[0568] The user accesses the interface.

[0569] The user opens a web browser and accesses the URL of the "Smart Handover" system.

[0570] Input: Login URL

[0571] Output: Login screen displayed

[0572] The user enters their login information and logs into the system.

[0573] The user enters their username and password and clicks the "Login" button.

[0574] Input: Username, Password

[0575] Data processing: The server authenticates the entered information

[0576] Output: Authentication result (success or failure), displayed on the main dashboard if successful

[0577] Step 2: Enter and submit your question

[0578] The user types the question in the interface: "What is my next task?"

[0579] A user clicks the "Ask a Question" button from the main dashboard and types "What's my next task?" into the question input field.

[0580] Input: Question (What is the next task?)

[0581] Output: Destination (server) of the query

[0582] The user clicks the "Submit" button.

[0583] Click the "Submit" button to submit the entered question.

[0584] Input: Click on submit button

[0585] Output: Sends the question to the server

[0586] Step 3: Question processing and answer generation

[0587] The server receives a query from a user.

[0588] The server receives the question sent by the user and analyzes its contents.

[0589] Input: User's question

[0590] Data processing: Analysis of questions

[0591] Output: Analysis result (prompt statement)

[0592] The server sends a prompt to the generative AI model.

[0593] The server sends a prompt to the generative AI model: "What is the next task?"

[0594] Input: Analysis result (prompt statement)

[0595] Output: Input to the generative AI model

[0596] A generative AI model generates answers to questions.

[0597] A generative AI model generates an answer based on the prompt.

[0598] Input: prompt statement

[0599] Data Computing: Answer Generation Using Natural Language Processing

[0600] Output: Answer (The next task is to check the design and give it to the client for approval)

[0601] The server receives the generated answer and sends it to the user.

[0602] The answer received from the generative AI model is sent to the user.

[0603] Input: Generated answer

[0604] Output: Response sent to user

[0605] Step 4: Automatic generation of handover documents

[0606] The server organizes the collected dialogue information and generates standardized handover documents.

[0607] Handover documents are automatically generated in a standardized format based on information collected interactively.

[0608] Input: Information collected interactively

[0609] Data processing: organizing information and converting it into a format

[0610] Output: Handover document (project status, next tasks, tools used, contact information of involved people)

[0611] The server stores the generated handover document in a database.

[0612] Store handover documents in a database and make them accessible as needed.

[0613] Input: Handover document

[0614] Output: Save to database

[0615] Step 5: Answer new member questions

[0616] A new member asks from a terminal, "How do I start the system?"

[0617] New members type in their questions on their devices and submit them.

[0618] Input: Question (How do I start the system?)

[0619] Output: Sends the question to the server

[0620] The server searches the FAQ database and extracts existing answers.

[0621] Search our FAQ database to see if your question is answered.

[0622] Input: User's question

[0623] Data Calculation: Search the FAQ database

[0624] Output: Search results (existing answers)

[0625] The server creates a response and sends it to the new member's device.

[0626] It creates an answer based on the search results and sends it to the device, and if an answer is not found, it uses a generative AI model to generate a new answer.

[0627] Input: Search results or Fee burden

[0628] Output: Send the response to the new member

[0629] Through this series of processes, the "smart handover" system realizes efficient job handover and allows new members to quickly adapt to the job.

[0630] (Application example 1)

[0631] 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."

[0632] Traditionally, work handovers have mainly been conducted through face-to-face explanations or information sharing via email, which has resulted in insufficient handover information, making it difficult for new workers to quickly adapt to the work. Furthermore, in the work processes within the factory, if the handover is not carried out properly, problems such as reduced work efficiency can arise. Furthermore, when new workers have questions, they often cannot receive prompt and accurate answers, which often leads to work delays.

[0633] 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.

[0634] In this invention, the server includes means for collecting task handover information interactively, means for automatically generating standardized handover documents based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for converting voice input into text and means for analyzing the handover information using generative artificial intelligence, means for saving the generated handover documents and making them accessible to other members, and means for supporting work processes within the factory. This improves the efficiency of the task handover process, allowing new workers to quickly adapt to the work. Furthermore, efficient and accurate handovers of work processes within the factory are possible, improving work efficiency. Furthermore, when new workers have questions, they can receive prompt and accurate answers, preventing work delays.

[0635] The "means for collecting task handover information in an interactive manner" is a means for providing an interface for collecting task handover information through a dialogue with a user, and for organizing the information in an interactive manner.

[0636] "Means for automatically generating standardized handover documents based on collected business handover information" refers to means for analyzing collected handover information and automatically creating documents in a unified format.

[0637] "Means for quickly answering questions based on accumulated handover information and FAQ database" refers to a means for searching pre-accumulated handover information and FAQ database to quickly provide appropriate answers to questions from users.

[0638] The "means for converting speech input into text" refers to a means for converting information input by speech by a user into text data using natural language processing technology.

[0639] "Means for analyzing handover information using generative artificial intelligence" refers to means for analyzing handover information collected using generative artificial intelligence and extracting necessary information.

[0640] "Means for storing the generated handover documents and making them accessible to other members" means means for storing the automatically generated handover documents in a database so that other members can access, view, and use them at any time.

[0641] "Means to support work processes within the factory" refers to means for monitoring the progress of work within the factory in real time and improving work efficiency by providing appropriate information and work instructions.

[0642] This invention is a system for streamlining task handover in manufacturing sites, which collects task handover information interactively, automatically generates standardized handover documents, and provides quick answers to questions based on accumulated information and an FAQ database. It also includes a function to support work processes within the factory.

[0643] Hardware and software used

[0644] 1. Hardware:

[0645] Work robots: assist with work and collect information within the factory.

[0646] Voice input device: Collects voice information from workers.

[0647] Network connection: Data communication between the server, robot, and terminal.

[0648] 2. Software:

[0649] Python 3.8 or higher: Use as the primary programming language.

[0650] OpenAI GPT-3 model: Used to collect and analyze job handover information, generate handover documents, and answer questions.

[0651] Google Speech-to-Text: Converts voice input into text.

[0652] Process Overview

[0653] 1. Collect handover information:

[0654] The server works in conjunction with a device that converts voice input into text, converting the voice input from the worker into text data. The converted text data is analyzed by generative artificial intelligence (GPT-3) and collected as handover information.

[0655] 2. Generate handover documents:

[0656] The server automatically generates a unified handover document based on the collected handover information, which includes information such as the project status, next steps, tools to be used, and contact information for the people involved.

[0657] 3. Question answering function:

[0658] When a new worker asks a question, the server references the accumulated handover information and FAQ database to provide a quick answer. For questions not in the FAQ database, the server uses the GPT-3 model to generate an appropriate answer and add it to the database.

[0659] 4. Factory support:

[0660] The server monitors and supports the work process in the factory in real time based on the collected handover information, providing the necessary information for specific work steps and improving work efficiency.

[0661] Specific example demo

[0662] For example, imagine a situation where a project is underway in a factory and the next task needs to be handed over. The existing worker asks the robot, "What is the next task?" The voice input through the voice input device is converted into text via Google Speech-to-Text. The server uses generative artificial intelligence to answer this question, saying, "The next task is to check the quality of the parts and perform the assembly process."

[0663] In another scenario, consider a new worker asking, "How do I start the system?" The server searches the FAQ database to find and provide the appropriate answer. If the answer is not in the FAQ database, the server uses the GPT-3 model to generate an answer: "To start the system, power it on, log in, and select the start-up option from the main menu," which is immediately provided to the new worker.

[0664] Example prompt sentence:

[0665] Please tell me the current progress of the project.

[0666] "What's the next task?"

[0667] "How do I start the system?"

[0668] In this way, using this system makes the handover of work more efficient and enables new workers to quickly adapt to the work.

[0669] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0670] Step 1:

[0671] The user (existing worker) inputs handover information to the robot by voice. A voice input device is used for voice input. The input voice data is converted into text data using voice recognition technology (Google Speech-to-Text). This converts the voice data into text format, making it easier to handle in subsequent processes.

[0672] Input: Voice data (questions and information)

[0673] Output: Text data (questions and information)

[0674] Step 2:

[0675] The server sends the text data to a generative artificial intelligence (GPT-3 model) for analysis. The necessary handover information is extracted from the analyzed data. Here, the text data is parsed into a specific format and organized as handover information.

[0676] Input: Text data

[0677] Output: Parsed handover information

[0678] Step 3:

[0679] The server automatically generates standardized handover documents based on the analyzed handover information. Generative AI is used to create documents in a unified format. These documents include project progress, next steps, tools to be used, and contact information for the people involved.

[0680] Input: Parsed handover information

[0681] Output: Standardized handover documents

[0682] Step 4:

[0683] The server saves the generated handover document in a database so that other members can access it. The saved handover document can be accessed by a new worker whenever necessary. This makes it easy to share information between workers.

[0684] Input: Standardized handover documents

[0685] Output: Handover document stored in database

[0686] Step 5:

[0687] When a new worker asks a question, the terminal (robot or computer) sends the question to the server. The server searches the accumulated handover information and FAQ database to provide an appropriate answer. If the FAQ database does not contain a corresponding answer, a new answer is generated using generative artificial intelligence and added to the database.

[0688] Input: New worker question

[0689] Output: The appropriate answer from the server

[0690] Step 6:

[0691] The terminal receives the answer provided by the server and presents it to the new worker. This allows the worker's questions to be resolved quickly and prevents work delays. The answer is displayed in text format or played back aloud.

[0692] Input: Response from the server

[0693] Output: Presents the answer to the new worker

[0694] The above processing steps improve the efficiency of work handover within the factory and create an environment in which new workers can quickly adapt to their work.

[0695] 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.

[0696] The "smart handover" system of the present invention is designed to streamline the task handover process and allow new members to quickly adapt to the task. The present invention can be combined with an emotion engine that recognizes the user's emotions to further improve the user experience. The system consists of the following main components:

[0697] 1. A method for collecting information on business handover in an interactive format

[0698] Provide an interface for users to enter handover information, for example, existing members answering specific questions such as "What is the current status of the project?"

[0699] The server uses generative artificial intelligence to generate and collect appropriate answers to user questions, interacting with the user using natural language processing to obtain important details about the business.

[0700] 2. A method for automatically generating standardized handover documents based on collected business handover information

[0701] The server consolidates the collected handover information and automatically generates handover documents in a standardized format.

[0702] This handover document is structured so that each member can easily understand it, and clearly states important points of the work and the next tasks to be performed.

[0703] 3. A means of quickly answering questions based on accumulated handover information and a FAQ database

[0704] The server searches the accumulated handover information and FAQ database to quickly answer the new member's questions. For example, if a new member asks, "How do I start the system?", the server will refer to the FAQ database and provide an answer.

[0705] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[0706] 4. Emotion engine that recognizes user emotions

[0707] The terminal collects the user's emotional data (e.g., facial expressions and voice tone) through the interface.

[0708] The server uses an emotion engine to analyze the collected emotion data and recognize the user's emotional state, which is then used to adjust the tone of the interaction and provide appropriate responses.

[0709] Based on the analysis results of the emotion engine, the server or terminal will take adaptive measures, such as displaying a message encouraging relaxation if the user is feeling stressed.

[0710] Specific examples

[0711] For example, if there is a project that requires handover, the system can be used in the following manner.

[0712] 1. User Input

[0713] A user (existing member) logs in to the system and enters a question through the interface, such as, "What is the next task I should do?" At this time, the emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[0714] 2. Server Processing

[0715] The server uses generative artificial intelligence to check the current project progress from a collected database and respond with a list of related tasks, such as, "The next task is to review the design and get it approved by the client."

[0716] The emotion engine analyzes the user's emotional state and generates responses with appropriate tone and wording.

[0717] 3. Creating and saving handover documents

[0718] The server uses the information collected interactively to automatically generate a comprehensive handover document that includes project status, next tasks, tools to be used, and contact information for everyone involved.

[0719] Save the generated handover document as a file and set it up so that other members can access it.

[0720] 4. Answering questions from new members

[0721] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If no answer is found, it uses generative artificial intelligence to generate a new answer and provides it.

[0722] 5. Emotion Recognition and Adaptive Responses

[0723] The device will recognize the emotions of the new member from their facial expressions and voice, and if they are feeling stressed, for example, it will display a message saying, "Please relax and continue working."

[0724] By operating this system, new members can quickly adapt to the work, improving the company's work efficiency, and the system also provides a better user experience by enabling adaptive responses based on the user's emotions. In this way, the present invention can achieve effective and efficient work handover.

[0725] The processing flow will be explained below.

[0726] Step 1:

[0727] A user accesses the interface and enters a question to begin collecting handover information, such as "What is the current project status?"

[0728] Step 2:

[0729] The device captures the user's input and sends the collected questions along with the user's facial expressions and tone of voice to the emotion engine.

[0730] Step 3:

[0731] The emotion engine analyzes the user's emotion data and recognizes their emotional state, such as whether they are tense or relaxed.

[0732] Step 4:

[0733] The server sends the question received from the user to the generative AI and instructs it to start a dialogue. At that time, the server also sends the analysis results of the emotion engine along with the question content to the generative AI.

[0734] Step 5:

[0735] The server receives the answer from the generative AI. This answer is provided in an appropriate tone depending on the emotional situation. For example, you might get an answer like "The current ongoing project is at ~% progress."

[0736] Step 6:

[0737] The server collects these responses and stores them in a database as handover information. The collected information becomes the basis for handover documents.

[0738] Step 7:

[0739] Once the server has collected the answers to all the questions, it automatically generates a standardized handover document based on this information.

[0740] Step 8:

[0741] The server saves the created handover document as a file, and the saved file is set so that other members can access it.

[0742] Step 9:

[0743] The device (the new member's computer or smartphone) accesses the handover document and retrieves the necessary information.

[0744] Step 10:

[0745] A user (new member) inputs a question about the FAQ through the system interface, for example, "How do I start the system?"

[0746] Step 11:

[0747] The device sends the user's facial expressions and tone of voice to the emotion engine.

[0748] Step 12:

[0749] The emotion engine analyzes the user's emotion data and recognizes their current emotional state.

[0750] Step 13:

[0751] The server consults the FAQ database to find an existing answer to the question. If found, it provides the answer to the user. The answer is adjusted based on the analysis results from the emotion engine.

[0752] Step 14:

[0753] If the server does not have a corresponding answer in its FAQ database, it uses generative artificial intelligence to generate a new answer and provides it in a tone that corresponds to the analyzed emotional state.

[0754] Step 15:

[0755] Users can check the answers to the provided FAQs to obtain the information they need for their work. Also, if the user is feeling stressed, for example, the system will display a message encouraging relaxation.

[0756] In this way, the present invention not only efficiently collects task handover information and automatically generates standardized handover documents, but also improves the user experience by adaptively responding to the user's emotional state.

[0757] Example 2

[0758] 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."

[0759] The process of business handover presents a challenge for new members, making it difficult for them to quickly adapt to the new work. Furthermore, traditional handover processes often result in poor user experience and a lack of emotional support, which can lead to stress for new members and reduced work efficiency.

[0760] 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.

[0761] In this invention, the server includes means for collecting task handover information in an interactive manner, means for automatically generating a standardized handover document based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for collecting emotion data, and means for analyzing the emotion data and responding adaptively based on the user's emotional state. This not only enables new members to quickly adapt to the task and improves work efficiency, but also enables adaptive responses according to the user's emotions, making it possible to provide a better user experience.

[0762] The "means for collecting task handover information interactively" is a function that allows the user to input questions and answers through an interface and collect the necessary task handover information based on them.

[0763] "Means for automatically generating standardized handover documents based on collected business handover information" refers to a function in which the system organizes collected handover information and automatically creates documents related to business handover according to a specific format.

[0764] "Means for quickly answering questions based on accumulated handover information and FAQ database" refers to a function in which the system searches the handover information and FAQ database that have already been saved and provides immediate answers to questions from users.

[0765] "Means for collecting emotional data" means the ability to capture emotion-related data, such as a user's facial expressions or vocal tone, and enable the system to analyze that data.

[0766] "Means for analyzing emotional data and responding adaptively based on the user's emotional state" refers to a function that analyzes collected emotional data, determines the user's current emotional state, and generates appropriate dialogue and messages accordingly.

[0767] The "smart handover" system of the present invention is designed to streamline task handover and enable new members to adapt to the task in a short period of time. In particular, by incorporating an emotion engine that recognizes the user's emotions, the user experience can be improved. The system includes the following main components:

[0768] A means of collecting information on business handover in an interactive format

[0769] The user inputs task handover information using a dedicated interface. This is done using generative AI (e.g., OpenAI GPT-3) that utilizes natural language processing technology. For example, if the user inputs a question such as "What task should I do next?", the generative AI generates an appropriate answer. At this time, the device also collects emotional data such as the user's facial expressions and tone of voice.

[0770] A method for automatically generating standardized handover documents based on collected business handover information

[0771] The server analyzes the collected handover information and automatically generates handover documents in a standardized format. These documents include the project's progress, next tasks, tools to be used, and contact information for the members involved. The generated documents are saved in cloud storage (e.g., Google Drive or Dropbox) so users can access them at any time.

[0772] A means of quickly answering questions based on accumulated handover information and a FAQ database

[0773] When a new member types a question into the system (e.g., "How do I start the system?"), the server searches the accumulated FAQ database and provides an immediate answer. If necessary, new answers can be generated using generative artificial intelligence.

[0774] Means of collecting emotion data

[0775] The device collects the user's facial expressions and voice tone using a webcam and microphone.

[0776] A means of analyzing emotional data and adaptively responding based on the user's emotional state

[0777] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the collected emotion data. Based on the analysis results, the server or device responds adaptively. For example, if the user is feeling stressed, a message saying "Relax and continue working" is displayed.

[0778] Specific examples

[0779] For example, if there is a project that requires a handover, the system could be used in the following way. First, the user enters a question into the interface: "What is the next task?" The device collects facial expressions and voice tone. The server uses generative artificial intelligence to generate an answer to the question, replying, "The next task is to check the design and get it approved by the client." The emotion engine then analyzes the user's emotional state and adjusts the answer to an appropriate tone. The generated handover document is saved in cloud storage and set up so that other members can easily access it.

[0780] Prompt Sentence Examples

[0781] "What's the next task?"

[0782] Please tell me the progress of your current project.

[0783] "How do I start the system?"

[0784] By operating this system, new members can quickly adapt to the work, improving work efficiency, and it also enables adaptive responses based on user emotions, providing a better user experience, making the work handover process more effective and efficient.

[0785] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0786] Step 1:

[0787] A user logs in to the system.

[0788] Input: User ID and password

[0789] Action: User authentication occurs.

[0790] Output: Authentication successful message is displayed.

[0791] Step 2:

[0792] The user inputs questions about the business handover through the interface.

[0793] Input: Questions like "What's the next task?"

[0794] Action: The question text is sent to the server.

[0795] Output: The question is saved on the server.

[0796] Step 3:

[0797] The device collects the user's emotional data (facial expressions and vocal tone).

[0798] Input: Face image via webcam and voice via microphone

[0799] How it works: Emotion data is captured and sent to a server.

[0800] Output: Emotion data is stored on the server.

[0801] Step 4:

[0802] The server uses generative artificial intelligence (e.g., OpenAI GPT-3) to analyze the entered question and generate an appropriate answer.

[0803] Input: User question text

[0804] Data processing: Perform natural language processing of questions and database searches.

[0805] Output: Answer text: "The next task is to review the design and get it approved by the client."

[0806] Step 5:

[0807] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the collected emotion data.

[0808] Input: User emotion data

[0809] Data Computation: Performs sentiment analysis to determine the user's emotional state.

[0810] Output: The user's emotional state (e.g., feeling stressed) is determined.

[0811] Step 6:

[0812] The server responds adaptively based on the emotional state.

[0813] Input: User's emotional state and answer text

[0814] Data processing: Adjust the tone of the response text.

[0815] Output: Adjusted answer text: "Your next task is to review the design and get it approved by the client. Relax and get going."

[0816] Step 7:

[0817] The terminal displays the adjusted answer text to the user.

[0818] Input: Adjusted answer text

[0819] Behavior: Displays the answer text on the screen.

[0820] Output: The user can check the answer.

[0821] Step 8:

[0822] The server automatically generates standardized handover documents based on the information collected interactively.

[0823] Input: Collected business handover information

[0824] Data processing: Organizing information and generating documents in a specific format.

[0825] Output: Handover documents are generated (e.g., project status, next steps, tools used, contact information for involved people, etc.).

[0826] Step 9:

[0827] The server stores the handover document in cloud storage.

[0828] Input: Generated handover document

[0829] Action: Save file to cloud storage (e.g. Google Drive, Dropbox)

[0830] Output: The handover document is saved to cloud storage and a sharing link is generated.

[0831] Step 10:

[0832] A user (new member) enters a question into the system.

[0833] Input: Questions like "How do I boot my system?"

[0834] Action: The question text is sent to the server.

[0835] Output: The question is saved on the server.

[0836] Step 11:

[0837] The server searches a stored FAQ database and provides existing answers to the question.

[0838] Input: Question text

[0839] Data processing: Searching the FAQ database and extracting matching answers

[0840] Output: Answer text: "To start the system, first press the power button, then enter your ID and password on the login screen."

[0841] Step 12:

[0842] If the server cannot find an appropriate answer, it uses generative artificial intelligence to generate a new answer.

[0843] Input: Question text

[0844] Data processing: Answer generation using generative artificial intelligence

[0845] Output: New answer text (e.g., "To start your system, first press the power button, then enter your ID and password on the login screen.")

[0846] Step 13:

[0847] The device sends the new member's facial expressions and voice to the emotion engine for analysis.

[0848] Input: User emotion data

[0849] Data processing: Emotion data analysis

[0850] Output: User's emotional state

[0851] Step 14:

[0852] The server generates an adaptive message based on the analysis results.

[0853] Input: User's emotional state

[0854] Data processing: Message generation according to emotional state

[0855] Output: "Just relax and get working."

[0856] Step 15:

[0857] The terminal displays the generated message on the screen.

[0858] Input: Message text

[0859] Behavior: Displays a message on the screen.

[0860] Output: The user is helped to acknowledge the message and relax.

[0861] (Application example 2)

[0862] 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."

[0863] Conventional work handover processes have the challenge of making it difficult for new members to quickly adapt to the work. Managing robots in factories, in particular, requires efficient communication of information due to the many detailed operating procedures and precautions required. Furthermore, communication of information can be unclear or emotional stress can arise, leading to reduced productivity and mistakes. To address these issues, a system is needed that allows new members to quickly and effectively adapt to the work environment.

[0864] The specific processing by the specific 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 collecting task handover information in an interactive format, means for automatically generating a standardized handover document based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for analyzing the user's emotional state using an emotion engine, and means for providing an interface operated by the industrial machinery manager. This enables new members to quickly adapt to the work environment and reduces emotional stress.

[0865] The "interactive format" is a format in which the user and the system collect information by exchanging questions and answers.

[0866] "Business handover information" refers to information including the progress of a specific business, the next task to be performed, the tools to be used, and contact information of the members involved.

[0867] A "standardized handover document" is a document that is automatically generated in a consistent and easy-to-understand format based on collected business handover information.

[0868] An "FAQ database" is a database that stores frequently asked questions and their answers.

[0869] An "emotion engine" is software or a system that analyzes emotional data such as a user's facial expressions and tone of voice to recognize the user's emotional state.

[0870] "Industrial machinery" refers to devices such as automated machinery and robots that are primarily used in industrial environments such as factories.

[0871] The "interface operated by the administrator" refers to a graphical user interface (GUI) or command line interface (CLI) intended for use by an administrator of industrial machinery.

[0872] "Generative AI" is an AI technology that automatically generates appropriate answers to questions posed by users in natural language.

[0873] The "smart factory robot handover support system" of this invention is a system that streamlines the handover process for robots working in a factory and allows new members to quickly adapt to the work. The invention is composed of the following main components:

[0874] 1. Gathering information on business handover in an interactive format

[0875] The user (factory manager) inputs handover information through an interactive interface. For example, the factory manager may input a question such as, "How do I maintain a robot?" At this time, the generative AI automatically generates an appropriate answer to the user's question.

[0876] 2. Automatic generation of standardized handover documents based on collected information

[0877] The server processes the collected task handover information in a batch and automatically generates a handover document in a standardized format, which includes the work content, procedures, and important points.

[0878] 3. Quick answers based on accumulated information and FAQ database

[0879] The server refers to the accumulated handover information and FAQ database to quickly provide answers to questions from new members. For example, if a new member asks, "How do I start the system?", the server refers to the FAQ database and provides an answer based on that.

[0880] 4. Use of Emotion Engine

[0881] The terminal collects emotional data (facial expressions and voice tone) through the administrator's interface. The server analyzes this emotional data using an emotion engine to understand the user's emotional state. For example, if the user is feeling stressed, the system displays a message encouraging relaxation. In this way, adaptive responses are made according to the user's emotional state.

[0882] Specific examples

[0883] For example, the following is the flow when a factory manager asks, "How do I maintain a robot?"

[0884] 1. User Input

[0885] A factory manager logs into the interface and types a question such as, "How do I maintain the robot?" At this time, the emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[0886] 2. Server Processing

[0887] The server uses generative artificial intelligence to search the database for relevant handover information and generate an appropriate answer, such as, "The robot's scheduled maintenance is performed every Monday. This includes checking the battery, calibrating the sensors, and updating the navigation system."

[0888] The emotion engine also analyzes the user's emotional state and provides responses in an appropriate tone and language. If the user is feeling stressed, the message displayed will be, "Please relax. We will respond appropriately."

[0889] 3. Automatic generation and storage of handover documents

[0890] Based on the information collected interactively, the server automatically generates comprehensive handover documents, including robot maintenance methods, work procedures, and important points, and stores them in a format that can be accessed by other team members.

[0891] An example of a prompt is as follows:

[0892] Q: How do I maintain my robot?

[0893] Answer: Routine maintenance of the robot is performed every Monday, which includes checking the battery, calibrating the sensors, and updating the navigation system.

[0894] The above system allows new members to quickly adapt to the work environment and reduces emotional stress, enabling them to work more efficiently.

[0895] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0896] Step 1:

[0897] The user (factory manager) logs into the interface and enters interactive questions.

[0898] Input: The user types a question: "How do I maintain my robot?"

[0899] Data processing: The emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[0900] Output: The user's question and emotion data are sent to the system.

[0901] Step 2:

[0902] The server uses generative artificial intelligence to generate answers to questions.

[0903] Input: User questions, collected emotional data, and stored handover information.

[0904] Data Computing: Generative AI uses natural language processing to search for relevant information in a database and generate appropriate answers.

[0905] Output: The server generates an answer and sends it to the user.

[0906] Step 3:

[0907] An emotion engine analyzes the user's emotional state and provides adaptive answers.

[0908] Input: Server-generated answers and user emotional state data.

[0909] Data Calculation: The emotion engine analyzes the user's emotional state and adjusts the tone and content of the response.

[0910] Output: For example, if the user is feeling stressed, an additional message will be displayed: "Relax. We will respond appropriately."

[0911] Step 4:

[0912] Based on the information collected by the server, standardized handover documents are automatically generated.

[0913] Input: Business handover information collected interactively.

[0914] Data processing: The server organizes the collected information in a standardized format and automatically generates consistent handover documents.

[0915] Output: The generated handover document is saved as a file and set up so that other members can access it.

[0916] Step 5:

[0917] Providing quick answers to new members' questions.

[0918] Input: New member's question (e.g., "How do I start the system?").

[0919] Data processing: The server searches the FAQ database and provides an existing answer. If no answer is found, a new answer is generated using generative artificial intelligence.

[0920] Output: Provide an immediate answer to new members.

[0921] The specific actions of each step enable factory managers and new members to carry out their work more efficiently, improving the productivity of the entire system.

[0922] 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.

[0923] 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.

[0924] 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.

[0925] [Third embodiment]

[0926] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0927] 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.

[0928] 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).

[0929] 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.

[0930] 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.

[0931] 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).

[0932] 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.

[0933] 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.

[0934] 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.

[0935] 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.

[0936] 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.

[0937] 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."

[0938] The "smart handover" system of the present invention is designed to streamline the process of job handover and enable new members to quickly adapt to the job. This system consists of the following main components:

[0939] 1. A method for collecting information on business handover in an interactive format

[0940] Provide an interface for users to enter handover information, for example, existing members answering specific questions such as "What is the current status of the project?"

[0941] The server uses generative artificial intelligence to generate and collect appropriate answers to user questions, interacting with the user using natural language processing to obtain important details about the business.

[0942] 2. A method for automatically generating standardized handover documents based on collected business handover information

[0943] The server consolidates the collected handover information and automatically generates handover documents in a standardized format.

[0944] This handover document is structured so that each member can easily understand it, and clearly states important points of the work and the next tasks to be performed.

[0945] 3. A means of quickly answering questions based on accumulated handover information and a FAQ database

[0946] The server searches the accumulated handover information and FAQ database to quickly answer the new member's questions. For example, if a new member asks, "How do I start the system?", the server will refer to the FAQ database and provide an answer.

[0947] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[0948] Specific examples

[0949] For example, if there is a project that requires handover, the system can be used in the following manner.

[0950] 1. User Procedure

[0951] A user (existing member) logs into the system and enters the question "What is the next task?" through the interface.

[0952] 2. Server Processing

[0953] The server uses generative artificial intelligence to check the progress of current projects from a collected database and respond by listing relevant tasks.

[0954] For example, the generated answer might be, "The next task is to review the design and get it approved by the client."

[0955] 3. Generate handover documents

[0956] Using the information collected interactively, the server automatically generates a comprehensive handover document that includes project status, next tasks, tools to be used, and contact information for everyone involved.

[0957] 4. Answering new member questions

[0958] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If it can't find one, it uses generative artificial intelligence to instantly generate a new answer and provide it.

[0959] By operating this system, new members can quickly adapt to the work, improving the company's work efficiency. In this way, the present invention can realize an effective and efficient work handover.

[0960] The processing flow will be explained below.

[0961] Step 1:

[0962] A user accesses the interface and enters a question to begin collecting handover information, such as "What is the current project status?"

[0963] Step 2:

[0964] The server analyzes the question received from the user and instructs the generative AI to start a dialogue, sending the question content to the generative AI.

[0965] Step 3:

[0966] The server receives the answer received from the generative AI. For example, you can get an answer such as "The current ongoing project is at ~% progress."

[0967] Step 4:

[0968] The server collects these responses and stores them in a database as handover information. The collected information becomes the basis for handover documents.

[0969] Step 5:

[0970] Once the server has collected the answers to all the questions, it automatically generates a standardized handover document based on this information.

[0971] Step 6:

[0972] The server saves the created handover document as a file, and the saved file is set so that other members can access it.

[0973] Step 7:

[0974] The device (the new member's computer or smartphone) accesses the handover document and retrieves the necessary information.

[0975] Step 8:

[0976] A user (new member) inputs a question about the FAQ through the system interface, for example, "How do I start the system?"

[0977] Step 9:

[0978] The server consults the FAQ database to find an existing answer to the question, and if found, provides the answer to the user.

[0979] Step 10:

[0980] If the server does not have a corresponding answer in its FAQ database, it uses generative artificial intelligence to generate a new answer and provides it to the user.

[0981] Step 11:

[0982] Users can check the answers to the provided FAQs and obtain the information they need to do their jobs. This process allows new members to quickly adapt to the job.

[0983] Example 1

[0984] 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."

[0985] The traditional process for handing over work relied on manual information gathering and document creation, making it inefficient and difficult for new members to quickly adapt to the work. Furthermore, the accumulated handover information and FAQ database were not properly utilized, resulting in a disruptive workflow.

[0986] 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.

[0987] In this invention, the server includes a means for allowing a user to interactively collect task handover information through an interface, a means for automatically generating standardized handover documents using a generation AI model based on the collected task handover information, and a means for quickly answering user questions based on the accumulated handover information and FAQ database, thereby enabling efficient task handover and enabling new members to quickly adapt to the tasks.

[0988] A "user" is a person who accesses the system to collect task handover information and input questions.

[0989] An "interface" is a screen or input form that allows a user to interact with a system.

[0990] A "generative AI model" is an artificial intelligence that uses natural language processing technology to generate appropriate answers or documents based on input information.

[0991] A "standardized handover document" is a document created in a unified format based on collected business handover information.

[0992] An "FAQ database" is a database that stores frequently asked questions and their answers.

[0993] The "means for collecting" refers to a function that allows a user to input task handover information through an interface.

[0994] "Means for automatic generation" refers to the ability to create handover documents using a generative AI model based on collected information.

[0995] "Means for quick response" refers to the function of quickly providing answers to users' questions from the accumulated handover information and FAQ database.

[0996] The "smart handover" system of the present invention is designed to streamline the job handover process and allow new members to quickly adapt to the job. This system consists of the following main components:

[0997] 1. A means for users to collect task handover information interactively through an interface

[0998] Users log in to the system and enter task handover information through the interface. For example, an existing member enters a question such as, "What is the next task?"

[0999] The interface is a dashboard accessible through a web browser that allows users to easily enter business questions.

[1000] 2. A method for automatically generating standardized handover documents using a generative AI model based on collected business handover information

[1001] The server uses generative artificial intelligence (generative AI model) to process the collected handover information and automatically generate a handover document in a standardized format, which includes information such as the project's progress, next tasks, tools to be used, and contact information for the members involved.

[1002] As a specific example, a user might ask, "What is the next task?" and the generative AI model might respond, "The next task is to review the design and get it approved by the client," and this information would be reflected in the handover document.

[1003] 3. A means of quickly answering user questions based on accumulated handover information and a FAQ database

[1004] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If no answer is found, it uses a generative AI model to generate a new answer and provides it.

[1005] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[1006] Hardware and software used

[1007] Server: High-performance data processing server

[1008] Generative AI model: An AI model using natural language processing

[1009] User devices: PCs, smartphones, etc.

[1010] Interface: UI accessible through a web browser

[1011] Database: A database that stores business handover information and FAQ information

[1012] Specific examples of operation

[1013] 1. User steps: Log in and type "What's my next task?"

[1014] 2. Server processing: Using the generative AI model, generate an answer, such as "The next task is to review the design and submit it to the client for approval."

[1015] 3. Generate handover documents: Automatically document information collected interactively.

[1016] 4. Answering new member questions: Ask "How do I start the system?" and we'll search our FAQ database to provide an answer, or generate a new answer with our generative AI model.

[1017] In this way, the present invention realizes an efficient work handover, allowing new members to quickly adapt to the work.

[1018] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1019] Step 1: User Login

[1020] The user accesses the interface.

[1021] The user opens a web browser and accesses the URL of the "Smart Handover" system.

[1022] Input: Login URL

[1023] Output: Login screen displayed

[1024] The user enters their login information and logs into the system.

[1025] The user enters their username and password and clicks the "Login" button.

[1026] Input: Username, Password

[1027] Data processing: The server authenticates the entered information

[1028] Output: Authentication result (success or failure), displayed on the main dashboard if successful

[1029] Step 2: Enter and submit your question

[1030] The user types the question in the interface: "What is my next task?"

[1031] A user clicks the "Ask a Question" button from the main dashboard and types "What's my next task?" into the question input field.

[1032] Input: Question (What is the next task?)

[1033] Output: Destination (server) of the query

[1034] The user clicks the "Submit" button.

[1035] Click the "Submit" button to submit the entered question.

[1036] Input: Click on submit button

[1037] Output: Sends the question to the server

[1038] Step 3: Question processing and answer generation

[1039] The server receives a query from a user.

[1040] The server receives the question sent by the user and analyzes its contents.

[1041] Input: User's question

[1042] Data processing: Analysis of questions

[1043] Output: Analysis result (prompt statement)

[1044] The server sends a prompt to the generative AI model.

[1045] The server sends a prompt to the generative AI model: "What is the next task?"

[1046] Input: Analysis result (prompt statement)

[1047] Output: Input to the generative AI model

[1048] A generative AI model generates answers to questions.

[1049] A generative AI model generates an answer based on the prompt.

[1050] Input: prompt statement

[1051] Data Computing: Answer Generation Using Natural Language Processing

[1052] Output: Answer (The next task is to check the design and give it to the client for approval)

[1053] The server receives the generated answer and sends it to the user.

[1054] The answer received from the generative AI model is sent to the user.

[1055] Input: Generated answer

[1056] Output: Response sent to user

[1057] Step 4: Automatic generation of handover documents

[1058] The server organizes the collected dialogue information and generates standardized handover documents.

[1059] Handover documents are automatically generated in a standardized format based on information collected interactively.

[1060] Input: Information collected interactively

[1061] Data processing: organizing information and converting it into a format

[1062] Output: Handover document (project status, next tasks, tools used, contact information of involved people)

[1063] The server stores the generated handover document in a database.

[1064] Store handover documents in a database and make them accessible as needed.

[1065] Input: Handover document

[1066] Output: Save to database

[1067] Step 5: Answer new member questions

[1068] A new member asks from a terminal, "How do I start the system?"

[1069] New members type in their questions on their devices and submit them.

[1070] Input: Question (How do I start the system?)

[1071] Output: Sends the question to the server

[1072] The server searches the FAQ database and extracts existing answers.

[1073] Search our FAQ database to see if your question is answered.

[1074] Input: User's question

[1075] Data Calculation: Search the FAQ database

[1076] Output: Search results (existing answers)

[1077] The server creates a response and sends it to the new member's device.

[1078] It creates an answer based on the search results and sends it to the device, and if an answer is not found, it uses a generative AI model to generate a new answer.

[1079] Input: Search results or Fee burden

[1080] Output: Send the response to the new member

[1081] Through this series of processes, the "smart handover" system realizes efficient job handover and allows new members to quickly adapt to the job.

[1082] (Application example 1)

[1083] 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."

[1084] Traditionally, work handovers have mainly been conducted through face-to-face explanations or information sharing via email, which has resulted in insufficient handover information, making it difficult for new workers to quickly adapt to the work. Furthermore, in the work processes within the factory, if the handover is not carried out properly, problems such as reduced work efficiency can arise. Furthermore, when new workers have questions, they often cannot receive prompt and accurate answers, which often leads to work delays.

[1085] 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.

[1086] In this invention, the server includes means for collecting task handover information interactively, means for automatically generating standardized handover documents based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for converting voice input into text and means for analyzing the handover information using generative artificial intelligence, means for saving the generated handover documents and making them accessible to other members, and means for supporting work processes within the factory. This improves the efficiency of the task handover process, allowing new workers to quickly adapt to the work. Furthermore, efficient and accurate handovers of work processes within the factory are possible, improving work efficiency. Furthermore, when new workers have questions, they can receive prompt and accurate answers, preventing work delays.

[1087] The "means for collecting task handover information in an interactive manner" is a means for providing an interface for collecting task handover information through a dialogue with a user, and for organizing the information in an interactive manner.

[1088] "Means for automatically generating standardized handover documents based on collected business handover information" refers to means for analyzing collected handover information and automatically creating documents in a unified format.

[1089] "Means for quickly answering questions based on accumulated handover information and FAQ database" refers to a means for searching pre-accumulated handover information and FAQ database to quickly provide appropriate answers to questions from users.

[1090] The "means for converting speech input into text" refers to a means for converting information input by speech by a user into text data using natural language processing technology.

[1091] "Means for analyzing handover information using generative artificial intelligence" refers to means for analyzing handover information collected using generative artificial intelligence and extracting necessary information.

[1092] "Means for storing the generated handover documents and making them accessible to other members" means means for storing the automatically generated handover documents in a database so that other members can access, view, and use them at any time.

[1093] "Means to support work processes within the factory" refers to means for monitoring the progress of work within the factory in real time and improving work efficiency by providing appropriate information and work instructions.

[1094] This invention is a system for streamlining task handover in manufacturing sites, which collects task handover information interactively, automatically generates standardized handover documents, and provides quick answers to questions based on accumulated information and an FAQ database. It also includes a function to support work processes within the factory.

[1095] Hardware and software used

[1096] 1. Hardware:

[1097] Work robots: assist with work and collect information within the factory.

[1098] Voice input device: Collects voice information from workers.

[1099] Network connection: Data communication between the server, robot, and terminal.

[1100] 2. Software:

[1101] Python 3.8 or higher: Use as the primary programming language.

[1102] OpenAI GPT-3 model: Used to collect and analyze job handover information, generate handover documents, and answer questions.

[1103] Google Speech-to-Text: Converts voice input into text.

[1104] Process Overview

[1105] 1. Collect handover information:

[1106] The server works in conjunction with a device that converts voice input into text, converting the voice input from the worker into text data. The converted text data is analyzed by generative artificial intelligence (GPT-3) and collected as handover information.

[1107] 2. Generate handover documents:

[1108] The server automatically generates a unified handover document based on the collected handover information, which includes information such as the project status, next steps, tools to be used, and contact information for the people involved.

[1109] 3. Question answering function:

[1110] When a new worker asks a question, the server references the accumulated handover information and FAQ database to provide a quick answer. For questions not in the FAQ database, the server uses the GPT-3 model to generate an appropriate answer and add it to the database.

[1111] 4. Factory support:

[1112] The server monitors and supports the work process in the factory in real time based on the collected handover information, providing the necessary information for specific work steps and improving work efficiency.

[1113] Specific example demo

[1114] For example, imagine a situation where a project is underway in a factory and the next task needs to be handed over. The existing worker asks the robot, "What is the next task?" The voice input through the voice input device is converted into text via Google Speech-to-Text. The server uses generative artificial intelligence to answer this question, saying, "The next task is to check the quality of the parts and perform the assembly process."

[1115] In another scenario, consider a new worker asking, "How do I start the system?" The server searches the FAQ database to find and provide the appropriate answer. If the answer is not in the FAQ database, the server uses the GPT-3 model to generate an answer: "To start the system, power it on, log in, and select the start-up option from the main menu," which is immediately provided to the new worker.

[1116] Example prompt sentence:

[1117] Please tell me the current progress of the project.

[1118] "What's the next task?"

[1119] "How do I start the system?"

[1120] In this way, using this system makes the handover of work more efficient and enables new workers to quickly adapt to the work.

[1121] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1122] Step 1:

[1123] The user (existing worker) inputs handover information to the robot by voice. A voice input device is used for voice input. The input voice data is converted into text data using voice recognition technology (Google Speech-to-Text). This converts the voice data into text format, making it easier to handle in subsequent processes.

[1124] Input: Voice data (questions and information)

[1125] Output: Text data (questions and information)

[1126] Step 2:

[1127] The server sends the text data to a generative artificial intelligence (GPT-3 model) for analysis. The necessary handover information is extracted from the analyzed data. Here, the text data is parsed into a specific format and organized as handover information.

[1128] Input: Text data

[1129] Output: Parsed handover information

[1130] Step 3:

[1131] The server automatically generates standardized handover documents based on the analyzed handover information. Generative AI is used to create documents in a unified format. These documents include project progress, next steps, tools to be used, and contact information for the people involved.

[1132] Input: Parsed handover information

[1133] Output: Standardized handover documents

[1134] Step 4:

[1135] The server saves the generated handover document in a database so that other members can access it. The saved handover document can be accessed by a new worker whenever necessary. This makes it easy to share information between workers.

[1136] Input: Standardized handover documents

[1137] Output: Handover document stored in database

[1138] Step 5:

[1139] When a new worker asks a question, the terminal (robot or computer) sends the question to the server. The server searches the accumulated handover information and FAQ database to provide an appropriate answer. If the FAQ database does not contain a corresponding answer, a new answer is generated using generative artificial intelligence and added to the database.

[1140] Input: New worker question

[1141] Output: The appropriate answer from the server

[1142] Step 6:

[1143] The terminal receives the answer provided by the server and presents it to the new worker. This allows the worker's questions to be resolved quickly and prevents work delays. The answer is displayed in text format or played back aloud.

[1144] Input: Response from the server

[1145] Output: Presents the answer to the new worker

[1146] The above processing steps improve the efficiency of work handover within the factory and create an environment in which new workers can quickly adapt to their work.

[1147] 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.

[1148] The "smart handover" system of the present invention is designed to streamline the task handover process and allow new members to quickly adapt to the task. The present invention can be combined with an emotion engine that recognizes the user's emotions to further improve the user experience. The system consists of the following main components:

[1149] 1. A method for collecting information on business handover in an interactive format

[1150] Provide an interface for users to enter handover information, for example, existing members answering specific questions such as "What is the current status of the project?"

[1151] The server uses generative artificial intelligence to generate and collect appropriate answers to user questions, interacting with the user using natural language processing to obtain important details about the business.

[1152] 2. A method for automatically generating standardized handover documents based on collected business handover information

[1153] The server consolidates the collected handover information and automatically generates handover documents in a standardized format.

[1154] This handover document is structured so that each member can easily understand it, and clearly states important points of the work and the next tasks to be performed.

[1155] 3. A means of quickly answering questions based on accumulated handover information and a FAQ database

[1156] The server searches the accumulated handover information and FAQ database to quickly answer the new member's questions. For example, if a new member asks, "How do I start the system?", the server will refer to the FAQ database and provide an answer.

[1157] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[1158] 4. Emotion engine that recognizes user emotions

[1159] The terminal collects the user's emotional data (e.g., facial expressions and voice tone) through the interface.

[1160] The server uses an emotion engine to analyze the collected emotion data and recognize the user's emotional state, which is then used to adjust the tone of the interaction and provide appropriate responses.

[1161] Based on the analysis results of the emotion engine, the server or terminal will take adaptive measures, such as displaying a message encouraging relaxation if the user is feeling stressed.

[1162] Specific examples

[1163] For example, if there is a project that requires handover, the system can be used in the following manner.

[1164] 1. User Input

[1165] A user (existing member) logs in to the system and enters a question through the interface, such as, "What is the next task I should do?" At this time, the emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[1166] 2. Server Processing

[1167] The server uses generative artificial intelligence to check the current project progress from a collected database and respond with a list of related tasks, such as, "The next task is to review the design and get it approved by the client."

[1168] The emotion engine analyzes the user's emotional state and generates responses with appropriate tone and wording.

[1169] 3. Creating and saving handover documents

[1170] The server uses the information collected interactively to automatically generate a comprehensive handover document that includes project status, next tasks, tools to be used, and contact information for everyone involved.

[1171] Save the generated handover document as a file and set it up so that other members can access it.

[1172] 4. Answering questions from new members

[1173] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If no answer is found, it uses generative artificial intelligence to generate a new answer and provides it.

[1174] 5. Emotion Recognition and Adaptive Responses

[1175] The device will recognize the emotions of the new member from their facial expressions and voice, and if they are feeling stressed, for example, it will display a message saying, "Please relax and continue working."

[1176] By operating this system, new members can quickly adapt to the work, improving the company's work efficiency, and the system also provides a better user experience by enabling adaptive responses based on the user's emotions. In this way, the present invention can achieve effective and efficient work handover.

[1177] The processing flow will be explained below.

[1178] Step 1:

[1179] A user accesses the interface and enters a question to begin collecting handover information, such as "What is the current project status?"

[1180] Step 2:

[1181] The device captures the user's input and sends the collected questions along with the user's facial expressions and tone of voice to the emotion engine.

[1182] Step 3:

[1183] The emotion engine analyzes the user's emotion data and recognizes their emotional state, such as whether they are tense or relaxed.

[1184] Step 4:

[1185] The server sends the question received from the user to the generative AI and instructs it to start a dialogue. At that time, the server also sends the analysis results of the emotion engine along with the question content to the generative AI.

[1186] Step 5:

[1187] The server receives the answer from the generative AI. This answer is provided in an appropriate tone depending on the emotional situation. For example, you might get an answer like "The current ongoing project is at ~% progress."

[1188] Step 6:

[1189] The server collects these responses and stores them in a database as handover information. The collected information becomes the basis for handover documents.

[1190] Step 7:

[1191] Once the server has collected the answers to all the questions, it automatically generates a standardized handover document based on this information.

[1192] Step 8:

[1193] The server saves the created handover document as a file, and the saved file is set so that other members can access it.

[1194] Step 9:

[1195] The device (the new member's computer or smartphone) accesses the handover document and retrieves the necessary information.

[1196] Step 10:

[1197] A user (new member) inputs a question about the FAQ through the system interface, for example, "How do I start the system?"

[1198] Step 11:

[1199] The device sends the user's facial expressions and tone of voice to the emotion engine.

[1200] Step 12:

[1201] The emotion engine analyzes the user's emotion data and recognizes their current emotional state.

[1202] Step 13:

[1203] The server consults the FAQ database to find an existing answer to the question. If found, it provides the answer to the user. The answer is adjusted based on the analysis results from the emotion engine.

[1204] Step 14:

[1205] If the server does not have a corresponding answer in its FAQ database, it uses generative artificial intelligence to generate a new answer and provides it in a tone that corresponds to the analyzed emotional state.

[1206] Step 15:

[1207] Users can check the answers to the provided FAQs to obtain the information they need for their work. Also, if the user is feeling stressed, for example, the system will display a message encouraging relaxation.

[1208] In this way, the present invention not only efficiently collects task handover information and automatically generates standardized handover documents, but also improves the user experience by adaptively responding to the user's emotional state.

[1209] Example 2

[1210] 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."

[1211] The process of business handover presents a challenge for new members, making it difficult for them to quickly adapt to the new work. Furthermore, traditional handover processes often result in poor user experience and a lack of emotional support, which can lead to stress for new members and reduced work efficiency.

[1212] 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.

[1213] In this invention, the server includes means for collecting task handover information in an interactive manner, means for automatically generating a standardized handover document based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for collecting emotion data, and means for analyzing the emotion data and responding adaptively based on the user's emotional state. This not only enables new members to quickly adapt to the task and improves work efficiency, but also enables adaptive responses according to the user's emotions, making it possible to provide a better user experience.

[1214] The "means for collecting task handover information interactively" is a function that allows the user to input questions and answers through an interface and collect the necessary task handover information based on them.

[1215] "Means for automatically generating standardized handover documents based on collected business handover information" refers to a function in which the system organizes collected handover information and automatically creates documents related to business handover according to a specific format.

[1216] "Means for quickly answering questions based on accumulated handover information and FAQ database" refers to a function in which the system searches the handover information and FAQ database that have already been saved and provides immediate answers to questions from users.

[1217] "Means for collecting emotional data" means the ability to capture emotion-related data, such as a user's facial expressions or vocal tone, and enable the system to analyze that data.

[1218] "Means for analyzing emotional data and responding adaptively based on the user's emotional state" refers to a function that analyzes collected emotional data, determines the user's current emotional state, and generates appropriate dialogue and messages accordingly.

[1219] The "smart handover" system of the present invention is designed to streamline task handover and enable new members to adapt to the task in a short period of time. In particular, by incorporating an emotion engine that recognizes the user's emotions, the user experience can be improved. The system includes the following main components:

[1220] A means of collecting information on business handover in an interactive format

[1221] The user inputs task handover information using a dedicated interface. This is done using generative AI (e.g., OpenAI GPT-3) that utilizes natural language processing technology. For example, if the user inputs a question such as "What task should I do next?", the generative AI generates an appropriate answer. At this time, the device also collects emotional data such as the user's facial expressions and tone of voice.

[1222] A method for automatically generating standardized handover documents based on collected business handover information

[1223] The server analyzes the collected handover information and automatically generates handover documents in a standardized format. These documents include the project's progress, next tasks, tools to be used, and contact information for the members involved. The generated documents are saved in cloud storage (e.g., Google Drive or Dropbox) so users can access them at any time.

[1224] A means of quickly answering questions based on accumulated handover information and a FAQ database

[1225] When a new member types a question into the system (e.g., "How do I start the system?"), the server searches the accumulated FAQ database and provides an immediate answer. If necessary, new answers can be generated using generative artificial intelligence.

[1226] Means of collecting emotion data

[1227] The device collects the user's facial expressions and voice tone using a webcam and microphone.

[1228] A means of analyzing emotional data and adaptively responding based on the user's emotional state

[1229] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the collected emotion data. Based on the analysis results, the server or device responds adaptively. For example, if the user is feeling stressed, a message saying "Relax and continue working" is displayed.

[1230] Specific examples

[1231] For example, if there is a project that requires a handover, the system could be used in the following way. First, the user enters a question into the interface: "What is the next task?" The device collects facial expressions and voice tone. The server uses generative artificial intelligence to generate an answer to the question, replying, "The next task is to check the design and get it approved by the client." The emotion engine then analyzes the user's emotional state and adjusts the answer to an appropriate tone. The generated handover document is saved in cloud storage and set up so that other members can easily access it.

[1232] Prompt Sentence Examples

[1233] "What's the next task?"

[1234] Please tell me the progress of your current project.

[1235] "How do I start the system?"

[1236] By operating this system, new members can quickly adapt to the work, improving work efficiency, and it also enables adaptive responses based on user emotions, providing a better user experience, making the work handover process more effective and efficient.

[1237] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1238] Step 1:

[1239] A user logs in to the system.

[1240] Input: User ID and password

[1241] Action: User authentication occurs.

[1242] Output: Authentication successful message is displayed.

[1243] Step 2:

[1244] The user inputs questions about the business handover through the interface.

[1245] Input: Questions like "What's the next task?"

[1246] Action: The question text is sent to the server.

[1247] Output: The question is saved on the server.

[1248] Step 3:

[1249] The device collects the user's emotional data (facial expressions and vocal tone).

[1250] Input: Face image via webcam and voice via microphone

[1251] How it works: Emotion data is captured and sent to a server.

[1252] Output: Emotion data is stored on the server.

[1253] Step 4:

[1254] The server uses generative artificial intelligence (e.g., OpenAI GPT-3) to analyze the entered question and generate an appropriate answer.

[1255] Input: User question text

[1256] Data processing: Perform natural language processing of questions and database searches.

[1257] Output: Answer text: "The next task is to review the design and get it approved by the client."

[1258] Step 5:

[1259] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the collected emotion data.

[1260] Input: User emotion data

[1261] Data Computation: Performs sentiment analysis to determine the user's emotional state.

[1262] Output: The user's emotional state (e.g., feeling stressed) is determined.

[1263] Step 6:

[1264] The server responds adaptively based on the emotional state.

[1265] Input: User's emotional state and answer text

[1266] Data processing: Adjust the tone of the response text.

[1267] Output: Adjusted answer text: "Your next task is to review the design and get it approved by the client. Relax and get going."

[1268] Step 7:

[1269] The terminal displays the adjusted answer text to the user.

[1270] Input: Adjusted answer text

[1271] Behavior: Displays the answer text on the screen.

[1272] Output: The user can check the answer.

[1273] Step 8:

[1274] The server automatically generates standardized handover documents based on the information collected interactively.

[1275] Input: Collected business handover information

[1276] Data processing: Organizing information and generating documents in a specific format.

[1277] Output: Handover documents are generated (e.g., project status, next steps, tools used, contact information for involved people, etc.).

[1278] Step 9:

[1279] The server stores the handover document in cloud storage.

[1280] Input: Generated handover document

[1281] Action: Save file to cloud storage (e.g. Google Drive, Dropbox)

[1282] Output: The handover document is saved to cloud storage and a sharing link is generated.

[1283] Step 10:

[1284] A user (new member) enters a question into the system.

[1285] Input: Questions like "How do I boot my system?"

[1286] Action: The question text is sent to the server.

[1287] Output: The question is saved on the server.

[1288] Step 11:

[1289] The server searches a stored FAQ database and provides existing answers to the question.

[1290] Input: Question text

[1291] Data processing: Searching the FAQ database and extracting matching answers

[1292] Output: Answer text: "To start the system, first press the power button, then enter your ID and password on the login screen."

[1293] Step 12:

[1294] If the server cannot find an appropriate answer, it uses generative artificial intelligence to generate a new answer.

[1295] Input: Question text

[1296] Data processing: Answer generation using generative artificial intelligence

[1297] Output: New answer text (e.g., "To start your system, first press the power button, then enter your ID and password on the login screen.")

[1298] Step 13:

[1299] The device sends the new member's facial expressions and voice to the emotion engine for analysis.

[1300] Input: User emotion data

[1301] Data processing: Emotion data analysis

[1302] Output: User's emotional state

[1303] Step 14:

[1304] The server generates an adaptive message based on the analysis results.

[1305] Input: User's emotional state

[1306] Data processing: Message generation according to emotional state

[1307] Output: "Just relax and get working."

[1308] Step 15:

[1309] The terminal displays the generated message on the screen.

[1310] Input: Message text

[1311] Behavior: Displays a message on the screen.

[1312] Output: The user is helped to acknowledge the message and relax.

[1313] (Application example 2)

[1314] 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."

[1315] Conventional work handover processes have the challenge of making it difficult for new members to quickly adapt to the work. Managing robots in factories, in particular, requires efficient communication of information due to the many detailed operating procedures and precautions required. Furthermore, communication of information can be unclear or emotional stress can arise, leading to reduced productivity and mistakes. To address these issues, a system is needed that allows new members to quickly and effectively adapt to the work environment.

[1316] The specific processing by the specific 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 collecting task handover information in an interactive format, means for automatically generating a standardized handover document based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for analyzing the user's emotional state using an emotion engine, and means for providing an interface operated by the industrial machinery manager. This enables new members to quickly adapt to the work environment and reduces emotional stress.

[1317] The "interactive format" is a format in which the user and the system collect information by exchanging questions and answers.

[1318] "Business handover information" refers to information including the progress of a specific business, the next task to be performed, the tools to be used, and contact information of the members involved.

[1319] A "standardized handover document" is a document that is automatically generated in a consistent and easy-to-understand format based on collected business handover information.

[1320] An "FAQ database" is a database that stores frequently asked questions and their answers.

[1321] An "emotion engine" is software or a system that analyzes emotional data such as a user's facial expressions and tone of voice to recognize the user's emotional state.

[1322] "Industrial machinery" refers to devices such as automated machinery and robots that are primarily used in industrial environments such as factories.

[1323] The "interface operated by the administrator" refers to a graphical user interface (GUI) or command line interface (CLI) intended for use by an administrator of industrial machinery.

[1324] "Generative AI" is an AI technology that automatically generates appropriate answers to questions posed by users in natural language.

[1325] The "smart factory robot handover support system" of this invention is a system that streamlines the handover process for robots working in a factory and allows new members to quickly adapt to the work. The invention is composed of the following main components:

[1326] 1. Gathering information on business handover in an interactive format

[1327] The user (factory manager) inputs handover information through an interactive interface. For example, the factory manager may input a question such as, "How do I maintain a robot?" At this time, the generative AI automatically generates an appropriate answer to the user's question.

[1328] 2. Automatic generation of standardized handover documents based on collected information

[1329] The server processes the collected task handover information in a batch and automatically generates a handover document in a standardized format, which includes the work content, procedures, and important points.

[1330] 3. Quick answers based on accumulated information and FAQ database

[1331] The server refers to the accumulated handover information and FAQ database to quickly provide answers to questions from new members. For example, if a new member asks, "How do I start the system?", the server refers to the FAQ database and provides an answer based on that.

[1332] 4. Use of Emotion Engine

[1333] The terminal collects emotional data (facial expressions and voice tone) through the administrator's interface. The server analyzes this emotional data using an emotion engine to understand the user's emotional state. For example, if the user is feeling stressed, the system displays a message encouraging relaxation. In this way, adaptive responses are made according to the user's emotional state.

[1334] Specific examples

[1335] For example, the following is the flow when a factory manager asks, "How do I maintain a robot?"

[1336] 1. User Input

[1337] A factory manager logs into the interface and types a question such as, "How do I maintain the robot?" At this time, the emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[1338] 2. Server Processing

[1339] The server uses generative artificial intelligence to search the database for relevant handover information and generate an appropriate answer, such as, "The robot's scheduled maintenance is performed every Monday. This includes checking the battery, calibrating the sensors, and updating the navigation system."

[1340] The emotion engine also analyzes the user's emotional state and provides responses in an appropriate tone and language. If the user is feeling stressed, the message displayed will be, "Please relax. We will respond appropriately."

[1341] 3. Automatic generation and storage of handover documents

[1342] Based on the information collected interactively, the server automatically generates comprehensive handover documents, including robot maintenance methods, work procedures, and important points, and stores them in a format that can be accessed by other team members.

[1343] An example of a prompt is as follows:

[1344] Q: How do I maintain my robot?

[1345] Answer: Routine maintenance of the robot is performed every Monday, which includes checking the battery, calibrating the sensors, and updating the navigation system.

[1346] The above system allows new members to quickly adapt to the work environment and reduces emotional stress, enabling them to work more efficiently.

[1347] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1348] Step 1:

[1349] The user (factory manager) logs into the interface and enters interactive questions.

[1350] Input: The user types a question: "How do I maintain my robot?"

[1351] Data processing: The emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[1352] Output: The user's question and emotion data are sent to the system.

[1353] Step 2:

[1354] The server uses generative artificial intelligence to generate answers to questions.

[1355] Input: User questions, collected emotional data, and stored handover information.

[1356] Data Computing: Generative AI uses natural language processing to search for relevant information in a database and generate appropriate answers.

[1357] Output: The server generates an answer and sends it to the user.

[1358] Step 3:

[1359] An emotion engine analyzes the user's emotional state and provides adaptive answers.

[1360] Input: Server-generated answers and user emotional state data.

[1361] Data Calculation: The emotion engine analyzes the user's emotional state and adjusts the tone and content of the response.

[1362] Output: For example, if the user is feeling stressed, an additional message will be displayed: "Relax. We will respond appropriately."

[1363] Step 4:

[1364] Based on the information collected by the server, standardized handover documents are automatically generated.

[1365] Input: Business handover information collected interactively.

[1366] Data processing: The server organizes the collected information in a standardized format and automatically generates consistent handover documents.

[1367] Output: The generated handover document is saved as a file and set up so that other members can access it.

[1368] Step 5:

[1369] Providing quick answers to new members' questions.

[1370] Input: New member's question (e.g., "How do I start the system?").

[1371] Data processing: The server searches the FAQ database and provides an existing answer. If no answer is found, a new answer is generated using generative artificial intelligence.

[1372] Output: Provide an immediate answer to new members.

[1373] The specific actions of each step enable factory managers and new members to carry out their work more efficiently, improving the productivity of the entire system.

[1374] 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.

[1375] 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.

[1376] 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.

[1377] [Fourth embodiment]

[1378] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1379] 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.

[1380] 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).

[1381] 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.

[1382] 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.

[1383] 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).

[1384] 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.

[1385] 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.

[1386] 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.

[1387] 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.

[1388] 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.

[1389] 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.

[1390] 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."

[1391] The "smart handover" system of the present invention is designed to streamline the process of job handover and enable new members to quickly adapt to the job. This system consists of the following main components:

[1392] 1. A method for collecting information on business handover in an interactive format

[1393] Provide an interface for users to enter handover information, for example, existing members answering specific questions such as "What is the current status of the project?"

[1394] The server uses generative artificial intelligence to generate and collect appropriate answers to user questions, interacting with the user using natural language processing to obtain important details about the business.

[1395] 2. A method for automatically generating standardized handover documents based on collected business handover information

[1396] The server consolidates the collected handover information and automatically generates handover documents in a standardized format.

[1397] This handover document is structured so that each member can easily understand it, and clearly states important points of the work and the next tasks to be performed.

[1398] 3. A means of quickly answering questions based on accumulated handover information and a FAQ database

[1399] The server searches the accumulated handover information and FAQ database to quickly answer the new member's questions. For example, if a new member asks, "How do I start the system?", the server will refer to the FAQ database and provide an answer.

[1400] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[1401] Specific examples

[1402] For example, if there is a project that requires handover, the system can be used in the following manner.

[1403] 1. User Procedure

[1404] A user (existing member) logs into the system and enters the question "What is the next task?" through the interface.

[1405] 2. Server Processing

[1406] The server uses generative artificial intelligence to check the progress of current projects from a collected database and respond by listing relevant tasks.

[1407] For example, the generated answer might be, "The next task is to review the design and get it approved by the client."

[1408] 3. Generate handover documents

[1409] Using the information collected interactively, the server automatically generates a comprehensive handover document that includes project status, next tasks, tools to be used, and contact information for everyone involved.

[1410] 4. Answering new member questions

[1411] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If it can't find one, it uses generative artificial intelligence to instantly generate a new answer and provide it.

[1412] By operating this system, new members can quickly adapt to the work, improving the company's work efficiency. In this way, the present invention can realize an effective and efficient work handover.

[1413] The processing flow will be explained below.

[1414] Step 1:

[1415] A user accesses the interface and enters a question to begin collecting handover information, such as "What is the current project status?"

[1416] Step 2:

[1417] The server analyzes the question received from the user and instructs the generative AI to start a dialogue, sending the question content to the generative AI.

[1418] Step 3:

[1419] The server receives the answer received from the generative AI. For example, you can get an answer such as "The current ongoing project is at ~% progress."

[1420] Step 4:

[1421] The server collects these responses and stores them in a database as handover information. The collected information becomes the basis for handover documents.

[1422] Step 5:

[1423] Once the server has collected the answers to all the questions, it automatically generates a standardized handover document based on this information.

[1424] Step 6:

[1425] The server saves the created handover document as a file, and the saved file is set so that other members can access it.

[1426] Step 7:

[1427] The device (the new member's computer or smartphone) accesses the handover document and retrieves the necessary information.

[1428] Step 8:

[1429] A user (new member) inputs a question about the FAQ through the system interface, for example, "How do I start the system?"

[1430] Step 9:

[1431] The server consults the FAQ database to find an existing answer to the question, and if found, provides the answer to the user.

[1432] Step 10:

[1433] If the server does not have a corresponding answer in its FAQ database, it uses generative artificial intelligence to generate a new answer and provides it to the user.

[1434] Step 11:

[1435] Users can check the answers to the provided FAQs and obtain the information they need to do their jobs. This process allows new members to quickly adapt to the job.

[1436] Example 1

[1437] 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."

[1438] The traditional process for handing over work relied on manual information gathering and document creation, making it inefficient and difficult for new members to quickly adapt to the work. Furthermore, the accumulated handover information and FAQ database were not properly utilized, resulting in a disruptive workflow.

[1439] 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.

[1440] In this invention, the server includes a means for allowing a user to interactively collect task handover information through an interface, a means for automatically generating standardized handover documents using a generation AI model based on the collected task handover information, and a means for quickly answering user questions based on the accumulated handover information and FAQ database, thereby enabling efficient task handover and enabling new members to quickly adapt to the tasks.

[1441] A "user" is a person who accesses the system to collect task handover information and input questions.

[1442] An "interface" is a screen or input form that allows a user to interact with a system.

[1443] A "generative AI model" is an artificial intelligence that uses natural language processing technology to generate appropriate answers or documents based on input information.

[1444] A "standardized handover document" is a document created in a unified format based on collected business handover information.

[1445] An "FAQ database" is a database that stores frequently asked questions and their answers.

[1446] The "means for collecting" refers to a function that allows a user to input task handover information through an interface.

[1447] "Means for automatic generation" refers to the ability to create handover documents using a generative AI model based on collected information.

[1448] "Means for quick response" refers to the function of quickly providing answers to users' questions from the accumulated handover information and FAQ database.

[1449] The "smart handover" system of the present invention is designed to streamline the job handover process and allow new members to quickly adapt to the job. This system consists of the following main components:

[1450] 1. A means for users to collect task handover information interactively through an interface

[1451] Users log in to the system and enter task handover information through the interface. For example, an existing member enters a question such as, "What is the next task?"

[1452] The interface is a dashboard accessible through a web browser that allows users to easily enter business questions.

[1453] 2. A method for automatically generating standardized handover documents using a generative AI model based on collected business handover information

[1454] The server uses generative artificial intelligence (generative AI model) to process the collected handover information and automatically generate a handover document in a standardized format, which includes information such as the project's progress, next tasks, tools to be used, and contact information for the members involved.

[1455] As a specific example, a user might ask, "What is the next task?" and the generative AI model might respond, "The next task is to review the design and get it approved by the client," and this information would be reflected in the handover document.

[1456] 3. A means of quickly answering user questions based on accumulated handover information and a FAQ database

[1457] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If no answer is found, it uses a generative AI model to generate a new answer and provides it.

[1458] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[1459] Hardware and software used

[1460] Server: High-performance data processing server

[1461] Generative AI model: An AI model using natural language processing

[1462] User devices: PCs, smartphones, etc.

[1463] Interface: UI accessible through a web browser

[1464] Database: A database that stores business handover information and FAQ information

[1465] Specific examples of operation

[1466] 1. User steps: Log in and type "What's my next task?"

[1467] 2. Server processing: Using the generative AI model, generate an answer, such as "The next task is to review the design and submit it to the client for approval."

[1468] 3. Generate handover documents: Automatically document information collected interactively.

[1469] 4. Answering new member questions: Ask "How do I start the system?" and we'll search our FAQ database to provide an answer, or generate a new answer with our generative AI model.

[1470] In this way, the present invention realizes an efficient work handover, allowing new members to quickly adapt to the work.

[1471] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1472] Step 1: User Login

[1473] The user accesses the interface.

[1474] The user opens a web browser and accesses the URL of the "Smart Handover" system.

[1475] Input: Login URL

[1476] Output: Login screen displayed

[1477] The user enters their login information and logs into the system.

[1478] The user enters their username and password and clicks the "Login" button.

[1479] Input: Username, Password

[1480] Data processing: The server authenticates the entered information

[1481] Output: Authentication result (success or failure), displayed on the main dashboard if successful

[1482] Step 2: Enter and submit your question

[1483] The user types the question in the interface: "What is my next task?"

[1484] A user clicks the "Ask a Question" button from the main dashboard and types "What's my next task?" into the question input field.

[1485] Input: Question (What is the next task?)

[1486] Output: Destination (server) of the query

[1487] The user clicks the "Submit" button.

[1488] Click the "Submit" button to submit the entered question.

[1489] Input: Click on submit button

[1490] Output: Sends the question to the server

[1491] Step 3: Question processing and answer generation

[1492] The server receives a query from a user.

[1493] The server receives the question sent by the user and analyzes its contents.

[1494] Input: User's question

[1495] Data processing: Analysis of questions

[1496] Output: Analysis result (prompt statement)

[1497] The server sends a prompt to the generative AI model.

[1498] The server sends a prompt to the generative AI model: "What is the next task?"

[1499] Input: Analysis result (prompt statement)

[1500] Output: Input to the generative AI model

[1501] A generative AI model generates answers to questions.

[1502] A generative AI model generates an answer based on the prompt.

[1503] Input: prompt statement

[1504] Data Computing: Answer Generation Using Natural Language Processing

[1505] Output: Answer (The next task is to check the design and give it to the client for approval)

[1506] The server receives the generated answer and sends it to the user.

[1507] The answer received from the generative AI model is sent to the user.

[1508] Input: Generated answer

[1509] Output: Response sent to user

[1510] Step 4: Automatic generation of handover documents

[1511] The server organizes the collected dialogue information and generates standardized handover documents.

[1512] Handover documents are automatically generated in a standardized format based on information collected interactively.

[1513] Input: Information collected interactively

[1514] Data processing: organizing information and converting it into a format

[1515] Output: Handover document (project status, next tasks, tools used, contact information of involved people)

[1516] The server stores the generated handover document in a database.

[1517] Store handover documents in a database and make them accessible as needed.

[1518] Input: Handover document

[1519] Output: Save to database

[1520] Step 5: Answer new member questions

[1521] A new member asks from a terminal, "How do I start the system?"

[1522] New members type in their questions on their devices and submit them.

[1523] Input: Question (How do I start the system?)

[1524] Output: Sends the question to the server

[1525] The server searches the FAQ database and extracts existing answers.

[1526] Search our FAQ database to see if your question is answered.

[1527] Input: User's question

[1528] Data Calculation: Search the FAQ database

[1529] Output: Search results (existing answers)

[1530] The server creates a response and sends it to the new member's device.

[1531] It creates an answer based on the search results and sends it to the device, and if an answer is not found, it uses a generative AI model to generate a new answer.

[1532] Input: Search results or Fee burden

[1533] Output: Send the response to the new member

[1534] Through this series of processes, the "smart handover" system realizes efficient job handover and allows new members to quickly adapt to the job.

[1535] (Application example 1)

[1536] 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."

[1537] Traditionally, work handovers have mainly been conducted through face-to-face explanations or information sharing via email, which has resulted in insufficient handover information, making it difficult for new workers to quickly adapt to the work. Furthermore, in the work processes within the factory, if the handover is not carried out properly, problems such as reduced work efficiency can arise. Furthermore, when new workers have questions, they often cannot receive prompt and accurate answers, which often leads to work delays.

[1538] 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.

[1539] In this invention, the server includes means for collecting task handover information interactively, means for automatically generating standardized handover documents based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for converting voice input into text and means for analyzing the handover information using generative artificial intelligence, means for saving the generated handover documents and making them accessible to other members, and means for supporting work processes within the factory. This improves the efficiency of the task handover process, allowing new workers to quickly adapt to the work. Furthermore, efficient and accurate handovers of work processes within the factory are possible, improving work efficiency. Furthermore, when new workers have questions, they can receive prompt and accurate answers, preventing work delays.

[1540] The "means for collecting task handover information in an interactive manner" is a means for providing an interface for collecting task handover information through a dialogue with a user, and for organizing the information in an interactive manner.

[1541] "Means for automatically generating standardized handover documents based on collected business handover information" refers to means for analyzing collected handover information and automatically creating documents in a unified format.

[1542] "Means for quickly answering questions based on accumulated handover information and FAQ database" refers to a means for searching pre-accumulated handover information and FAQ database to quickly provide appropriate answers to questions from users.

[1543] The "means for converting speech input into text" refers to a means for converting information input by speech by a user into text data using natural language processing technology.

[1544] "Means for analyzing handover information using generative artificial intelligence" refers to means for analyzing handover information collected using generative artificial intelligence and extracting necessary information.

[1545] "Means for storing the generated handover documents and making them accessible to other members" means means for storing the automatically generated handover documents in a database so that other members can access, view, and use them at any time.

[1546] "Means to support work processes within the factory" refers to means for monitoring the progress of work within the factory in real time and improving work efficiency by providing appropriate information and work instructions.

[1547] This invention is a system for streamlining task handover in manufacturing sites, which collects task handover information interactively, automatically generates standardized handover documents, and provides quick answers to questions based on accumulated information and an FAQ database. It also includes a function to support work processes within the factory.

[1548] Hardware and software used

[1549] 1. Hardware:

[1550] Work robots: assist with work and collect information within the factory.

[1551] Voice input device: Collects voice information from workers.

[1552] Network connection: Data communication between the server, robot, and terminal.

[1553] 2. Software:

[1554] Python 3.8 or higher: Use as the primary programming language.

[1555] OpenAI GPT-3 model: Used to collect and analyze job handover information, generate handover documents, and answer questions.

[1556] Google Speech-to-Text: Converts voice input into text.

[1557] Process Overview

[1558] 1. Collect handover information:

[1559] The server works in conjunction with a device that converts voice input into text, converting the voice input from the worker into text data. The converted text data is analyzed by generative artificial intelligence (GPT-3) and collected as handover information.

[1560] 2. Generate handover documents:

[1561] The server automatically generates a unified handover document based on the collected handover information, which includes information such as the project status, next steps, tools to be used, and contact information for the people involved.

[1562] 3. Question answering function:

[1563] When a new worker asks a question, the server references the accumulated handover information and FAQ database to provide a quick answer. For questions not in the FAQ database, the server uses the GPT-3 model to generate an appropriate answer and add it to the database.

[1564] 4. Factory support:

[1565] The server monitors and supports the work process in the factory in real time based on the collected handover information, providing the necessary information for specific work steps and improving work efficiency.

[1566] Specific example demo

[1567] For example, imagine a situation where a project is underway in a factory and the next task needs to be handed over. The existing worker asks the robot, "What is the next task?" The voice input through the voice input device is converted into text via Google Speech-to-Text. The server uses generative artificial intelligence to answer this question, saying, "The next task is to check the quality of the parts and perform the assembly process."

[1568] In another scenario, consider a new worker asking, "How do I start the system?" The server searches the FAQ database to find and provide the appropriate answer. If the answer is not in the FAQ database, the server uses the GPT-3 model to generate an answer: "To start the system, power it on, log in, and select the start-up option from the main menu," which is immediately provided to the new worker.

[1569] Example prompt sentence:

[1570] Please tell me the current progress of the project.

[1571] "What's the next task?"

[1572] "How do I start the system?"

[1573] In this way, using this system makes the handover of work more efficient and enables new workers to quickly adapt to the work.

[1574] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1575] Step 1:

[1576] The user (existing worker) inputs handover information to the robot by voice. A voice input device is used for voice input. The input voice data is converted into text data using voice recognition technology (Google Speech-to-Text). This converts the voice data into text format, making it easier to handle in subsequent processes.

[1577] Input: Voice data (questions and information)

[1578] Output: Text data (questions and information)

[1579] Step 2:

[1580] The server sends the text data to a generative artificial intelligence (GPT-3 model) for analysis. The necessary handover information is extracted from the analyzed data. Here, the text data is parsed into a specific format and organized as handover information.

[1581] Input: Text data

[1582] Output: Parsed handover information

[1583] Step 3:

[1584] The server automatically generates standardized handover documents based on the analyzed handover information. Generative AI is used to create documents in a unified format. These documents include project progress, next steps, tools to be used, and contact information for the people involved.

[1585] Input: Parsed handover information

[1586] Output: Standardized handover documents

[1587] Step 4:

[1588] The server saves the generated handover document in a database so that other members can access it. The saved handover document can be accessed by a new worker whenever necessary. This makes it easy to share information between workers.

[1589] Input: Standardized handover documents

[1590] Output: Handover document stored in database

[1591] Step 5:

[1592] When a new worker asks a question, the terminal (robot or computer) sends the question to the server. The server searches the accumulated handover information and FAQ database to provide an appropriate answer. If the FAQ database does not contain a corresponding answer, a new answer is generated using generative artificial intelligence and added to the database.

[1593] Input: New worker question

[1594] Output: The appropriate answer from the server

[1595] Step 6:

[1596] The terminal receives the answer provided by the server and presents it to the new worker. This allows the worker's questions to be resolved quickly and prevents work delays. The answer is displayed in text format or played back aloud.

[1597] Input: Response from the server

[1598] Output: Presents the answer to the new worker

[1599] The above processing steps improve the efficiency of work handover within the factory and create an environment in which new workers can quickly adapt to their work.

[1600] 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.

[1601] The "smart handover" system of the present invention is designed to streamline the task handover process and allow new members to quickly adapt to the task. The present invention can be combined with an emotion engine that recognizes the user's emotions to further improve the user experience. The system consists of the following main components:

[1602] 1. A method for collecting information on business handover in an interactive format

[1603] Provide an interface for users to enter handover information, for example, existing members answering specific questions such as "What is the current status of the project?"

[1604] The server uses generative artificial intelligence to generate and collect appropriate answers to user questions, interacting with the user using natural language processing to obtain important details about the business.

[1605] 2. A method for automatically generating standardized handover documents based on collected business handover information

[1606] The server consolidates the collected handover information and automatically generates handover documents in a standardized format.

[1607] This handover document is structured so that each member can easily understand it, and clearly states important points of the work and the next tasks to be performed.

[1608] 3. A means of quickly answering questions based on accumulated handover information and a FAQ database

[1609] The server searches the accumulated handover information and FAQ database to quickly answer the new member's questions. For example, if a new member asks, "How do I start the system?", the server will refer to the FAQ database and provide an answer.

[1610] The terminal (user's computer or smartphone) can access the answers provided by the server and obtain the necessary information.

[1611] 4. Emotion engine that recognizes user emotions

[1612] The terminal collects the user's emotional data (e.g., facial expressions and voice tone) through the interface.

[1613] The server uses an emotion engine to analyze the collected emotion data and recognize the user's emotional state, which is then used to adjust the tone of the interaction and provide appropriate responses.

[1614] Based on the analysis results of the emotion engine, the server or terminal will take adaptive measures, such as displaying a message encouraging relaxation if the user is feeling stressed.

[1615] Specific examples

[1616] For example, if there is a project that requires handover, the system can be used in the following manner.

[1617] 1. User Input

[1618] A user (existing member) logs in to the system and enters a question through the interface, such as, "What is the next task I should do?" At this time, the emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[1619] 2. Server Processing

[1620] The server uses generative artificial intelligence to check the current project progress from a collected database and respond with a list of related tasks, such as, "The next task is to review the design and get it approved by the client."

[1621] The emotion engine analyzes the user's emotional state and generates responses with appropriate tone and wording.

[1622] 3. Creating and saving handover documents

[1623] The server uses the information collected interactively to automatically generate a comprehensive handover document that includes project status, next tasks, tools to be used, and contact information for everyone involved.

[1624] Save the generated handover document as a file and set it up so that other members can access it.

[1625] 4. Answering questions from new members

[1626] When a new member asks, "How do I start the system?", the server searches the FAQ database and provides an existing answer. If no answer is found, it uses generative artificial intelligence to generate a new answer and provides it.

[1627] 5. Emotion Recognition and Adaptive Responses

[1628] The device will recognize the emotions of the new member from their facial expressions and voice, and if they are feeling stressed, for example, it will display a message saying, "Please relax and continue working."

[1629] By operating this system, new members can quickly adapt to the work, improving the company's work efficiency, and the system also provides a better user experience by enabling adaptive responses based on the user's emotions. In this way, the present invention can achieve effective and efficient work handover.

[1630] The processing flow will be explained below.

[1631] Step 1:

[1632] A user accesses the interface and enters a question to begin collecting handover information, such as "What is the current project status?"

[1633] Step 2:

[1634] The device captures the user's input and sends the collected questions along with the user's facial expressions and tone of voice to the emotion engine.

[1635] Step 3:

[1636] The emotion engine analyzes the user's emotion data and recognizes their emotional state, such as whether they are tense or relaxed.

[1637] Step 4:

[1638] The server sends the question received from the user to the generative AI and instructs it to start a dialogue. At that time, the server also sends the analysis results of the emotion engine along with the question content to the generative AI.

[1639] Step 5:

[1640] The server receives the answer from the generative AI. This answer is provided in an appropriate tone depending on the emotional situation. For example, you might get an answer like "The current ongoing project is at ~% progress."

[1641] Step 6:

[1642] The server collects these responses and stores them in a database as handover information. The collected information becomes the basis for handover documents.

[1643] Step 7:

[1644] Once the server has collected the answers to all the questions, it automatically generates a standardized handover document based on this information.

[1645] Step 8:

[1646] The server saves the created handover document as a file, and the saved file is set so that other members can access it.

[1647] Step 9:

[1648] The device (the new member's computer or smartphone) accesses the handover document and retrieves the necessary information.

[1649] Step 10:

[1650] A user (new member) inputs a question about the FAQ through the system interface, for example, "How do I start the system?"

[1651] Step 11:

[1652] The device sends the user's facial expressions and tone of voice to the emotion engine.

[1653] Step 12:

[1654] The emotion engine analyzes the user's emotion data and recognizes their current emotional state.

[1655] Step 13:

[1656] The server consults the FAQ database to find an existing answer to the question. If found, it provides the answer to the user. The answer is adjusted based on the analysis results from the emotion engine.

[1657] Step 14:

[1658] If the server does not have a corresponding answer in its FAQ database, it uses generative artificial intelligence to generate a new answer and provides it in a tone that corresponds to the analyzed emotional state.

[1659] Step 15:

[1660] Users can check the answers to the provided FAQs to obtain the information they need for their work. Also, if the user is feeling stressed, for example, the system will display a message encouraging relaxation.

[1661] In this way, the present invention not only efficiently collects task handover information and automatically generates standardized handover documents, but also improves the user experience by adaptively responding to the user's emotional state.

[1662] Example 2

[1663] 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."

[1664] The process of business handover presents a challenge for new members, making it difficult for them to quickly adapt to the new work. Furthermore, traditional handover processes often result in poor user experience and a lack of emotional support, which can lead to stress for new members and reduced work efficiency.

[1665] 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.

[1666] In this invention, the server includes means for collecting task handover information in an interactive manner, means for automatically generating a standardized handover document based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for collecting emotion data, and means for analyzing the emotion data and responding adaptively based on the user's emotional state. This not only enables new members to quickly adapt to the task and improves work efficiency, but also enables adaptive responses according to the user's emotions, making it possible to provide a better user experience.

[1667] The "means for collecting task handover information interactively" is a function that allows the user to input questions and answers through an interface and collect the necessary task handover information based on them.

[1668] "Means for automatically generating standardized handover documents based on collected business handover information" refers to a function in which the system organizes collected handover information and automatically creates documents related to business handover according to a specific format.

[1669] "Means for quickly answering questions based on accumulated handover information and FAQ database" refers to a function in which the system searches the handover information and FAQ database that have already been saved and provides immediate answers to questions from users.

[1670] "Means for collecting emotional data" means the ability to capture emotion-related data, such as a user's facial expressions or vocal tone, and enable the system to analyze that data.

[1671] "Means for analyzing emotional data and responding adaptively based on the user's emotional state" refers to a function that analyzes collected emotional data, determines the user's current emotional state, and generates appropriate dialogue and messages accordingly.

[1672] The "smart handover" system of the present invention is designed to streamline task handover and enable new members to adapt to the task in a short period of time. In particular, by incorporating an emotion engine that recognizes the user's emotions, the user experience can be improved. The system includes the following main components:

[1673] A means of collecting information on business handover in an interactive format

[1674] The user inputs task handover information using a dedicated interface. This is done using generative AI (e.g., OpenAI GPT-3) that utilizes natural language processing technology. For example, if the user inputs a question such as "What task should I do next?", the generative AI generates an appropriate answer. At this time, the device also collects emotional data such as the user's facial expressions and tone of voice.

[1675] A method for automatically generating standardized handover documents based on collected business handover information

[1676] The server analyzes the collected handover information and automatically generates handover documents in a standardized format. These documents include the project's progress, next tasks, tools to be used, and contact information for the members involved. The generated documents are saved in cloud storage (e.g., Google Drive or Dropbox) so users can access them at any time.

[1677] A means of quickly answering questions based on accumulated handover information and a FAQ database

[1678] When a new member types a question into the system (e.g., "How do I start the system?"), the server searches the accumulated FAQ database and provides an immediate answer. If necessary, new answers can be generated using generative artificial intelligence.

[1679] Means of collecting emotion data

[1680] The device collects the user's facial expressions and voice tone using a webcam and microphone.

[1681] A means of analyzing emotional data and adaptively responding based on the user's emotional state

[1682] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the collected emotion data. Based on the analysis results, the server or device responds adaptively. For example, if the user is feeling stressed, a message saying "Relax and continue working" is displayed.

[1683] Specific examples

[1684] For example, if there is a project that requires a handover, the system could be used in the following way. First, the user enters a question into the interface: "What is the next task?" The device collects facial expressions and voice tone. The server uses generative artificial intelligence to generate an answer to the question, replying, "The next task is to check the design and get it approved by the client." The emotion engine then analyzes the user's emotional state and adjusts the answer to an appropriate tone. The generated handover document is saved in cloud storage and set up so that other members can easily access it.

[1685] Prompt Sentence Examples

[1686] "What's the next task?"

[1687] Please tell me the progress of your current project.

[1688] "How do I start the system?"

[1689] By operating this system, new members can quickly adapt to the work, improving work efficiency, and it also enables adaptive responses based on user emotions, providing a better user experience, making the work handover process more effective and efficient.

[1690] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1691] Step 1:

[1692] A user logs in to the system.

[1693] Input: User ID and password

[1694] Action: User authentication occurs.

[1695] Output: Authentication successful message is displayed.

[1696] Step 2:

[1697] The user inputs questions about the business handover through the interface.

[1698] Input: Questions like "What's the next task?"

[1699] Action: The question text is sent to the server.

[1700] Output: The question is saved on the server.

[1701] Step 3:

[1702] The device collects the user's emotional data (facial expressions and vocal tone).

[1703] Input: Face image via webcam and voice via microphone

[1704] How it works: Emotion data is captured and sent to a server.

[1705] Output: Emotion data is stored on the server.

[1706] Step 4:

[1707] The server uses generative artificial intelligence (e.g., OpenAI GPT-3) to analyze the entered question and generate an appropriate answer.

[1708] Input: User question text

[1709] Data processing: Perform natural language processing of questions and database searches.

[1710] Output: Answer text: "The next task is to review the design and get it approved by the client."

[1711] Step 5:

[1712] The server uses an emotion engine (e.g., IBM Watson's emotion analysis API) to analyze the collected emotion data.

[1713] Input: User emotion data

[1714] Data Computation: Performs sentiment analysis to determine the user's emotional state.

[1715] Output: The user's emotional state (e.g., feeling stressed) is determined.

[1716] Step 6:

[1717] The server responds adaptively based on the emotional state.

[1718] Input: User's emotional state and answer text

[1719] Data processing: Adjust the tone of the response text.

[1720] Output: Adjusted answer text: "Your next task is to review the design and get it approved by the client. Relax and get going."

[1721] Step 7:

[1722] The terminal displays the adjusted answer text to the user.

[1723] Input: Adjusted answer text

[1724] Behavior: Displays the answer text on the screen.

[1725] Output: The user can check the answer.

[1726] Step 8:

[1727] The server automatically generates standardized handover documents based on the information collected interactively.

[1728] Input: Collected business handover information

[1729] Data processing: Organizing information and generating documents in a specific format.

[1730] Output: Handover documents are generated (e.g., project status, next steps, tools used, contact information for involved people, etc.).

[1731] Step 9:

[1732] The server stores the handover document in cloud storage.

[1733] Input: Generated handover document

[1734] Action: Save file to cloud storage (e.g. Google Drive, Dropbox)

[1735] Output: The handover document is saved to cloud storage and a sharing link is generated.

[1736] Step 10:

[1737] A user (new member) enters a question into the system.

[1738] Input: Questions like "How do I boot my system?"

[1739] Action: The question text is sent to the server.

[1740] Output: The question is saved on the server.

[1741] Step 11:

[1742] The server searches a stored FAQ database and provides existing answers to the question.

[1743] Input: Question text

[1744] Data processing: Searching the FAQ database and extracting matching answers

[1745] Output: Answer text: "To start the system, first press the power button, then enter your ID and password on the login screen."

[1746] Step 12:

[1747] If the server cannot find an appropriate answer, it uses generative artificial intelligence to generate a new answer.

[1748] Input: Question text

[1749] Data processing: Answer generation using generative artificial intelligence

[1750] Output: New answer text (e.g., "To start your system, first press the power button, then enter your ID and password on the login screen.")

[1751] Step 13:

[1752] The device sends the new member's facial expressions and voice to the emotion engine for analysis.

[1753] Input: User emotion data

[1754] Data processing: Emotion data analysis

[1755] Output: User's emotional state

[1756] Step 14:

[1757] The server generates an adaptive message based on the analysis results.

[1758] Input: User's emotional state

[1759] Data processing: Message generation according to emotional state

[1760] Output: "Just relax and get working."

[1761] Step 15:

[1762] The terminal displays the generated message on the screen.

[1763] Input: Message text

[1764] Behavior: Displays a message on the screen.

[1765] Output: The user is helped to acknowledge the message and relax.

[1766] (Application example 2)

[1767] 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."

[1768] Conventional work handover processes have the challenge of making it difficult for new members to quickly adapt to the work. Managing robots in factories, in particular, requires efficient communication of information due to the many detailed operating procedures and precautions required. Furthermore, communication of information can be unclear or emotional stress can arise, leading to reduced productivity and mistakes. To address these issues, a system is needed that allows new members to quickly and effectively adapt to the work environment.

[1769] The specific processing by the specific 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 collecting task handover information in an interactive format, means for automatically generating a standardized handover document based on the collected task handover information, means for quickly answering questions based on the accumulated handover information and an FAQ database, means for analyzing the user's emotional state using an emotion engine, and means for providing an interface operated by the industrial machinery manager. This enables new members to quickly adapt to the work environment and reduces emotional stress.

[1770] The "interactive format" is a format in which the user and the system collect information by exchanging questions and answers.

[1771] "Business handover information" refers to information including the progress of a specific business, the next task to be performed, the tools to be used, and contact information of the members involved.

[1772] A "standardized handover document" is a document that is automatically generated in a consistent and easy-to-understand format based on collected business handover information.

[1773] An "FAQ database" is a database that stores frequently asked questions and their answers.

[1774] An "emotion engine" is software or a system that analyzes emotional data such as a user's facial expressions and tone of voice to recognize the user's emotional state.

[1775] "Industrial machinery" refers to devices such as automated machinery and robots that are primarily used in industrial environments such as factories.

[1776] The "interface operated by the administrator" refers to a graphical user interface (GUI) or command line interface (CLI) intended for use by an administrator of industrial machinery.

[1777] "Generative AI" is an AI technology that automatically generates appropriate answers to questions posed by users in natural language.

[1778] The "smart factory robot handover support system" of this invention is a system that streamlines the handover process for robots working in a factory and allows new members to quickly adapt to the work. The invention is composed of the following main components:

[1779] 1. Gathering information on business handover in an interactive format

[1780] The user (factory manager) inputs handover information through an interactive interface. For example, the factory manager may input a question such as, "How do I maintain a robot?" At this time, the generative AI automatically generates an appropriate answer to the user's question.

[1781] 2. Automatic generation of standardized handover documents based on collected information

[1782] The server processes the collected task handover information in a batch and automatically generates a handover document in a standardized format, which includes the work content, procedures, and important points.

[1783] 3. Quick answers based on accumulated information and FAQ database

[1784] The server refers to the accumulated handover information and FAQ database to quickly provide answers to questions from new members. For example, if a new member asks, "How do I start the system?", the server refers to the FAQ database and provides an answer based on that.

[1785] 4. Use of Emotion Engine

[1786] The terminal collects emotional data (facial expressions and voice tone) through the administrator's interface. The server analyzes this emotional data using an emotion engine to understand the user's emotional state. For example, if the user is feeling stressed, the system displays a message encouraging relaxation. In this way, adaptive responses are made according to the user's emotional state.

[1787] Specific examples

[1788] For example, the following is the flow when a factory manager asks, "How do I maintain a robot?"

[1789] 1. User Input

[1790] A factory manager logs into the interface and types a question such as, "How do I maintain the robot?" At this time, the emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[1791] 2. Server Processing

[1792] The server uses generative artificial intelligence to search the database for relevant handover information and generate an appropriate answer, such as, "The robot's scheduled maintenance is performed every Monday. This includes checking the battery, calibrating the sensors, and updating the navigation system."

[1793] The emotion engine also analyzes the user's emotional state and provides responses in an appropriate tone and language. If the user is feeling stressed, the message displayed will be, "Please relax. We will respond appropriately."

[1794] 3. Automatic generation and storage of handover documents

[1795] Based on the information collected interactively, the server automatically generates comprehensive handover documents, including robot maintenance methods, work procedures, and important points, and stores them in a format that can be accessed by other team members.

[1796] An example of a prompt is as follows:

[1797] Q: How do I maintain my robot?

[1798] Answer: Routine maintenance of the robot is performed every Monday, which includes checking the battery, calibrating the sensors, and updating the navigation system.

[1799] The above system allows new members to quickly adapt to the work environment and reduces emotional stress, enabling them to work more efficiently.

[1800] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1801] Step 1:

[1802] The user (factory manager) logs into the interface and enters interactive questions.

[1803] Input: The user types a question: "How do I maintain my robot?"

[1804] Data processing: The emotion engine analyzes the user's facial expressions and voice to collect emotional data.

[1805] Output: The user's question and emotion data are sent to the system.

[1806] Step 2:

[1807] The server uses generative artificial intelligence to generate answers to questions.

[1808] Input: User questions, collected emotional data, and stored handover information.

[1809] Data Computing: Generative AI uses natural language processing to search for relevant information in a database and generate appropriate answers.

[1810] Output: The server generates an answer and sends it to the user.

[1811] Step 3:

[1812] An emotion engine analyzes the user's emotional state and provides adaptive answers.

[1813] Input: Server-generated answers and user emotional state data.

[1814] Data Calculation: The emotion engine analyzes the user's emotional state and adjusts the tone and content of the response.

[1815] Output: For example, if the user is feeling stressed, an additional message will be displayed: "Relax. We will respond appropriately."

[1816] Step 4:

[1817] Based on the information collected by the server, standardized handover documents are automatically generated.

[1818] Input: Business handover information collected interactively.

[1819] Data processing: The server organizes the collected information in a standardized format and automatically generates consistent handover documents.

[1820] Output: The generated handover document is saved as a file and set up so that other members can access it.

[1821] Step 5:

[1822] Providing quick answers to new members' questions.

[1823] Input: New member's question (e.g., "How do I start the system?").

[1824] Data processing: The server searches the FAQ database and provides an existing answer. If no answer is found, a new answer is generated using generative artificial intelligence.

[1825] Output: Provide an immediate answer to new members.

[1826] The specific actions of each step enable factory managers and new members to carry out their work more efficiently, improving the productivity of the entire system.

[1827] 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.

[1828] 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.

[1829] 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.

[1830] 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.

[1831] 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.

[1832] 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.

[1833] 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).

[1834] 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.

[1835] 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."

[1836] 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.

[1837] 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).

[1838] 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.

[1839] 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.

[1840] 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.

[1841] 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.

[1842] 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.

[1843] 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.

[1844] 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.

[1845] 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.

[1846] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1847] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1848] The following is further disclosed regarding the above embodiment.

[1849] (Claim 1)

[1850] A means of collecting business handover information in an interactive format;

[1851] A means for automatically generating a standardized handover document based on the collected business handover information;

[1852] A means of quickly answering questions based on accumulated handover information and a FAQ database,

[1853] A system including:

[1854] (Claim 2)

[1855] 2. The system according to claim 1, wherein the means for collecting task handover information in an interactive manner uses generative artificial intelligence.

[1856] (Claim 3)

[1857] 10. The system of claim 1, further comprising means for storing the collected business handover information and making it accessible to other members.

[1858] "Example 1"

[1859] (Claim 1)

[1860] A means for a user to interactively collect task handover information through an interface;

[1861] A means for automatically generating standardized handover documents using a generative AI model based on the collected business handover information;

[1862] A means of quickly answering user questions based on accumulated handover information and a FAQ database;

[1863] A system including:

[1864] (Claim 2)

[1865] 2. The system of claim 1, wherein the means for collecting task handover information interactively uses generative artificial intelligence and prompt sentences.

[1866] (Claim 3)

[1867] 2. The system according to claim 1, further comprising means for storing the collected business handover information and the automatically generated handover document and making them accessible to other members.

[1868] "Application Example 1"

[1869] (Claim 1)

[1870] A means of collecting business handover information in an interactive format;

[1871] A means for automatically generating a standardized handover document based on the collected business handover information;

[1872] A means of quickly answering questions based on accumulated handover information and a FAQ database,

[1873] A means for converting voice input into text and a means for analyzing handover information using generative artificial intelligence;

[1874] A means for storing the generated handover document and making it accessible to other members;

[1875] means of supporting work processes within the factory;

[1876] A system including:

[1877] (Claim 2)

[1878] 2. The system according to claim 1, wherein the means for collecting task handover information in an interactive manner uses generative artificial intelligence.

[1879] (Claim 3)

[1880] 10. The system of claim 1, further comprising means for storing the collected business handover information and making it accessible to other members.

[1881] "Example 2: Combining Emotion Engines"

[1882] (Claim 1)

[1883] A means of collecting business handover information in an interactive format;

[1884] A means for automatically generating a standardized handover document based on the collected business handover information;

[1885] A means of quickly answering questions based on accumulated handover information and a FAQ database,

[1886] a means for collecting emotion data;

[1887] means for analyzing the emotional data and adaptively responding based on the emotional state of the user;

[1888] A system including:

[1889] (Claim 2)

[1890] 2. The system according to claim 1, wherein the means for collecting task handover information in an interactive manner uses generative artificial intelligence.

[1891] (Claim 3)

[1892] 10. The system of claim 1, further comprising means for storing the collected business handover information and making it accessible to other members.

[1893] "Application example 2 when combining emotion engines"

[1894] (Claim 1)

[1895] A means of collecting business handover information in an interactive format;

[1896] A means for automatically generating a standardized handover document based on the collected business handover information;

[1897] A means of quickly answering questions based on accumulated handover information and a FAQ database,

[1898] means for analyzing a user's emotional state using an emotion engine;

[1899] means for providing an interface operated by an industrial machine manager;

[1900] A system including:

[1901] (Claim 2)

[1902] 2. The system according to claim 1, wherein the means for collecting task handover information in an interactive manner uses generative artificial intelligence.

[1903] (Claim 3)

[1904] 10. The system of claim 1, further comprising means for storing the collected business handover information and making it accessible to other members. [Explanation of symbols]

[1905] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of collecting business handover information in an interactive format; A means for automatically generating a standardized handover document based on the collected business handover information; A means of quickly answering questions based on accumulated handover information and a FAQ database, A system including:

2. 2. The system according to claim 1, wherein the means for collecting task handover information in an interactive manner uses generative artificial intelligence.

3. 2. The system of claim 1, further comprising means for storing the collected business handover information and making it accessible to other members.

Images