system

Abstract

We provide the system. [Solution] A means of automating business procedures using generative artificial intelligence, A means of saving user-entered data to a database, A means by which artificial intelligence analyzes data stored in a database to generate business procedures and executes them, A means of notifying the user of the results performed by the generative artificial intelligence, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In conventional industries such as the construction industry, analog operations are numerous, and it is common for people to directly carry out operations on a PC. In such a situation, manual errors, operation delays, and the complexity of inquiry responses occur. In particular, when multiple cooperating companies are involved, it is difficult to share information and unify business procedures, and efficient operation is often hindered. In addition, a quick and accurate response to inquiries from the site is required, but it is difficult to respond with the current system. Therefore, there is a demand for a system that solves these problems and realizes digitalization and automation of business processes.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides the following means: means for automating business procedures using generative artificial intelligence; means for saving user-input data to a database; means for the generative artificial intelligence to execute business procedures by analyzing the data stored in the database; and means for notifying the user of the results executed by the generative artificial intelligence. The invention also provides a system that includes means for users to input business data using a terminal; means for making inquiries from the field using a terminal; means for a server to analyze the inquiry content using generative artificial intelligence and generate an answer; and means for displaying the generated answer on the user's terminal. Furthermore, the invention provides a system that includes means for providing a business flow setting screen; means for saving the set business flow to a database; and means for users to check and modify the business flow stored in the database using a terminal. This enables the digitalization and automation of business flows and quick and accurate inquiry response.

[0006] "Generative artificial intelligence" is an artificial intelligence technology that automatically learns, analyzes, and executes tasks such as business procedures and customer support.

[0007] A "business procedure" refers to a series of steps or operations necessary to complete a specific task or process.

[0008] A "database" is an information storage system that organizes and stores data, making it possible to search and edit it efficiently.

[0009] "Users" refer to all individuals who utilize the system, including field workers, administrators, and operators.

[0010] A "terminal" refers to an electronic device used by a user, such as a PC or smart device.

[0011] A "server" is a central control unit that stores and manages data and communicates with terminals and other systems.

[0012] "Automation" refers to a function where a system performs tasks based on its own judgment, without requiring human manual work.

[0013] An "input form" is an electronic format used by users to enter data.

[0014] A "notification" is a means by which a system communicates specific information or results to a user.

[0015] An "inquiry" refers to a question asked by a field worker to resolve doubts or problems regarding the system or work procedures.

[0016] "Generated answers" refer to answer information created by the generative artificial intelligence based on the analysis results.

[0017] The "business process settings screen" is an interface that allows users to check and modify business procedures.

[0018] "Analysis" is the process of finding meaning and relationships in information based on input data and making judgments.

[0019] "The site" primarily refers to a place where physical work, such as in the construction industry, is carried out.

[0020] "Real-time" refers to a state in which data and information are processed and displayed instantly without delay. [Brief explanation of the drawing]

[0021] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4]It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0022] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0023] First, the terms used in the following description will be explained.

[0024] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0025] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0026] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0027] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0028] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0029] [First Embodiment]

[0030] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0031] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0032] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0033] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0034] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0035] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0036] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0037] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0039] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0040] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0041] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0042] This invention is a system that digitizes and automates the workflows of industries with many analog operations, such as the construction industry. This system has the function of automating work procedures using generative artificial intelligence, the function of saving and analyzing user-entered data in a database, and the function of responding quickly and accurately to inquiries from the field.

[0043] System configuration and operation

[0044] Digitalization and automation of business processes

[0045] Server: This server plays a central role in this system. It incorporates a database for storing and managing business procedures. The server receives business data sent by users and stores it in the database. It also uses generative artificial intelligence to execute automated tasks based on business procedures and notifies users of the results.

[0046] Terminal: A device (e.g., PC or smart device) used by users to input, verify, and modify business data. Data entered on the terminal is sent to the server in real time, where it is analyzed and processed.

[0047] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[0048] Responding to inquiries from the field.

[0049] Server: Receives the inquiry content and analyzes it using a generation AI. Generates an appropriate answer from the analysis results and saves that answer in the database. The generated answer is notified to the user in real time.

[0050] Terminal: This is the device on which the user enters and submits their inquiry. It displays the response sent from the server.

[0051] User: Inputs and sends inquiries from the field using a terminal, and checks the generated response.

[0052] Specific examples of operation

[0053] Setting up business workflows

[0054] Users access the workflow settings screen using their PCs. For example, they can configure business processes such as "order management," "inventory check," and "delivery management."

[0055] The server saves these settings to the database.

[0056] The terminal displays the workflow configured by the user and allows them to modify it as needed.

[0057] Data entry and automation

[0058] The user uses a terminal to enter order information into the "Order Management" screen. For example, they might enter the product code, quantity, delivery date, etc.

[0059] The terminal sends the entered information to the server.

[0060] The server stores order information in a database and uses AI to automatically check inventory and place necessary orders. The results are stored in the database and notified to the user.

[0061] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[0062] Inquiry response

[0063] Users input inquiries from the field using a terminal and send questions, for example, about "today's work procedures."

[0064] The terminal sends the inquiry details to the server.

[0065] The server uses generation AI to analyze the inquiry and generate an appropriate response. For example, it can provide instructions for work procedures or answers to related FAQs.

[0066] The responses generated by the server are stored in a database and notified to the user in real time.

[0067] The user checks the answers displayed on the device and incorporates that information into their work.

[0068] This system digitizes and automates business processes using the procedures described above, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[0069] The following describes the processing flow.

[0070] Program processing

[0071] Digitalization and automation of business processes

[0072] Step 1: Setting up the business workflow

[0073] User: Access the workflow settings screen using a PC and configure workflows such as "Order Management," "Inventory Check," and "Delivery Management."

[0074] Terminal: Sends information about the configured workflow to the server.

[0075] Server: Saves the received business flow information to the database.

[0076] Step 2: Data Entry

[0077] User: Use your device to enter information into the "Order Management" screen (e.g., product code, quantity, delivery date).

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

[0079] Server: Stores order information in the database.

[0080] Step 3: Processing by Generator AI

[0081] Server: Receives data from the database and passes it to the AI ​​for inventory checks and ordering instructions.

[0082] Server: Saves the processing results of the generated AI (inventory check results and order details) to the database.

[0083] Server: Notifies the user's terminal of the processing results.

[0084] Step 4: Review the results and take appropriate action.

[0085] User: Check the processing results notified on the device and make corrections or approvals as necessary.

[0086] Terminal: Sends user modifications and approvals to the server.

[0087] Server: Reflects changes and approvals in the database.

[0088] Responding to inquiries from the field.

[0089] Step 1: Enter your inquiry

[0090] User: Enter the inquiry details from the field into the terminal and send it (e.g., "I don't know today's work procedure").

[0091] Terminal: Sends the inquiry details to the server.

[0092] Step 2: Inquiry Analysis

[0093] Server: Uses generation AI to analyze inquiry content and extract and generate relevant answers and information.

[0094] Server: Saves the generated responses to the database.

[0095] Step 3: Provide your response

[0096] Server: Sends the answers stored in the database to the user's terminal.

[0097] Terminal: Displays the answer to the inquiry.

[0098] User: Review the displayed answer and proceed with the task.

[0099] Specific example

[0100] Step 1: Setting up the business workflow

[0101] User: The construction site manager logs into the system on their PC and sets up workflows such as "order management," "inventory check," and "delivery management."

[0102] Terminal: Sends configuration information to the server.

[0103] Server: Saves the received data to the database.

[0104] Step 2: Data Entry

[0105] User: The sales representative enters information about a new order into the "Order Management" screen on their terminal.

[0106] Terminal: Sends input data to the server.

[0107] Server: Stores order information in the database.

[0108] Step 3: Processing by Generator AI

[0109] Server: The generation AI checks inventory based on order information and automatically places orders according to the required quantity.

[0110] Server: Saves the results (inventory check and order details) generated by the AI ​​and notifies the user of these results.

[0111] Step 4: Review the results and take appropriate action.

[0112] User: The site manager reviews the results and verifies whether the order details are correct.

[0113] Terminal: Sends user confirmation details to the server.

[0114] Server: Reflect the verification results in the database.

[0115] Examples of how to handle inquiries

[0116] Step 1: Enter your inquiry

[0117] User: Field workers enter their questions about today's work procedures into the terminal and send them.

[0118] Terminal: Sends the inquiry details to the server.

[0119] Step 2: Inquiry Analysis

[0120] Server: The AI ​​generates responses by analyzing the inquiry and producing answers such as, "Today, we will proceed with the work according to the following steps."

[0121] Server: Saves the generated responses to the database.

[0122] Step 3: Provide your response

[0123] Server: Sends the generated response to the user's device.

[0124] Terminal: Displays the answer to the inquiry.

[0125] User: Review the answer and proceed with the task.

[0126] This system enables the digitalization and automation of business processes, as well as providing quick and accurate responses to inquiries from the field.

[0127] (Example 1)

[0128] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0129] Currently, many industries are demanding the digitalization and automation of business procedures, but the labor of field workers and managers, as well as errors caused by manual processes, remain major problems. Furthermore, there are challenges in responding quickly and accurately to inquiries. In particular, industries with many analog operations, such as construction, require increased efficiency in workflows and reduced errors, but achieving this presents significant cost and technical hurdles.

[0130] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0131] This invention includes a server that includes means for automating business procedures using generative artificial intelligence, means for saving user-input data to a database, and means for the generative artificial intelligence to execute business procedures by analyzing the data stored in the database. This enables automation and efficiency of business procedures. It also includes means for the user to input business data using a terminal, means for making inquiries from the field using a terminal, means for the server to analyze the inquiry content using generative artificial intelligence and generate an answer, and means for displaying the generated answer on the user's terminal. This enables a quick and accurate response to inquiries. It also includes means for the user to operate a business flow setting screen via a terminal, means for saving the business flow settings to a database, means for the user to check and modify the saved business flow on a terminal, and means for the business data stored in the database to be sent to the server in real time. This enables easy setting and updating of business flows. It also includes means for the server to automatically perform inventory checks and orders using a generative AI model based on the business data received, means for notifying the user of the generated inventory check and order results, and means for the user to check the notified results and make corrections or approvals as necessary. This achieves efficiency and accuracy in inventory management and ordering operations.

[0132] "Generative artificial intelligence" refers to systems that use machine learning and natural language processing technologies to perform intelligent tasks like humans.

[0133] "Automating business procedures" refers to automatically executing business processes that were previously performed manually, using systems and software.

[0134] A "database" refers to a system for efficiently storing, managing, and retrieving large amounts of data.

[0135] "User" refers to a person who uses this system to input business data, make inquiries, and check the results, or a person with a similar role.

[0136] "Terminal" refers to a hardware device used by a user (e.g., PC, smartphone, tablet).

[0137] A "server" refers to a computer system that plays a central role in storing, managing, and analyzing data, and connecting users and their devices.

[0138] "Inquiry" refers to a question that a user asks via their device to resolve doubts or uncertainties regarding the field or the performance of their work.

[0139] "Answer" refers to information or solutions generated by the server using artificial intelligence and provided to the user.

[0140] The "settings screen" refers to the interface that allows users to configure and modify business workflows and processes.

[0141] "Inventory check" refers to verifying the current inventory status based on inventory information stored in a database.

[0142] "Placement" refers to the business process of ordering necessary goods or materials from suppliers.

[0143] "Notification" refers to the real-time transmission of results or responses generated by the server to the user.

[0144] This invention is a system that digitizes and automates the workflows of industries with many analog operations, such as the construction industry. This system has the function of automating work procedures using generative artificial intelligence, the function of saving and analyzing user-entered data in a database, and the function of responding quickly and accurately to inquiries from the field.

[0145] System configuration and operation

[0146] Digitalization and automation of business processes

[0147] 1. Server

[0148] The server plays a central role in this system. This server incorporates a database (e.g., MySQL®) for storing and managing business procedures. The server receives business data sent by users and stores it in the database. It also uses generative artificial intelligence (e.g., GPT-4®) to execute automated tasks based on business procedures and notifies the user of the results.

[0149] 2. Terminal

[0150] A terminal is a device used by users to input, verify, and modify business data. Typically, a PC or smart device is used. Data entered on the terminal is transmitted to the server in real time, where it is analyzed and processed.

[0151] 3. User

[0152] Users are field workers or managers who input, verify, and modify business data through terminals. For example, a user might use a PC to input product codes, quantities, and delivery dates on the "Order Management" screen. This data is sent to the server via the terminal, where automated tasks are executed.

[0153] Responding to inquiries from the field.

[0154] 1. User

[0155] Users input inquiries from the field using their devices (PCs, smartphones, etc.). For example, they might input a question like, "What should I do if there is insufficient stock?"

[0156] 2. Terminal

[0157] The terminal sends the inquiry to the server and displays the response sent from the server.

[0158] 3. Server

[0159] The server receives the inquiry and analyzes the content using a generative AI model (e.g., GPT-4). It generates an appropriate response from the analysis results and saves it to a database. The generated response is notified to the user in real time. For example, a response such as "If inventory is low, an additional order is required" might be provided.

[0160] Specific example of the operation flow

[0161] 1. Setting up the business workflow

[0162] Users access the workflow settings screen using their PCs and configure business processes such as "order management," "inventory check," and "delivery management."

[0163] The server saves these settings to the database.

[0164] The terminal displays the workflow configured by the user and allows them to modify it as needed.

[0165] 2. Data entry and automation

[0166] The user enters order information into the "Order Management" screen using their device. For example, they might enter the product code, quantity, and delivery date.

[0167] The terminal sends the entered information to the server.

[0168] The server saves order information to a database and uses AI to automatically check inventory and place necessary orders. The results are saved in the database and notified to the user.

[0169] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[0170] 3. Handling inquiries

[0171] Users input inquiries from the field using a terminal and send questions, for example, about "today's work procedures."

[0172] The terminal sends the inquiry details to the server.

[0173] The server uses AI to analyze the inquiry and generate an appropriate response. For example, it may provide instructions on how to perform tasks or answers to related FAQs.

[0174] The responses generated by the server are stored in a database and notified to the user in real time.

[0175] The user reviews the answers displayed on their device and incorporates that information into their work.

[0176] Example of a prompt

[0177] "Product code: ABC123, Quantity: 10, Delivery date: 2023-10-15. Please check inventory and process the order for this item."

[0178] "Please tell me today's work procedure."

[0179] As a result, this system digitizes and automates business processes, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[0180] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0181] Step 1:

[0182] The user enters business data using a terminal. For example, they enter the product code, quantity, and delivery date. Specifically, the entered data is product code "ABC123", quantity "10", and delivery date "2023-10-15".

[0183] input:

[0184] Product code, quantity, delivery date

[0185] output:

[0186] Input data displayed on the terminal

[0187] Step 2:

[0188] The terminal sends the entered business data to the server. The data is sent to the server as an HTTP POST request. Specifically, the data sent from the terminal includes the product code "ABC123", quantity "10", and delivery date "2023-10-15".

[0189] input:

[0190] Business data entered into the terminal

[0191] output:

[0192] Business data sent to the server

[0193] Step 3:

[0194] The server analyzes the received business data and saves it to the database. Specifically, the server saves the product code "ABC123", quantity "10", and delivery date "2023-10-15" to the MySQL database.

[0195] input:

[0196] Business data sent to the server

[0197] output:

[0198] Business data stored in the database

[0199] Step 4:

[0200] The server uses a generated AI model (e.g., GPT-4) based on the stored data to check inventory and automatically place necessary orders. For example, the AI ​​model might determine that "there are 50 units in stock, so no additional orders are needed."

[0201] input:

[0202] Business data stored in the database

[0203] Inventory data required by the generative AI model

[0204] output:

[0205] The decision was made that an order is not necessary.

[0206] Step 5:

[0207] The server saves the results of tasks automated by the generated AI model to a database and notifies the user of those results. For example, a notification such as "Inventory check results indicate no additional orders are needed" is sent via email or system notification.

[0208] input:

[0209] Inventory check results

[0210] output:

[0211] Results notified to the user

[0212] Step 6:

[0213] The user checks the notification results using their device. If necessary, they can modify or approve the results on the system screen. For example, the user might check a notification on their smartphone stating "No additional order is needed" and approve it without making any changes.

[0214] input:

[0215] Notified results

[0216] output:

[0217] User verification and modification / approval results

[0218] Step 7:

[0219] Users input inquiries from the field using a terminal. For example, they might input a question like, "What are today's work procedures?"

[0220] input:

[0221] Inquiry details

[0222] output:

[0223] Inquiry content displayed on the device

[0224] Step 8:

[0225] The terminal sends the inquiry details to the server. The data is sent to the server as an HTTP POST request.

[0226] input:

[0227] Inquiry content entered on the terminal

[0228] output:

[0229] Inquiry content sent to the server

[0230] Step 9:

[0231] The server receives the inquiry and analyzes the content using a generation AI model. An appropriate answer is generated from the analysis results. For example, the AI ​​model might generate the answer: "Today's work procedure is as follows: 1. Arrive at the site 2. Prepare equipment 3. Begin work."

[0232] input:

[0233] Inquiry content sent to the server

[0234] Business procedure data required by the generated AI model

[0235] output:

[0236] Generated answer

[0237] Step 10:

[0238] The server saves the generated response to a database and notifies the user in real time. For example, the response might say, "Today's work procedure is as follows."

[0239] input:

[0240] Generated answer

[0241] output:

[0242] Responses notified to the user

[0243] Step 11:

[0244] The user checks the answers displayed on the device and incorporates that information into their work. For example, they might start on-site work following the work procedure displayed on the device.

[0245] input:

[0246] Notified response

[0247] output:

[0248] Tasks performed by the user

[0249] As a result, this system digitizes and automates business processes, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[0250] (Application Example 1)

[0251] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0252] In existing factory operations, work procedures and workflows are often managed manually, resulting in insufficient efficiency and automation. This leads to problems such as manual errors, wasted time, and delays in responding to inquiries, ultimately reducing productivity and quality. The objective of this invention is to solve these problems and realize the digitalization and automation of workflows.

[0253] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0254] In this invention, the server includes means for automating work procedures using generative artificial intelligence, means for storing user-input data in a database, means for transmitting data to the server in real time, means for optimizing work procedures using generative AI, and means for automating operations on a factory production line. This enables more efficient workflows, reduced errors, and faster response times to inquiries.

[0255] "Generative artificial intelligence" is an advanced artificial intelligence technology used to automate business procedures, analyze data, and generate appropriate responses.

[0256] A "database" is a digital information repository where information such as business data, workflows, and inquiry details are centrally managed and stored and analyzed as needed.

[0257] "A means of sending data to a server in real time" refers to a system configuration that instantly sends data entered by a user to a server, enabling immediate processing and analysis of the data.

[0258] "Generative AI" is a type of artificial intelligence technology that automatically provides appropriate responses and optimizes work procedures based on user questions and data.

[0259] "Methods for optimizing work procedures" refers to technologies that use generative AI to automatically plan and propose efficient and error-free work procedures.

[0260] "Methods for automating factory production line operations" refer to systems in which robots and automated equipment perform production activities without human intervention, based on business flows and work procedures stored in a database.

[0261] "Users" refer to people such as field workers and managers who input and verify business data and use the system to perform their duties.

[0262] A "terminal" is a device used by users to input, verify, and modify business data, and includes PCs and smartphones.

[0263] A "server" is a computer system that plays a central role in this system, comprehensively managing data storage and analysis, execution of generating AI, and notification of results.

[0264] This invention is a system aimed at automating and digitizing work procedures and workflows in factories. This system stores user-inputted data in a database, and based on that data, generative artificial intelligence (generative AI) optimizes and automatically executes work procedures. It also includes means for sharing work procedures with robots within the factory and for quickly responding to inquiries from the factory floor.

[0265] Hardware and software configuration

[0266] server

[0267] The server plays a central role in the system. It performs the following functions:

[0268] Data Storage: User-entered data is saved to a database. SQLite is used as the database.

[0269] Data Analysis: Analyze data stored in the database and optimize work procedures using generative AI. OpenAI's GPT-3® is used for generative AI.

[0270] Result Notification: Notifies the user of the results generated by the AI.

[0271] terminal

[0272] A terminal is a device used by users to input, verify, and modify business data. It has the following functions:

[0273] Data entry: Provide a screen for entering business data. This could be a smartphone or computer, for example.

[0274] Inquiry Submission: A function that allows users to input inquiries from the field and send them to the server.

[0275] Results display: Displays notifications from the server and responses generated by the AI ​​in real time.

[0276] robot

[0277] The robots in the factory are responsible for automatically performing tasks based on work procedures shared from a server. The robots perform the following functions:

[0278] Task Execution: Perform tasks on the production line according to the specified work procedures.

[0279] Data transmission: Sends the progress of the work to the server in real time.

[0280] Specific examples of actions

[0281] Setting up business workflows

[0282] 1. The user accesses the business process setting screen using a smartphone. For example, set business processes such as "order management", "inventory confirmation", and "delivery management".

[0283] 2. The server saves these settings in the database.

[0284] Data Input and Automation

[0285] 1. The user uses the terminal to input order information on the "order management" screen. For example, input information such as product code, quantity, delivery date, etc.

[0286] 2. The terminal sends the input information to the server.

[0287] 3. The server saves the order information in the database and automatically performs inventory confirmation and necessary ordering using the generative AI.

[0288] 4. The server saves the result in the database and notifies the user.

[0289] 5. The user checks the notified result on the terminal and makes corrections or approvals as necessary.

[0290] [[ID=3�]] Inquiry Response

[0291] 1. The user inputs an inquiry from the site using the terminal and sends, for example, "today's work procedure".

[0292] 2. The terminal sends the inquiry content to the server.

[0293] 3. The server analyzes the inquiry content using the generative AI and generates an appropriate answer. For example, provide a guide to the work procedure and answers to related FAQs.

[0294] 4. The server saves the generated answer in the database and notifies the user in real time.

[0295] 5. The user checks the answer displayed on the terminal and reflects its content in the work.

[0296] Examples of prompt sentences

[0297] Work process:

[0298] Order registration of goods

[0299] Inventory check

[0300] Order arrangement

[0301] Delivery preparation

[0302] Question: Please tell me today's work procedure.

[0303] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0304] Step 1:

[0305] The user accesses the business process setting screen using a smartphone. The user sets business processes such as "order management", "inventory check", and "delivery management".

[0306] Input: Settings of business process (e.g., order management, inventory check, delivery management)

[0307] Action: Input of content on the business process setting screen

[0308] Output: Data of the set business process <>

[0309] Step 2:

[0310] The server saves the settings input by the user in the database.

[0311] Input: Data from the configured business flow

[0312] Operation: Saving flow configuration data to the database

[0313] Output: Saved business flow data

[0314] Step 3:

[0315] The user uses a terminal to enter order information into the "Order Management" screen. For example, they enter information such as product code, quantity, and delivery date.

[0316] Input: Order information (product code, quantity, delivery date, etc.)

[0317] Operation: Entering order information on the screen

[0318] Output: Input order data

[0319] Step 4:

[0320] The terminal sends the entered information to the server.

[0321] Input: Entered order data

[0322] Operation: Sending data to the server

[0323] Output: Order data received by the server

[0324] Step 5:

[0325] The server stores order information in a database and uses AI generation to automatically check inventory and place necessary orders.

[0326] Input: Order data received by the server

[0327] Operation: Saves order information to the database and uses AI to check inventory and automatically place orders.

[0328] Output: Inventory status, order placement information

[0329] Step 6:

[0330] The server saves the results to the database and notifies the user.

[0331] Input: Inventory status, order placement information

[0332] Operation: Save results to a database and notify the user.

[0333] Output: Processing results notified to the user

[0334] Step 7:

[0335] Users can check the notified results on their devices and make corrections or approvals as needed.

[0336] Input: Processing result notified to the user

[0337] Action: Review results, make necessary corrections and approvals.

[0338] Output: Corrected and approved data

[0339] Step 8:

[0340] Users input inquiries from the field using a terminal and send, for example, "Today's work procedure."

[0341] Input: Inquiry details (e.g., "Today's work procedure")

[0342] Operation: Input and send inquiry content to the terminal.

[0343] Output: Query content sent to the server

[0344] Step 9:

[0345] The server uses a generation AI to analyze the inquiry and generate an appropriate response.

[0346] Input: Inquiry received by the server

[0347] Operation: Analysis of inquiry content and generation of answers using a generation AI.

[0348] Output: Generated answer

[0349] Step 10:

[0350] The server saves the generated responses to a database and notifies the user in real time.

[0351] Input: Generated answer

[0352] Operation: Saves responses to the database and provides real-time notifications to users.

[0353] Output: Response notified to the user

[0354] Step 11:

[0355] The user checks the answers displayed on their device and incorporates that information into their work.

[0356] Input: Response notified to the user

[0357] Action: Confirmation of notified responses and implementation of the work.

[0358] Output: Results of the work

[0359] This enables the efficient execution of a series of processes and achieves the automation and digitalization of the workflow and work procedures within the factory.

[0360] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0361] This invention relates to a system for digitizing and automating business workflows by combining an emotion engine. This system uses generative artificial intelligence to automate business procedures and leverages user emotion data to provide more appropriate and effective support.

[0362] System configuration and operation

[0363] Digitalization and automation of business processes

[0364] Server: This server plays a central role in this system. It incorporates a database for storing work procedures, generative artificial intelligence, and an emotion engine for analyzing user sentiment data. The server receives work data sent by users and stores it in the database. It also uses generative artificial intelligence to execute automated tasks based on work procedures and notifies the user of the results.

[0365] Terminal: A device (e.g., PC or smart device) used by users to input, verify, and modify business data. Data entered on the terminal is sent to the server in real time, where it is analyzed and processed. In addition, user emotional data is collected in conjunction with the emotion engine.

[0366] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[0367] Collection and analysis of emotional data

[0368] Server: The emotion engine collects emotional data from the user's facial expressions, voice, and language use, and analyzes this data. The analysis results are fed back to the generating AI and used to adjust work procedures and the content of responses to inquiries.

[0369] Terminal: Along with the business data entered by the user, the emotion engine sends collected emotion data to the server. The user's emotion data is analyzed in real time, and the results are reflected in the progress of the work.

[0370] Specific examples of operation

[0371] Setting up business workflows

[0372] Users access a workflow configuration screen using their PCs and set up processes such as "order management," "inventory check," and "delivery management."

[0373] The terminal sends information about the configured workflow to the server.

[0374] The server saves the received business flow information to the database.

[0375] Data entry and automation

[0376] The user enters information into the "Order Management" screen using their device (e.g., product code, quantity, delivery date).

[0377] The device sends the entered information to the server. Simultaneously, the emotion engine collects the user's emotional data.

[0378] The server stores order information and sentiment data in a database and uses a generating AI to check inventory and issue ordering instructions. The results are stored in the database and notified to the user.

[0379] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[0380] Use of emotional data

[0381] Server: Based on the user's emotional data analyzed by the emotion engine, the generating AI adjusts the work procedures and responses. For example, if a user is feeling stressed, it can suggest simplifying the operation.

[0382] Device: By displaying emotional data in real time while the user is operating the device, administrators can more easily provide appropriate support.

[0383] Responding to inquiries from the field.

[0384] The user enters the content of the inquiry from the field into the terminal and sends it (e.g., "Question about today's work procedure").

[0385] The device sends the inquiry details to the server. Simultaneously, the emotion engine collects the user's emotional data.

[0386] The server uses a generative AI to analyze the inquiry content and sentiment data, and generates an appropriate response. For example, if the user is feeling anxious, it will provide a response that takes that into consideration.

[0387] The responses generated by the server are stored in a database and notified to the user in real time.

[0388] The user checks the answers displayed on the device and incorporates that information into their work.

[0389] This enables the system to digitize and automate business processes, as well as provide prompt and accurate support through user sentiment data. This results in reduced manual errors, increased operational efficiency, and higher user satisfaction.

[0390] The following describes the processing flow.

[0391] Program processing

[0392] Digitalization and automation of business processes

[0393] Step 1: Setting up the business workflow

[0394] User: Use a PC to access the workflow settings screen and configure workflows such as "Order Management," "Inventory Check," and "Delivery Management."

[0395] Terminal: Sends information about the configured workflow to the server.

[0396] Server: Saves the received business flow information to the database.

[0397] Step 2: Data Entry

[0398] User: Use your device to enter information into the "Order Management" screen (e.g., product code, quantity, delivery date).

[0399] Terminal: Sends the entered order information to the server.

[0400] Server: Stores order information in the database.

[0401] Step 3: Collecting emotional data

[0402] Terminal: While the user is inputting data, the terminal's camera and microphone are used to collect facial expressions and voice.

[0403] Server: Analyzes facial expressions and voice data sent from terminals using an emotion engine and generates emotion data.

[0404] Server: Stores emotional data in a database.

[0405] Step 4: Processing by Generator AI

[0406] Server: Passes business data and emotional data received from the database to the AI ​​for inventory checks and ordering instructions.

[0407] Server: Saves the processing results of the generated AI (inventory check results and order details) to the database.

[0408] Server: Notifies the user's terminal of the processing results.

[0409] Step 5: Review the results and take appropriate action.

[0410] User: Check the processing results notified on the device and make corrections or approvals as necessary.

[0411] Terminal: Sends user modifications and approvals to the server.

[0412] Server: Reflects changes and approvals in the database.

[0413] Responding to inquiries from the field.

[0414] Step 1: Enter your inquiry

[0415] User: Enter the inquiry details from the field into the terminal and send it (e.g., "I don't know today's work procedure").

[0416] Terminal: Sends the inquiry details to the server.

[0417] Step 2: Analyzing inquiry and sentiment data

[0418] Terminal: Collects facial expressions and voice data from the user while they are entering their inquiry, and sends it to the server.

[0419] Server: The emotion engine analyzes the user's facial expressions and voice data to generate emotion data.

[0420] Server: Uses emotional data to generate inquiry content. An AI analyzes the data and generates relevant answers and information.

[0421] Server: Saves the generated responses to the database.

[0422] Step 3: Provide your response

[0423] Server: Sends the generated response to the user's device.

[0424] Terminal: Displays the answer to the inquiry.

[0425] User: Review the displayed answer and proceed with the task.

[0426] Specific example

[0427] Step 1: Setting up the business workflow

[0428] User: The construction site manager logs into the system on their PC and sets up workflows such as "order management," "inventory check," and "delivery management."

[0429] Terminal: Sends configuration information to the server.

[0430] Server: Saves the received data to the database.

[0431] Step 2: Data Entry

[0432] User: The sales representative enters information about a new order into the "Order Management" screen on their terminal.

[0433] Terminal: Sends input data to the server.

[0434] Server: Stores order information in the database.

[0435] Step 3: Collecting emotional data

[0436] Terminal: The camera and microphone collect the facial expressions and voices of sales representatives entering order information.

[0437] Server: The emotion engine analyzes the collected data and generates emotion data.

[0438] Server: Stores emotional data in a database.

[0439] Step 4: Processing by Generator AI

[0440] Server: The generating AI checks inventory based on order information and sentiment data, and automatically places orders according to the required quantity.

[0441] Server: Saves the results (inventory check and order details) generated by the AI ​​and notifies the user of these results.

[0442] Step 5: Review the results and take appropriate action.

[0443] User: The site manager reviews the results and verifies whether the order details are correct.

[0444] Terminal: Sends user confirmation details to the server.

[0445] Server: Reflect the verification results in the database.

[0446] Examples of how to handle inquiries

[0447] Step 1: Enter your inquiry

[0448] User: Field workers enter their questions about today's work procedures into the terminal and send them.

[0449] Terminal: Sends the inquiry details to the server.

[0450] Step 2: Analyzing inquiry and sentiment data

[0451] Terminal: Collects facial expressions and voice recordings from the user while they are entering their inquiry and sends them to the server.

[0452] Server: The emotion engine analyzes facial expressions and voice data to generate emotion data.

[0453] Server: The generation AI analyzes the inquiry content and sentiment data to generate an appropriate response.

[0454] Step 3: Provide your response

[0455] Server: Saves the generated response to the database and notifies the user.

[0456] Terminal: Displays the answer to the inquiry.

[0457] User: Review the answer and proceed with the task.

[0458] This enables the system to digitize and automate business processes, while also providing meticulous support that takes user emotions into consideration.

[0459] (Example 2)

[0460] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0461] Conventional business process management systems have suffered from inefficiency due to the frequent use of manual operations. Furthermore, they often fail to consider user emotions when providing procedures and support, resulting in low user satisfaction. This invention aims to provide a system that achieves high efficiency and user satisfaction by automating business procedures and utilizing user emotion data.

[0462] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0463] In this invention, the server includes means for automating work procedures using generative artificial intelligence, means for saving user-inputted data to a database, and means for analyzing the data stored in the database and having the generative artificial intelligence execute the work procedures. By combining this with means for collecting and analyzing user emotional data and means for adjusting work procedures based on emotional data, rapid and accurate support becomes possible.

[0464] "Generative artificial intelligence" is a type of artificial intelligence that performs self-learning based on given data to optimize and automate business procedures.

[0465] "Business procedures" refer to a series of steps and procedures necessary to perform a specific task or process.

[0466] A "database" is a system for organizing and storing data, allowing for the quick retrieval of necessary information.

[0467] "Emotional data" refers to information that indicates a user's emotional state, obtained from their facial expressions, voice, and choice of words.

[0468] An "emotion engine" is a part of the software or hardware used to collect and analyze emotional data.

[0469] A "server" is a computer system used to store, process, and transmit data over a network.

[0470] A "terminal" is a device (e.g., a PC or smart device) used by a user to input, verify, and modify business data.

[0471] "Analysis" is the process of examining data in detail and finding its meaning and patterns.

[0472] "Notification" refers to the act of a system informing a user of processing results or other information.

[0473] This invention relates to a system for digitizing and automating business workflows by combining an emotion engine. This system uses generative artificial intelligence (generative AI) to automate business procedures and leverages user emotion data to provide more appropriate and effective support.

[0474] Digitalization and automation of business processes

[0475] Server Configuration

[0476] The server plays a central role in this system. It incorporates a database for storing work procedures, generative artificial intelligence, and an emotion engine for analyzing user sentiment data. The server receives work data sent by users and stores it in the database. It also uses generative AI to execute automated tasks based on work procedures and notifies the user of the results.

[0477] Device configuration

[0478] These are devices (e.g., PCs and smart devices) that users use to input, verify, and modify business data. Data entered on the terminal is transmitted to the server in real time, where it is analyzed and processed. Furthermore, user emotional data is collected in conjunction with an emotion engine.

[0479] Collection and analysis of emotional data

[0480] Collection of emotional data

[0481] The device collects emotional data in real time through facial expressions and voice during user interaction. For example, it uses a facial recognition camera and microphone. The collected emotional data is sent to a server.

[0482] Analysis of emotional data

[0483] The server uses an emotion engine to analyze the received emotional data. The analysis results are fed back to the generating AI, which adjusts the work procedures and responses according to the user's emotions.

[0484] Specific examples of operation

[0485] Setting up business workflows

[0486] User: Access the workflow settings screen using a PC and configure processes such as "Order Management," "Inventory Check," and "Delivery Management."

[0487] Terminal: Sends information about the configured workflow to the server.

[0488] Server: Saves the received business flow information to the database.

[0489] Data entry and automation

[0490] User: Use the terminal to enter information into the "Order Management" screen. For example, enter order information such as product code, quantity, and delivery date.

[0491] Terminal: Collects emotional data along with the entered order information and sends it to the server.

[0492] Server: Stores submitted order information and sentiment data in a database and uses generated AI to check inventory and issue ordering instructions. For example, it automatically instructs ordering procedures for items with insufficient stock.

[0493] Server: Stores inventory check and order instruction results in a database and notifies users.

[0494] User: Review the results notified via the device and make corrections or approvals as necessary.

[0495] Use of emotional data

[0496] Server: Based on the user's emotional data analyzed by the emotion engine, the generating AI adjusts the work procedures and responses. For example, if a user is feeling stressed, it can suggest simplifying the operation.

[0497] Terminal: Displays emotional data in real time while the user is operating the device, making it easier for administrators to provide appropriate support.

[0498] Responding to inquiries from the field.

[0499] Inquiry reception

[0500] User: Enter the inquiry from the field into the terminal and send it. For example, enter "Question about today's work procedure."

[0501] Terminal: Sends emotional data along with the inquiry content to the server.

[0502] Answer generation

[0503] Server: Uses a generation AI to analyze inquiry content and sentiment data to generate appropriate responses. For example, if anxiety is felt, it will create content that provides reassurance.

[0504] Submit and confirm your response.

[0505] Server: Generated responses are stored in a database and users are notified in real time.

[0506] User: Check the answers on the device and incorporate the information into the work.

[0507] Example of a prompt

[0508] "The generating AI checks the inventory of product code 12345 and issues order instructions as needed."

[0509] "If a user is feeling anxious, we will provide an answer that takes that into consideration."

[0510] "Generate suggestions to simplify operations for users who are experiencing stress."

[0511] This enables efficient and user-satisfying business operations through detailed procedures and specific actions.

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

[0513] Step 1:

[0514] Users access a business workflow settings screen and configure business procedures such as "order management," "inventory check," and "delivery management." For example, in "order management," a user might input "product code," "quantity," and "delivery date." The entered data is then used to configure the business workflow settings.

[0515] Input: Business flow configuration information (e.g., product code, quantity, delivery date)

[0516] Output: Configured business workflow (e.g., order management)

[0517] Step 2:

[0518] The terminal transmits information about the user's configured workflow to the server in real time. This transmission transfers the configuration information to the server.

[0519] Input: Configured business flow information (e.g., order management information)

[0520] Output: Business flow information sent to the server

[0521] Step 3:

[0522] The server saves the received business flow information to a database. This saving process allows configuration information to be accumulated in the database and made available for later processing.

[0523] Input: Business flow information sent to the server (e.g., order management information)

[0524] Output: Business flow information stored in the database

[0525] Step 4:

[0526] The user enters information into the "Order Management" screen based on the configured workflow. For example, they might enter product code "12345", quantity "100", and delivery date "next Monday". The entered data is then compiled into order information.

[0527] Input: Order information (e.g., product code, quantity, delivery date)

[0528] Output: Entered order information

[0529] Step 5:

[0530] The terminal collects emotional data in real time along with the entered order information and sends it to the server. The terminal collects emotional data using a facial recognition camera and microphone.

[0531] Input: Order information and emotional data (e.g., user's facial expressions, voice)

[0532] Output: Order information and sentiment data sent to the server

[0533] Step 6:

[0534] The server stores the submitted order information and sentiment data in a database.

[0535] Input: Order information and sentiment data

[0536] Output: Order information and sentiment data stored in the database

[0537] Step 7:

[0538] The server uses a generating AI based on stored order information to check inventory and issue ordering instructions. For example, the generating AI automatically instructs ordering processes for products with insufficient stock. The analysis results are stored in a database.

[0539] Input: Order information stored in the database

[0540] Output: Inventory check results and order instructions

[0541] Step 8:

[0542] The server stores the results of inventory checks and order instructions in a database, generates notification information, and notifies the user.

[0543] Input: Inventory check results and order instructions

[0544] Output: Notification Information

[0545] Step 9:

[0546] Users review the results notified via their devices and make corrections or approvals as needed. For example, a user might make changes based on inventory check results.

[0547] Input: Notification information

[0548] Output: Corrected or approved information

[0549] Step 10:

[0550] The device collects emotional data in real time through facial expressions and voice while the user is operating it. For example, it uses a facial recognition camera and microphone.

[0551] Input: User's facial expressions, voice

[0552] Output: Collected sentiment data

[0553] Step 11:

[0554] The device sends the collected emotional data to the server.

[0555] Input: Collected emotional data

[0556] Output: Sentiment data sent to the server

[0557] Step 12:

[0558] The server uses an emotion engine to analyze the received emotional data. The analysis results are fed back to the generating AI, which adjusts the work procedures and responses according to the user's emotions.

[0559] Input: Collected emotional data

[0560] Output: Analysis results and feedback information

[0561] Step 13:

[0562] The user enters the inquiry details from the field into the terminal and sends it. For example, they might enter "A question about today's work procedure."

[0563] Input: Inquiry details

[0564] Output: Inquiry content entered into the terminal

[0565] Step 14:

[0566] The device sends emotion data along with the inquiry content to the server.

[0567] Input: Inquiry details and sentiment data

[0568] Output: Query content and sentiment data sent to the server

[0569] Step 15:

[0570] The server uses a generative AI to analyze the inquiry content and sentiment data, and generates an appropriate response. For example, if the user is feeling anxious, it will create a response that provides reassurance.

[0571] Input: Inquiry details and sentiment data

[0572] Output: Generated answer

[0573] Step 16:

[0574] The server stores the generated responses in a database and notifies the user in real time.

[0575] Input: Generated answer

[0576] Output: Notified response

[0577] Step 17:

[0578] Users review their responses on their devices and incorporate that information into their work. For example, a user might modify their work procedures based on the generated responses.

[0579] Input: Notified response

[0580] Output: Answers reflected in the work

[0581] (Application Example 2)

[0582] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0583] The present invention aims to provide a system that digitizes and automates business workflows, while also understanding user emotions in real time and providing personalized support. Conventional systems have struggled to respond while considering user emotions, resulting in problems with operational efficiency and user satisfaction. In particular, it is necessary to provide appropriate support according to emotional states to improve operational efficiency, reduce errors, and achieve high user satisfaction.

[0584] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0585] In this invention, the server includes means for collecting and analyzing emotional data, means for providing personalized support to the user based on the emotional data, and means for providing appropriate responses based on the user's emotional data. This makes it possible to grasp the user's emotions in real time and provide appropriate support quickly.

[0586] "Generative artificial intelligence" refers to an artificial intelligence system that automatically executes tasks in response to business procedures and user inquiries, and generates appropriate answers and results.

[0587] "Emotional data" refers to information that represents a user's emotional state, obtained from their facial expressions, voice, and choice of words.

[0588] An "emotion engine" is a system that collects and analyzes user emotional data and uses the results to adjust work procedures and support content.

[0589] "Personalized support" refers to specific assistance and content provided according to each user's individual emotional state and needs.

[0590] A "terminal" is a device used by a user to input, verify, and modify business data.

[0591] A "database" is an information management system used to centrally store and manage business procedures, user input data, emotional data, and other similar information.

[0592] A "business process flow" is a sequence of processes and tasks that make up a business procedure.

[0593] A "server" is a central processing unit that processes and analyzes business procedures and emotional data, and manages and notifies the generated results.

[0594] An "inquiry" is a question or request made by a user to seek support or address doubts regarding the work environment or procedures.

[0595] An "answer" is a response to a generated inquiry, providing appropriate solutions and information to the user's questions or requests.

[0596] This invention is a system for digitizing and automating business workflows using a combination of generative AI and an emotion engine. This system utilizes the following hardware and software to enhance user work efficiency and provide personalized support.

[0597] System configuration and operation

[0598] Digitalization and automation of business processes

[0599] Server: Plays a central role in the system. The server incorporates a database for storing business procedures, a generative AI model, and an emotion engine. The server receives business data sent by users and stores it in the database. It also uses generative AI to execute automated tasks based on business procedures and notifies the user of the results.

[0600] Software used: Database management system (e.g., MySQL), AI model (e.g., TENSORFLOW® / Keras), request processing (e.g., Flask).

[0601] Terminal: A device used by users to input, verify, and modify business data (e.g., PC or smart device). Data entered on the terminal is sent to the server in real time, where it is analyzed and processed. It also has a function to collect user emotion data in conjunction with the emotion engine.

[0602] Software to be used: Face recognition libraries (e.g., OpenCV, dlib), emotion recognition models (e.g., TensorFlow / Keras).

[0603] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[0604] Collection and analysis of emotional data

[0605] Server: The emotion engine collects emotional data from the user's facial expressions, voice, and language use, and analyzes this data. The analysis results are fed back to the generating AI and used to adjust work procedures and the content of responses to inquiries.

[0606] Software to be used: Emotion recognition library (e.g., TensorFlow / Keras).

[0607] Terminal: Along with the business data entered by the user, the emotion engine sends collected emotion data to the server. The user's emotion data is analyzed in real time, and the results are reflected in the progress of the work.

[0608] Specific example

[0609] For example, when a user is searching for products in a virtual store, their smartphone camera captures their facial expressions, and an emotion engine detects that the user is having trouble. This information is sent to a server, and an appropriate support message is displayed.

[0610] Example of a prompt:

[0611] "Based on emotion recognition, generate appropriate support messages to display when a user is experiencing difficulties."

[0612] This allows the system to understand users' emotions in real time and provide appropriate support. In addition, the digitalization and automation of workflows improves user work efficiency, reduces errors, and enables faster task completion.

[0613] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0614] Step 1:

[0615] Terminal: Users input business data. Specifically, users use a terminal (PC or smart device) to input information such as product code, quantity, and delivery date into the order management screen. The entered data is temporarily stored on the terminal.

[0616] Input: Business data entered by the user (e.g., product code, quantity, delivery date)

[0617] Output: Business data temporarily stored on the terminal

[0618] Step 2:

[0619] Terminal: Sends entered business data to the server. Simultaneously, it uses the terminal's camera to capture user facial data and collects emotional data in real time using an emotion engine. The collected emotional data is also sent to the server.

[0620] Input: Business data, user facial expression data

[0621] Output: Business data and sentiment data sent to the server

[0622] Step 3:

[0623] Server: Stores received business data and sentiment data in the database. Business data is stored according to the business flow, and sentiment data is stored linked to the user session.

[0624] Input: Business data and emotional data sent from the terminal.

[0625] Output: Business data and sentiment data stored in the database

[0626] Step 4:

[0627] Server: Analyzes stored business data using a generation AI model and automatically generates necessary business procedures. It also adjusts the workflow as needed based on emotional data. For example, if a user is experiencing stress, it simplifies the business procedures.

[0628] Input: Business data and emotional data stored in the database

[0629] Output: Business procedures and adjusted workflows analyzed and generated by the AI ​​model.

[0630] Step 5:

[0631] Server: Executes the generated business procedures. Specifically, it automates tasks such as inventory checks and order placement, and generates the results.

[0632] Input: Generated business procedure

[0633] Output: Automated task results (e.g., inventory check results, order instructions)

[0634] Step 6:

[0635] Server: Notifies the user of the results of automated tasks. Simultaneously, it generates appropriate feedback and support messages for the user based on sentiment data. For example, if the user is having trouble, it displays a support message to help resolve the issue.

[0636] Input: Automated task results, sentiment data

[0637] Output: Results notified to the user, support messages

[0638] Step 7:

[0639] User: Check the results and support messages notified on the device. Modify or approve the results as needed.

[0640] Input: Notified results, support message

[0641] Output: User review, modification, and approval of results

[0642] This enables the system to provide swift and accurate support within a digitized workflow, while taking user emotions into consideration.

[0643] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0644] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0645] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0646] [Second Embodiment]

[0647] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0648] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0649] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0650] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0651] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0652] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0653] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0654] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0655] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0656] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0657] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0658] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0659] This invention is a system that digitizes and automates the workflows of industries with many analog operations, such as the construction industry. This system has the function of automating work procedures using generative artificial intelligence, the function of saving and analyzing user-entered data in a database, and the function of responding quickly and accurately to inquiries from the field.

[0660] System configuration and operation

[0661] Digitalization and automation of business processes

[0662] Server: This server plays a central role in this system. It incorporates a database for storing and managing business procedures. The server receives business data sent by users and stores it in the database. It also uses generative artificial intelligence to execute automated tasks based on business procedures and notifies users of the results.

[0663] Terminal: A device (e.g., PC or smart device) used by users to input, verify, and modify business data. Data entered on the terminal is sent to the server in real time, where it is analyzed and processed.

[0664] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[0665] Responding to inquiries from the field.

[0666] Server: Receives the inquiry content and analyzes it using a generation AI. Generates an appropriate answer from the analysis results and saves that answer in the database. The generated answer is notified to the user in real time.

[0667] Terminal: This is the device on which the user enters and submits their inquiry. It displays the response sent from the server.

[0668] User: Inputs and sends inquiries from the field using a terminal, and checks the generated response.

[0669] Specific examples of operation

[0670] Setting up business workflows

[0671] Users access the workflow settings screen using their PCs. For example, they can configure business processes such as "order management," "inventory check," and "delivery management."

[0672] The server saves these settings to the database.

[0673] The terminal displays the workflow configured by the user and allows them to modify it as needed.

[0674] Data entry and automation

[0675] The user uses a terminal to enter order information into the "Order Management" screen. For example, they might enter the product code, quantity, delivery date, etc.

[0676] The terminal sends the entered information to the server.

[0677] The server stores order information in a database and uses AI to automatically check inventory and place necessary orders. The results are stored in the database and notified to the user.

[0678] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[0679] Inquiry response

[0680] Users input inquiries from the field using a terminal and send questions, for example, about "today's work procedures."

[0681] The terminal sends the inquiry details to the server.

[0682] The server uses generation AI to analyze the inquiry and generate an appropriate response. For example, it can provide instructions for work procedures or answers to related FAQs.

[0683] The responses generated by the server are stored in a database and notified to the user in real time.

[0684] The user checks the answers displayed on the device and incorporates that information into their work.

[0685] This system digitizes and automates business processes using the procedures described above, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[0686] The following describes the processing flow.

[0687] Program processing

[0688] Digitalization and automation of business processes

[0689] Step 1: Setting up the business workflow

[0690] User: Access the workflow settings screen using a PC and configure workflows such as "Order Management," "Inventory Check," and "Delivery Management."

[0691] Terminal: Sends information about the configured workflow to the server.

[0692] Server: Saves the received business flow information to the database.

[0693] Step 2: Data Entry

[0694] User: Use your device to enter information into the "Order Management" screen (e.g., product code, quantity, delivery date).

[0695] Terminal: Sends the entered order information to the server.

[0696] Server: Stores order information in the database.

[0697] Step 3: Processing by Generator AI

[0698] Server: Receives data from the database and passes it to the AI ​​for inventory checks and ordering instructions.

[0699] Server: Saves the processing results of the generated AI (inventory check results and order details) to the database.

[0700] Server: Notifies the user's terminal of the processing results.

[0701] Step 4: Review the results and take appropriate action.

[0702] User: Check the processing results notified on the device and make corrections or approvals as necessary.

[0703] Terminal: Sends user modifications and approvals to the server.

[0704] Server: Reflects changes and approvals in the database.

[0705] Responding to inquiries from the field.

[0706] Step 1: Enter your inquiry

[0707] User: Enter the inquiry details from the field into the terminal and send it (e.g., "I don't know today's work procedure").

[0708] Terminal: Sends the inquiry details to the server.

[0709] Step 2: Inquiry Analysis

[0710] Server: Uses generation AI to analyze inquiry content and extract and generate relevant answers and information.

[0711] Server: Saves the generated responses to the database.

[0712] Step 3: Provide your response

[0713] Server: Sends the answers stored in the database to the user's terminal.

[0714] Terminal: Displays the answer to the inquiry.

[0715] User: Review the displayed answer and proceed with the task.

[0716] Specific example

[0717] Step 1: Setting up the business workflow

[0718] User: The construction site manager logs into the system on their PC and sets up workflows such as "order management," "inventory check," and "delivery management."

[0719] Terminal: Sends configuration information to the server.

[0720] Server: Saves the received data to the database.

[0721] Step 2: Data Entry

[0722] User: The sales representative enters information about a new order into the "Order Management" screen on their terminal.

[0723] Terminal: Sends input data to the server.

[0724] Server: Stores order information in the database.

[0725] Step 3: Processing by Generator AI

[0726] Server: The generation AI checks inventory based on order information and automatically places orders according to the required quantity.

[0727] Server: Saves the results (inventory check and order details) generated by the AI ​​and notifies the user of these results.

[0728] Step 4: Review the results and take appropriate action.

[0729] User: The site manager reviews the results and verifies whether the order details are correct.

[0730] Terminal: Sends user confirmation details to the server.

[0731] Server: Reflect the verification results in the database.

[0732] Examples of how to handle inquiries

[0733] Step 1: Enter your inquiry

[0734] User: Field workers enter their questions about today's work procedures into the terminal and send them.

[0735] Terminal: Sends the inquiry details to the server.

[0736] Step 2: Inquiry Analysis

[0737] Server: The AI ​​generates responses by analyzing the inquiry and producing answers such as, "Today, we will proceed with the work according to the following steps."

[0738] Server: Saves the generated responses to the database.

[0739] Step 3: Provide your response

[0740] Server: Sends the generated response to the user's device.

[0741] Terminal: Displays the answer to the inquiry.

[0742] User: Review the answer and proceed with the task.

[0743] This system enables the digitalization and automation of business processes, as well as providing quick and accurate responses to inquiries from the field.

[0744] (Example 1)

[0745] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0746] Currently, many industries are demanding the digitalization and automation of business procedures, but the labor of field workers and managers, as well as errors caused by manual processes, remain major problems. Furthermore, there are challenges in responding quickly and accurately to inquiries. In particular, industries with many analog operations, such as construction, require increased efficiency in workflows and reduced errors, but achieving this presents significant cost and technical hurdles.

[0747] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0748] This invention includes a server that includes means for automating business procedures using generative artificial intelligence, means for saving user-input data to a database, and means for the generative artificial intelligence to execute business procedures by analyzing the data stored in the database. This enables automation and efficiency of business procedures. It also includes means for the user to input business data using a terminal, means for making inquiries from the field using a terminal, means for the server to analyze the inquiry content using generative artificial intelligence and generate an answer, and means for displaying the generated answer on the user's terminal. This enables a quick and accurate response to inquiries. It also includes means for the user to operate a business flow setting screen via a terminal, means for saving the business flow settings to a database, means for the user to check and modify the saved business flow on a terminal, and means for the business data stored in the database to be sent to the server in real time. This enables easy setting and updating of business flows. It also includes means for the server to automatically perform inventory checks and orders using a generative AI model based on the business data received, means for notifying the user of the generated inventory check and order results, and means for the user to check the notified results and make corrections or approvals as necessary. This achieves efficiency and accuracy in inventory management and ordering operations.

[0749] "Generative artificial intelligence" refers to systems that use machine learning and natural language processing technologies to perform intelligent tasks like humans.

[0750] "Automating business procedures" refers to automatically executing business processes that were previously performed manually, using systems and software.

[0751] A "database" refers to a system for efficiently storing, managing, and retrieving large amounts of data.

[0752] "User" refers to a person who uses this system to input business data, make inquiries, and check the results, or a person with a similar role.

[0753] "Terminal" refers to a hardware device used by a user (e.g., PC, smartphone, tablet).

[0754] A "server" refers to a computer system that plays a central role in storing, managing, and analyzing data, and connecting users and their devices.

[0755] "Inquiry" refers to a question that a user asks via their device to resolve doubts or uncertainties regarding the field or the performance of their work.

[0756] "Answer" refers to information or solutions generated by the server using artificial intelligence and provided to the user.

[0757] The "settings screen" refers to the interface that allows users to configure and modify business workflows and processes.

[0758] "Inventory check" refers to verifying the current inventory status based on inventory information stored in a database.

[0759] "Placement" refers to the business process of ordering necessary goods or materials from suppliers.

[0760] "Notification" refers to the real-time transmission of results or responses generated by the server to the user.

[0761] This invention is a system that digitizes and automates the workflows of industries with many analog operations, such as the construction industry. This system has the function of automating work procedures using generative artificial intelligence, the function of saving and analyzing user-entered data in a database, and the function of responding quickly and accurately to inquiries from the field.

[0762] System configuration and operation

[0763] Digitalization and automation of business processes

[0764] 1. Server

[0765] The server plays a central role in this system. This server incorporates a database (e.g., MySQL) for storing and managing business procedures. The server receives business data sent by users and stores it in the database. It also uses generative artificial intelligence (e.g., GPT-4) to execute automated tasks based on business procedures and notifies the user of the results.

[0766] 2. Terminal

[0767] A terminal is a device used by users to input, verify, and modify business data. Typically, a PC or smart device is used. Data entered on the terminal is transmitted to the server in real time, where it is analyzed and processed.

[0768] 3. User

[0769] Users are field workers or managers who input, verify, and modify business data through terminals. For example, a user might use a PC to input product codes, quantities, and delivery dates on the "Order Management" screen. This data is sent to the server via the terminal, where automated tasks are executed.

[0770] Responding to inquiries from the field.

[0771] 1. User

[0772] Users input inquiries from the field using their devices (PCs, smartphones, etc.). For example, they might input a question like, "What should I do if there is insufficient stock?"

[0773] 2. Terminal

[0774] The terminal sends the inquiry to the server and displays the response sent from the server.

[0775] 3. Server

[0776] The server receives the inquiry and analyzes the content using a generative AI model (e.g., GPT-4). It generates an appropriate response from the analysis results and saves it to a database. The generated response is notified to the user in real time. For example, a response such as "If inventory is low, an additional order is required" might be provided.

[0777] Specific example of the operation flow

[0778] 1. Setting up the business workflow

[0779] Users access the workflow settings screen using their PCs and configure business processes such as "order management," "inventory check," and "delivery management."

[0780] The server saves these settings to the database.

[0781] The terminal displays the workflow configured by the user and allows them to modify it as needed.

[0782] 2. Data entry and automation

[0783] The user enters order information into the "Order Management" screen using their device. For example, they might enter the product code, quantity, and delivery date.

[0784] The terminal sends the entered information to the server.

[0785] The server saves order information to a database and uses AI to automatically check inventory and place necessary orders. The results are saved in the database and notified to the user.

[0786] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[0787] 3. Handling inquiries

[0788] Users input inquiries from the field using a terminal and send questions, for example, about "today's work procedures."

[0789] The terminal sends the inquiry details to the server.

[0790] The server uses AI to analyze the inquiry and generate an appropriate response. For example, it may provide instructions on how to perform tasks or answers to related FAQs.

[0791] The responses generated by the server are stored in a database and notified to the user in real time.

[0792] The user reviews the answers displayed on their device and incorporates that information into their work.

[0793] Example of a prompt

[0794] "Product code: ABC123, Quantity: 10, Delivery date: 2023-10-15. Please check inventory and process the order for this item."

[0795] "Please tell me today's work procedure."

[0796] As a result, this system digitizes and automates business processes, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[0797] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0798] Step 1:

[0799] The user enters business data using a terminal. For example, they enter the product code, quantity, and delivery date. Specifically, the entered data is product code "ABC123", quantity "10", and delivery date "2023-10-15".

[0800] input:

[0801] Product code, quantity, delivery date

[0802] output:

[0803] Input data displayed on the terminal

[0804] Step 2:

[0805] The terminal sends the entered business data to the server. The data is sent to the server as an HTTP POST request. Specifically, the data sent from the terminal includes the product code "ABC123", quantity "10", and delivery date "2023-10-15".

[0806] input:

[0807] Business data entered into the terminal

[0808] output:

[0809] Business data sent to the server

[0810] Step 3:

[0811] The server analyzes the received business data and saves it to the database. Specifically, the server saves the product code "ABC123", quantity "10", and delivery date "2023-10-15" to the MySQL database.

[0812] input:

[0813] Business data sent to the server

[0814] output:

[0815] Business data stored in the database

[0816] Step 4:

[0817] The server uses a generated AI model (e.g., GPT-4) based on the stored data to check inventory and automatically place necessary orders. For example, the AI ​​model might determine that "there are 50 units in stock, so no additional orders are needed."

[0818] input:

[0819] Business data stored in the database

[0820] Inventory data required by the generative AI model

[0821] output:

[0822] The decision was made that an order is not necessary.

[0823] Step 5:

[0824] The server saves the results of tasks automated by the generated AI model to a database and notifies the user of those results. For example, a notification such as "Inventory check results indicate no additional orders are needed" is sent via email or system notification.

[0825] input:

[0826] Inventory check results

[0827] output:

[0828] Results notified to the user

[0829] Step 6:

[0830] The user checks the notification results using their device. If necessary, they can modify or approve the results on the system screen. For example, the user might check a notification on their smartphone stating "No additional order is needed" and approve it without making any changes.

[0831] input:

[0832] Notified results

[0833] output:

[0834] User verification and modification / approval results

[0835] Step 7:

[0836] Users input inquiries from the field using a terminal. For example, they might input a question like, "What are today's work procedures?"

[0837] input:

[0838] Inquiry details

[0839] output:

[0840] Inquiry content displayed on the device

[0841] Step 8:

[0842] The terminal sends the inquiry details to the server. The data is sent to the server as an HTTP POST request.

[0843] input:

[0844] Inquiry content entered on the terminal

[0845] output:

[0846] Inquiry content sent to the server

[0847] Step 9:

[0848] The server receives the inquiry and analyzes the content using a generation AI model. An appropriate answer is generated from the analysis results. For example, the AI ​​model might generate the answer: "Today's work procedure is as follows: 1. Arrive at the site 2. Prepare equipment 3. Begin work."

[0849] input:

[0850] Inquiry content sent to the server

[0851] Business procedure data required by the generated AI model

[0852] output:

[0853] Generated answer

[0854] Step 10:

[0855] The server saves the generated response to a database and notifies the user in real time. For example, the response might say, "Today's work procedure is as follows."

[0856] input:

[0857] Generated answer

[0858] output:

[0859] Responses notified to the user

[0860] Step 11:

[0861] The user checks the answers displayed on the device and incorporates that information into their work. For example, they might start on-site work following the work procedure displayed on the device.

[0862] input:

[0863] Notified response

[0864] output:

[0865] Tasks performed by the user

[0866] As a result, this system digitizes and automates business processes, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[0867] (Application Example 1)

[0868] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0869] In existing factory operations, work procedures and workflows are often managed manually, resulting in insufficient efficiency and automation. This leads to problems such as manual errors, wasted time, and delays in responding to inquiries, ultimately reducing productivity and quality. The objective of this invention is to solve these problems and realize the digitalization and automation of workflows.

[0870] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0871] In this invention, the server includes means for automating work procedures using generative artificial intelligence, means for storing user-input data in a database, means for transmitting data to the server in real time, means for optimizing work procedures using generative AI, and means for automating operations on a factory production line. This enables more efficient workflows, reduced errors, and faster response times to inquiries.

[0872] "Generative artificial intelligence" is an advanced artificial intelligence technology used to automate business procedures, analyze data, and generate appropriate responses.

[0873] A "database" is a digital information repository where information such as business data, workflows, and inquiry details are centrally managed and stored and analyzed as needed.

[0874] "A means of sending data to a server in real time" refers to a system configuration that instantly sends data entered by a user to a server, enabling immediate processing and analysis of the data.

[0875] "Generative AI" is a type of artificial intelligence technology that automatically provides appropriate responses and optimizes work procedures based on user questions and data.

[0876] "Methods for optimizing work procedures" refers to technologies that use generative AI to automatically plan and propose efficient and error-free work procedures.

[0877] "Methods for automating factory production line operations" refer to systems in which robots and automated equipment perform production activities without human intervention, based on business flows and work procedures stored in a database.

[0878] "Users" refer to people such as field workers and managers who input and verify business data and use the system to perform their duties.

[0879] A "terminal" is a device used by users to input, verify, and modify business data, and includes PCs and smartphones.

[0880] A "server" is a computer system that plays a central role in this system, comprehensively managing data storage and analysis, execution of generating AI, and notification of results.

[0881] This invention is a system aimed at automating and digitizing work procedures and workflows in factories. This system stores user-inputted data in a database, and based on that data, generative artificial intelligence (generative AI) optimizes and automatically executes work procedures. It also includes means for sharing work procedures with robots within the factory and for quickly responding to inquiries from the factory floor.

[0882] Hardware and software configuration

[0883] server

[0884] The server plays a central role in the system. It performs the following functions:

[0885] Data Storage: User-entered data is saved to a database. SQLite is used as the database.

[0886] Data Analysis: Analyze data stored in the database and optimize work procedures using generative AI. OpenAI's GPT-3 is used for generative AI.

[0887] Result Notification: Notifies the user of the results generated by the AI.

[0888] terminal

[0889] A terminal is a device used by users to input, verify, and modify business data. It has the following functions:

[0890] Data entry: Provide a screen for entering business data. This could be a smartphone or computer, for example.

[0891] Inquiry Submission: A function that allows users to input inquiries from the field and send them to the server.

[0892] Results display: Displays notifications from the server and responses generated by the AI ​​in real time.

[0893] robot

[0894] The robots in the factory are responsible for automatically performing tasks based on work procedures shared from a server. The robots perform the following functions:

[0895] Task Execution: Perform tasks on the production line according to the specified work procedures.

[0896] Data transmission: Sends the progress of the work to the server in real time.

[0897] Specific examples of actions

[0898] Setting up business workflows

[0899] 1. Users access the business workflow settings screen using their smartphones. For example, they can set up business processes such as "order management," "inventory check," and "delivery management."

[0900] 2. The server saves these settings to the database.

[0901] Data entry and automation

[0902] 1. The user enters order information into the "Order Management" screen using their terminal. For example, they enter information such as product code, quantity, and delivery date.

[0903] 2. The terminal sends the entered information to the server.

[0904] 3. The server stores order information in a database and uses AI generation to automatically check inventory and place necessary orders.

[0905] 4. The server saves the results to the database and notifies the user.

[0906] 5. The user checks the notified results on their device and makes corrections or approvals as necessary.

[0907] Inquiry response

[0908] 1. Users input inquiries from the field using a terminal and send, for example, "Today's work procedure."

[0909] 2. The terminal sends the inquiry details to the server.

[0910] 3. The server uses a generation AI to analyze the inquiry and generate an appropriate response. For example, it may provide a work procedure guide or answers to related FAQs.

[0911] 4. The server saves the generated responses to a database and notifies the user in real time.

[0912] 5. The user reviews the answers displayed on the device and incorporates them into their work.

[0913] Example of a prompt

[0914] Working process:

[0915] Product order registration

[0916] Check stock availability

[0917] Order Placement

[0918] Preparation for delivery

[0919] Question: Please explain today's work procedure.

[0920] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0921] Step 1:

[0922] Users access the workflow settings screen using their smartphones. Users configure business processes such as "order management," "inventory check," and "delivery management."

[0923] Input: Business flow settings (e.g., order management, inventory check, delivery management)

[0924] Operation: Entering content on the business flow settings screen.

[0925] Output: Data from the configured business flow

[0926] Step 2:

[0927] The server saves the user's entered settings to a database.

[0928] Input: Data from the configured business flow

[0929] Operation: Saving flow configuration data to the database

[0930] Output: Saved business flow data

[0931] Step 3:

[0932] The user uses a terminal to enter order information into the "Order Management" screen. For example, they enter information such as product code, quantity, and delivery date.

[0933] Input: Order information (product code, quantity, delivery date, etc.)

[0934] Operation: Entering order information on the screen

[0935] Output: Input order data

[0936] Step 4:

[0937] The terminal sends the entered information to the server.

[0938] Input: Entered order data

[0939] Operation: Sending data to the server

[0940] Output: Order data received by the server

[0941] Step 5:

[0942] The server stores order information in a database and uses AI generation to automatically check inventory and place necessary orders.

[0943] Input: Order data received by the server

[0944] Operation: Saves order information to the database and uses AI to check inventory and automatically place orders.

[0945] Output: Inventory status, order placement information

[0946] Step 6:

[0947] The server saves the results to the database and notifies the user.

[0948] Input: Inventory status, order placement information

[0949] Operation: Save results to a database and notify the user.

[0950] Output: Processing results notified to the user

[0951] Step 7:

[0952] Users can check the notified results on their devices and make corrections or approvals as needed.

[0953] Input: Processing result notified to the user

[0954] Action: Review results, make necessary corrections and approvals.

[0955] Output: Corrected and approved data

[0956] Step 8:

[0957] Users input inquiries from the field using a terminal and send, for example, "Today's work procedure."

[0958] Input: Inquiry details (e.g., "Today's work procedure")

[0959] Operation: Input and send inquiry content to the terminal.

[0960] Output: Query content sent to the server

[0961] Step 9:

[0962] The server uses a generation AI to analyze the inquiry and generate an appropriate response.

[0963] Input: Inquiry received by the server

[0964] Operation: Analysis of inquiry content and generation of answers using a generation AI.

[0965] Output: Generated answer

[0966] Step 10:

[0967] The server saves the generated responses to a database and notifies the user in real time.

[0968] Input: Generated answer

[0969] Operation: Saves responses to the database and provides real-time notifications to users.

[0970] Output: Response notified to the user

[0971] Step 11:

[0972] The user checks the answers displayed on their device and incorporates that information into their work.

[0973] Input: Response notified to the user

[0974] Action: Confirmation of notified responses and implementation of the work.

[0975] Output: Results of the work

[0976] This enables the efficient execution of a series of processes and achieves the automation and digitalization of the workflow and work procedures within the factory.

[0977] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0978] This invention relates to a system for digitizing and automating business workflows by combining an emotion engine. This system uses generative artificial intelligence to automate business procedures and leverages user emotion data to provide more appropriate and effective support.

[0979] System configuration and operation

[0980] Digitalization and automation of business processes

[0981] Server: This server plays a central role in this system. It incorporates a database for storing work procedures, generative artificial intelligence, and an emotion engine for analyzing user sentiment data. The server receives work data sent by users and stores it in the database. It also uses generative artificial intelligence to execute automated tasks based on work procedures and notifies the user of the results.

[0982] Terminal: A device (e.g., PC or smart device) used by users to input, verify, and modify business data. Data entered on the terminal is sent to the server in real time, where it is analyzed and processed. In addition, user emotional data is collected in conjunction with the emotion engine.

[0983] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[0984] Collection and analysis of emotional data

[0985] Server: The emotion engine collects emotional data from the user's facial expressions, voice, and language use, and analyzes this data. The analysis results are fed back to the generating AI and used to adjust work procedures and the content of responses to inquiries.

[0986] Terminal: Along with the business data entered by the user, the emotion engine sends collected emotion data to the server. The user's emotion data is analyzed in real time, and the results are reflected in the progress of the work.

[0987] Specific examples of operation

[0988] Setting up business workflows

[0989] Users access a workflow configuration screen using their PCs and set up processes such as "order management," "inventory check," and "delivery management."

[0990] The terminal sends information about the configured workflow to the server.

[0991] The server saves the received business flow information to the database.

[0992] Data entry and automation

[0993] The user enters information into the "Order Management" screen using their device (e.g., product code, quantity, delivery date).

[0994] The device sends the entered information to the server. Simultaneously, the emotion engine collects the user's emotional data.

[0995] The server stores order information and sentiment data in a database and uses a generating AI to check inventory and issue ordering instructions. The results are stored in the database and notified to the user.

[0996] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[0997] Use of emotional data

[0998] Server: Based on the user's emotional data analyzed by the emotion engine, the generating AI adjusts the work procedures and responses. For example, if a user is feeling stressed, it can suggest simplifying the operation.

[0999] Device: By displaying emotional data in real time while the user is operating the device, administrators can more easily provide appropriate support.

[1000] Responding to inquiries from the field.

[1001] The user enters the content of the inquiry from the field into the terminal and sends it (e.g., "Question about today's work procedure").

[1002] The device sends the inquiry details to the server. Simultaneously, the emotion engine collects the user's emotional data.

[1003] The server uses a generative AI to analyze the inquiry content and sentiment data, and generates an appropriate response. For example, if the user is feeling anxious, it will provide a response that takes that into consideration.

[1004] The responses generated by the server are stored in a database and notified to the user in real time.

[1005] The user checks the answers displayed on the device and incorporates that information into their work.

[1006] This enables the system to digitize and automate business processes, as well as provide prompt and accurate support through user sentiment data. This results in reduced manual errors, increased operational efficiency, and higher user satisfaction.

[1007] The following describes the processing flow.

[1008] Program processing

[1009] Digitalization and automation of business processes

[1010] Step 1: Setting up the business workflow

[1011] User: Use a PC to access the workflow settings screen and configure workflows such as "Order Management," "Inventory Check," and "Delivery Management."

[1012] Terminal: Sends information about the configured workflow to the server.

[1013] Server: Saves the received business flow information to the database.

[1014] Step 2: Data Entry

[1015] User: Use your device to enter information into the "Order Management" screen (e.g., product code, quantity, delivery date).

[1016] Terminal: Sends the entered order information to the server.

[1017] Server: Stores order information in the database.

[1018] Step 3: Collecting emotional data

[1019] Terminal: While the user is inputting data, the terminal's camera and microphone are used to collect facial expressions and voice.

[1020] Server: Analyzes facial expressions and voice data sent from terminals using an emotion engine and generates emotion data.

[1021] Server: Stores emotional data in a database.

[1022] Step 4: Processing by Generator AI

[1023] Server: Passes business data and emotional data received from the database to the AI ​​for inventory checks and ordering instructions.

[1024] Server: Saves the processing results of the generated AI (inventory check results and order details) to the database.

[1025] Server: Notifies the user's terminal of the processing results.

[1026] Step 5: Review the results and take appropriate action.

[1027] User: Check the processing results notified on the device and make corrections or approvals as necessary.

[1028] Terminal: Sends user modifications and approvals to the server.

[1029] Server: Reflects changes and approvals in the database.

[1030] Responding to inquiries from the field.

[1031] Step 1: Enter your inquiry

[1032] User: Enter the inquiry details from the field into the terminal and send it (e.g., "I don't know today's work procedure").

[1033] Terminal: Sends the inquiry details to the server.

[1034] Step 2: Analyzing inquiry and sentiment data

[1035] Terminal: Collects facial expressions and voice data from the user while they are entering their inquiry, and sends it to the server.

[1036] Server: The emotion engine analyzes the user's facial expressions and voice data to generate emotion data.

[1037] Server: Uses emotional data to generate inquiry content. An AI analyzes the data and generates relevant answers and information.

[1038] Server: Saves the generated responses to the database.

[1039] Step 3: Provide your response

[1040] Server: Sends the generated response to the user's device.

[1041] Terminal: Displays the answer to the inquiry.

[1042] User: Review the displayed answer and proceed with the task.

[1043] Specific example

[1044] Step 1: Setting up the business workflow

[1045] User: The construction site manager logs into the system on their PC and sets up workflows such as "order management," "inventory check," and "delivery management."

[1046] Terminal: Sends configuration information to the server.

[1047] Server: Saves the received data to the database.

[1048] Step 2: Data Entry

[1049] User: The sales representative enters information about a new order into the "Order Management" screen on their terminal.

[1050] Terminal: Sends input data to the server.

[1051] Server: Stores order information in the database.

[1052] Step 3: Collecting emotional data

[1053] Terminal: The camera and microphone collect the facial expressions and voices of sales representatives entering order information.

[1054] Server: The emotion engine analyzes the collected data and generates emotion data.

[1055] Server: Stores emotional data in a database.

[1056] Step 4: Processing by Generator AI

[1057] Server: The generating AI checks inventory based on order information and sentiment data, and automatically places orders according to the required quantity.

[1058] Server: Saves the results (inventory check and order details) generated by the AI ​​and notifies the user of these results.

[1059] Step 5: Review the results and take appropriate action.

[1060] User: The site manager reviews the results and verifies whether the order details are correct.

[1061] Terminal: Sends user confirmation details to the server.

[1062] Server: Reflect the verification results in the database.

[1063] Examples of how to handle inquiries

[1064] Step 1: Enter your inquiry

[1065] User: Field workers enter their questions about today's work procedures into the terminal and send them.

[1066] Terminal: Sends the inquiry details to the server.

[1067] Step 2: Analyzing inquiry and sentiment data

[1068] Terminal: Collects facial expressions and voice recordings from the user while they are entering their inquiry and sends them to the server.

[1069] Server: The emotion engine analyzes facial expressions and voice data to generate emotion data.

[1070] Server: The generation AI analyzes the inquiry content and sentiment data to generate an appropriate response.

[1071] Step 3: Provide your response

[1072] Server: Saves the generated response to the database and notifies the user.

[1073] Terminal: Displays the answer to the inquiry.

[1074] User: Review the answer and proceed with the task.

[1075] This enables the system to digitize and automate business processes, while also providing meticulous support that takes user emotions into consideration.

[1076] (Example 2)

[1077] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1078] Conventional business process management systems have suffered from inefficiency due to the frequent use of manual operations. Furthermore, they often fail to consider user emotions when providing procedures and support, resulting in low user satisfaction. This invention aims to provide a system that achieves high efficiency and user satisfaction by automating business procedures and utilizing user emotion data.

[1079] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1080] In this invention, the server includes means for automating work procedures using generative artificial intelligence, means for saving user-inputted data to a database, and means for analyzing the data stored in the database and having the generative artificial intelligence execute the work procedures. By combining this with means for collecting and analyzing user emotional data and means for adjusting work procedures based on emotional data, rapid and accurate support becomes possible.

[1081] "Generative artificial intelligence" is a type of artificial intelligence that performs self-learning based on given data to optimize and automate business procedures.

[1082] "Business procedures" refer to a series of steps and procedures necessary to perform a specific task or process.

[1083] A "database" is a system for organizing and storing data, allowing for the quick retrieval of necessary information.

[1084] "Emotional data" refers to information that indicates a user's emotional state, obtained from their facial expressions, voice, and choice of words.

[1085] An "emotion engine" is a part of the software or hardware used to collect and analyze emotional data.

[1086] A "server" is a computer system used to store, process, and transmit data over a network.

[1087] A "terminal" is a device (e.g., a PC or smart device) used by a user to input, verify, and modify business data.

[1088] "Analysis" is the process of examining data in detail and finding its meaning and patterns.

[1089] "Notification" refers to the act of a system informing a user of processing results or other information.

[1090] This invention relates to a system for digitizing and automating business workflows by combining an emotion engine. This system uses generative artificial intelligence (generative AI) to automate business procedures and leverages user emotion data to provide more appropriate and effective support.

[1091] Digitalization and automation of business processes

[1092] Server Configuration

[1093] The server plays a central role in this system. It incorporates a database for storing work procedures, generative artificial intelligence, and an emotion engine for analyzing user sentiment data. The server receives work data sent by users and stores it in the database. It also uses generative AI to execute automated tasks based on work procedures and notifies the user of the results.

[1094] Device configuration

[1095] These are devices (e.g., PCs and smart devices) that users use to input, verify, and modify business data. Data entered on the terminal is transmitted to the server in real time, where it is analyzed and processed. Furthermore, user emotional data is collected in conjunction with an emotion engine.

[1096] Collection and analysis of emotional data

[1097] Collection of emotional data

[1098] The device collects emotional data in real time through facial expressions and voice during user interaction. For example, it uses a facial recognition camera and microphone. The collected emotional data is sent to a server.

[1099] Analysis of emotional data

[1100] The server uses an emotion engine to analyze the received emotional data. The analysis results are fed back to the generating AI, which adjusts the work procedures and responses according to the user's emotions.

[1101] Specific examples of operation

[1102] Setting up business workflows

[1103] User: Access the workflow settings screen using a PC and configure processes such as "Order Management," "Inventory Check," and "Delivery Management."

[1104] Terminal: Sends information about the configured workflow to the server.

[1105] Server: Saves the received business flow information to the database.

[1106] Data entry and automation

[1107] User: Use the terminal to enter information into the "Order Management" screen. For example, enter order information such as product code, quantity, and delivery date.

[1108] Terminal: Collects emotional data along with the entered order information and sends it to the server.

[1109] Server: Stores submitted order information and sentiment data in a database and uses generated AI to check inventory and issue ordering instructions. For example, it automatically instructs ordering procedures for items with insufficient stock.

[1110] Server: Stores inventory check and order instruction results in a database and notifies users.

[1111] User: Review the results notified via the device and make corrections or approvals as necessary.

[1112] Use of emotional data

[1113] Server: Based on the user's emotional data analyzed by the emotion engine, the generating AI adjusts the work procedures and responses. For example, if a user is feeling stressed, it can suggest simplifying the operation.

[1114] Terminal: Displays emotional data in real time while the user is operating the device, making it easier for administrators to provide appropriate support.

[1115] Responding to inquiries from the field.

[1116] Inquiry reception

[1117] User: Enter the inquiry from the field into the terminal and send it. For example, enter "Question about today's work procedure."

[1118] Terminal: Sends emotional data along with the inquiry content to the server.

[1119] Answer generation

[1120] Server: Uses a generation AI to analyze inquiry content and sentiment data to generate appropriate responses. For example, if anxiety is felt, it will create content that provides reassurance.

[1121] Submit and confirm your response.

[1122] Server: Generated responses are stored in a database and users are notified in real time.

[1123] User: Check the answers on the device and incorporate the information into the work.

[1124] Example of a prompt

[1125] "The generating AI checks the inventory of product code 12345 and issues order instructions as needed."

[1126] "If a user is feeling anxious, we will provide an answer that takes that into consideration."

[1127] "Generate suggestions to simplify operations for users who are experiencing stress."

[1128] This enables efficient and user-satisfying business operations through detailed procedures and specific actions.

[1129] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1130] Step 1:

[1131] Users access a business workflow settings screen and configure business procedures such as "order management," "inventory check," and "delivery management." For example, in "order management," a user might input "product code," "quantity," and "delivery date." The entered data is then used to configure the business workflow settings.

[1132] Input: Business flow configuration information (e.g., product code, quantity, delivery date)

[1133] Output: Configured business workflow (e.g., order management)

[1134] Step 2:

[1135] The terminal transmits information about the user's configured workflow to the server in real time. This transmission transfers the configuration information to the server.

[1136] Input: Configured business flow information (e.g., order management information)

[1137] Output: Business flow information sent to the server

[1138] Step 3:

[1139] The server saves the received business flow information to a database. This saving process allows configuration information to be accumulated in the database and made available for later processing.

[1140] Input: Business flow information sent to the server (e.g., order management information)

[1141] Output: Business flow information stored in the database

[1142] Step 4:

[1143] The user enters information into the "Order Management" screen based on the configured workflow. For example, they might enter product code "12345", quantity "100", and delivery date "next Monday". The entered data is then compiled into order information.

[1144] Input: Order information (e.g., product code, quantity, delivery date)

[1145] Output: Entered order information

[1146] Step 5:

[1147] The terminal collects emotional data in real time along with the entered order information and sends it to the server. The terminal collects emotional data using a facial recognition camera and microphone.

[1148] Input: Order information and emotional data (e.g., user's facial expressions, voice)

[1149] Output: Order information and sentiment data sent to the server

[1150] Step 6:

[1151] The server stores the submitted order information and sentiment data in a database.

[1152] Input: Order information and sentiment data

[1153] Output: Order information and sentiment data stored in the database

[1154] Step 7:

[1155] The server uses a generating AI based on stored order information to check inventory and issue ordering instructions. For example, the generating AI automatically instructs ordering processes for products with insufficient stock. The analysis results are stored in a database.

[1156] Input: Order information stored in the database

[1157] Output: Inventory check results and order instructions

[1158] Step 8:

[1159] The server stores the results of inventory checks and order instructions in a database, generates notification information, and notifies the user.

[1160] Input: Inventory check results and order instructions

[1161] Output: Notification Information

[1162] Step 9:

[1163] Users review the results notified via their devices and make corrections or approvals as needed. For example, a user might make changes based on inventory check results.

[1164] Input: Notification information

[1165] Output: Corrected or approved information

[1166] Step 10:

[1167] The device collects emotional data in real time through facial expressions and voice while the user is operating it. For example, it uses a facial recognition camera and microphone.

[1168] Input: User's facial expressions, voice

[1169] Output: Collected sentiment data

[1170] Step 11:

[1171] The device sends the collected emotional data to the server.

[1172] Input: Collected emotional data

[1173] Output: Sentiment data sent to the server

[1174] Step 12:

[1175] The server uses an emotion engine to analyze the received emotional data. The analysis results are fed back to the generating AI, which adjusts the work procedures and responses according to the user's emotions.

[1176] Input: Collected emotional data

[1177] Output: Analysis results and feedback information

[1178] Step 13:

[1179] The user enters the inquiry details from the field into the terminal and sends it. For example, they might enter "A question about today's work procedure."

[1180] Input: Inquiry details

[1181] Output: Inquiry content entered into the terminal

[1182] Step 14:

[1183] The device sends emotion data along with the inquiry content to the server.

[1184] Input: Inquiry details and sentiment data

[1185] Output: Query content and sentiment data sent to the server

[1186] Step 15:

[1187] The server uses a generative AI to analyze the inquiry content and sentiment data, and generates an appropriate response. For example, if the user is feeling anxious, it will create a response that provides reassurance.

[1188] Input: Inquiry details and sentiment data

[1189] Output: Generated answer

[1190] Step 16:

[1191] The server stores the generated responses in a database and notifies the user in real time.

[1192] Input: Generated answer

[1193] Output: Notified response

[1194] Step 17:

[1195] Users review their responses on their devices and incorporate that information into their work. For example, a user might modify their work procedures based on the generated responses.

[1196] Input: Notified response

[1197] Output: Answers reflected in the work

[1198] (Application Example 2)

[1199] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1200] The present invention aims to provide a system that digitizes and automates business workflows, while also understanding user emotions in real time and providing personalized support. Conventional systems have struggled to respond while considering user emotions, resulting in problems with operational efficiency and user satisfaction. In particular, it is necessary to provide appropriate support according to emotional states to improve operational efficiency, reduce errors, and achieve high user satisfaction.

[1201] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1202] In this invention, the server includes means for collecting and analyzing emotional data, means for providing personalized support to the user based on the emotional data, and means for providing appropriate responses based on the user's emotional data. This makes it possible to grasp the user's emotions in real time and provide appropriate support quickly.

[1203] "Generative artificial intelligence" refers to an artificial intelligence system that automatically executes tasks in response to business procedures and user inquiries, and generates appropriate answers and results.

[1204] "Emotional data" refers to information that represents a user's emotional state, obtained from their facial expressions, voice, and choice of words.

[1205] An "emotion engine" is a system that collects and analyzes user emotional data and uses the results to adjust work procedures and support content.

[1206] "Personalized support" refers to specific assistance and content provided according to each user's individual emotional state and needs.

[1207] A "terminal" is a device used by a user to input, verify, and modify business data.

[1208] A "database" is an information management system used to centrally store and manage business procedures, user input data, emotional data, and other similar information.

[1209] A "business process flow" is a sequence of processes and tasks that make up a business procedure.

[1210] A "server" is a central processing unit that processes and analyzes business procedures and emotional data, and manages and notifies the generated results.

[1211] An "inquiry" is a question or request made by a user to seek support or address doubts regarding the work environment or procedures.

[1212] An "answer" is a response to a generated inquiry, providing appropriate solutions and information to the user's questions or requests.

[1213] This invention is a system for digitizing and automating business workflows using a combination of generative AI and an emotion engine. This system utilizes the following hardware and software to enhance user work efficiency and provide personalized support.

[1214] System configuration and operation

[1215] Digitalization and automation of business processes

[1216] Server: Plays a central role in the system. The server incorporates a database for storing business procedures, a generative AI model, and an emotion engine. The server receives business data sent by users and stores it in the database. It also uses generative AI to execute automated tasks based on business procedures and notifies the user of the results.

[1217] Software used: Database management system (e.g., MySQL), AI model (e.g., TensorFlow / Keras), request processing (e.g., Flask).

[1218] Terminal: A device used by users to input, verify, and modify business data (e.g., PC or smart device). Data entered on the terminal is sent to the server in real time, where it is analyzed and processed. It also has a function to collect user emotion data in conjunction with the emotion engine.

[1219] Software to be used: Face recognition libraries (e.g., OpenCV, dlib), emotion recognition models (e.g., TensorFlow / Keras).

[1220] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[1221] Collection and analysis of emotional data

[1222] Server: The emotion engine collects emotional data from the user's facial expressions, voice, and language use, and analyzes this data. The analysis results are fed back to the generating AI and used to adjust work procedures and the content of responses to inquiries.

[1223] Software to be used: Emotion recognition library (e.g., TensorFlow / Keras).

[1224] Terminal: Along with the business data entered by the user, the emotion engine sends collected emotion data to the server. The user's emotion data is analyzed in real time, and the results are reflected in the progress of the work.

[1225] Specific example

[1226] For example, when a user is searching for products in a virtual store, their smartphone camera captures their facial expressions, and an emotion engine detects that the user is having trouble. This information is sent to a server, and an appropriate support message is displayed.

[1227] Example of a prompt:

[1228] "Based on emotion recognition, generate appropriate support messages to display when a user is experiencing difficulties."

[1229] This allows the system to understand users' emotions in real time and provide appropriate support. In addition, the digitalization and automation of workflows improves user work efficiency, reduces errors, and enables faster task completion.

[1230] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1231] Step 1:

[1232] Terminal: Users input business data. Specifically, users use a terminal (PC or smart device) to input information such as product code, quantity, and delivery date into the order management screen. The entered data is temporarily stored on the terminal.

[1233] Input: Business data entered by the user (e.g., product code, quantity, delivery date)

[1234] Output: Business data temporarily stored on the terminal

[1235] Step 2:

[1236] Terminal: Sends entered business data to the server. Simultaneously, it uses the terminal's camera to capture user facial data and collects emotional data in real time using an emotion engine. The collected emotional data is also sent to the server.

[1237] Input: Business data, user facial expression data

[1238] Output: Business data and sentiment data sent to the server

[1239] Step 3:

[1240] Server: Stores received business data and sentiment data in the database. Business data is stored according to the business flow, and sentiment data is stored linked to the user session.

[1241] Input: Business data and emotional data sent from the terminal.

[1242] Output: Business data and sentiment data stored in the database

[1243] Step 4:

[1244] Server: Analyzes stored business data using a generation AI model and automatically generates necessary business procedures. It also adjusts the workflow as needed based on emotional data. For example, if a user is experiencing stress, it simplifies the business procedures.

[1245] Input: Business data and emotional data stored in the database

[1246] Output: Business procedures and adjusted workflows analyzed and generated by the AI ​​model.

[1247] Step 5:

[1248] Server: Executes the generated business procedures. Specifically, it automates tasks such as inventory checks and order placement, and generates the results.

[1249] Input: Generated business procedure

[1250] Output: Automated task results (e.g., inventory check results, order instructions)

[1251] Step 6:

[1252] Server: Notifies the user of the results of automated tasks. Simultaneously, it generates appropriate feedback and support messages for the user based on sentiment data. For example, if the user is having trouble, it displays a support message to help resolve the issue.

[1253] Input: Automated task results, sentiment data

[1254] Output: Results notified to the user, support messages

[1255] Step 7:

[1256] User: Check the results and support messages notified on the device. Modify or approve the results as needed.

[1257] Input: Notified results, support message

[1258] Output: User review, modification, and approval of results

[1259] This enables the system to provide swift and accurate support within a digitized workflow, while taking user emotions into consideration.

[1260] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1261] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1262] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1263] [Third Embodiment]

[1264] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1265] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1266] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1267] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1268] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1269] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1270] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1271] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1272] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1273] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1274] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1275] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1276] This invention is a system that digitizes and automates the workflows of industries with many analog operations, such as the construction industry. This system has the function of automating work procedures using generative artificial intelligence, the function of saving and analyzing user-entered data in a database, and the function of responding quickly and accurately to inquiries from the field.

[1277] System configuration and operation

[1278] Digitalization and automation of business processes

[1279] Server: This server plays a central role in this system. It incorporates a database for storing and managing business procedures. The server receives business data sent by users and stores it in the database. It also uses generative artificial intelligence to execute automated tasks based on business procedures and notifies users of the results.

[1280] Terminal: A device (e.g., PC or smart device) used by users to input, verify, and modify business data. Data entered on the terminal is sent to the server in real time, where it is analyzed and processed.

[1281] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[1282] Responding to inquiries from the field.

[1283] Server: Receives the inquiry content and analyzes it using a generation AI. Generates an appropriate answer from the analysis results and saves that answer in the database. The generated answer is notified to the user in real time.

[1284] Terminal: This is the device on which the user enters and submits their inquiry. It displays the response sent from the server.

[1285] User: Inputs and sends inquiries from the field using a terminal, and checks the generated response.

[1286] Specific examples of operation

[1287] Setting up business workflows

[1288] Users access the workflow settings screen using their PCs. For example, they can configure business processes such as "order management," "inventory check," and "delivery management."

[1289] The server saves these settings to the database.

[1290] The terminal displays the workflow configured by the user and allows them to modify it as needed.

[1291] Data entry and automation

[1292] The user uses a terminal to enter order information into the "Order Management" screen. For example, they might enter the product code, quantity, delivery date, etc.

[1293] The terminal sends the entered information to the server.

[1294] The server stores order information in a database and uses AI to automatically check inventory and place necessary orders. The results are stored in the database and notified to the user.

[1295] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[1296] Inquiry response

[1297] Users input inquiries from the field using a terminal and send questions, for example, about "today's work procedures."

[1298] The terminal sends the inquiry details to the server.

[1299] The server uses generation AI to analyze the inquiry and generate an appropriate response. For example, it can provide instructions for work procedures or answers to related FAQs.

[1300] The responses generated by the server are stored in a database and notified to the user in real time.

[1301] The user checks the answers displayed on the device and incorporates that information into their work.

[1302] This system digitizes and automates business processes using the procedures described above, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[1303] The following describes the processing flow.

[1304] Program processing

[1305] Digitalization and automation of business processes

[1306] Step 1: Setting up the business workflow

[1307] User: Access the workflow settings screen using a PC and configure workflows such as "Order Management," "Inventory Check," and "Delivery Management."

[1308] Terminal: Sends information about the configured workflow to the server.

[1309] Server: Saves the received business flow information to the database.

[1310] Step 2: Data Entry

[1311] User: Use your device to enter information into the "Order Management" screen (e.g., product code, quantity, delivery date).

[1312] Terminal: Sends the entered order information to the server.

[1313] Server: Stores order information in the database.

[1314] Step 3: Processing by Generator AI

[1315] Server: Receives data from the database and passes it to the AI ​​for inventory checks and ordering instructions.

[1316] Server: Saves the processing results of the generated AI (inventory check results and order details) to the database.

[1317] Server: Notifies the user's terminal of the processing results.

[1318] Step 4: Review the results and take appropriate action.

[1319] User: Check the processing results notified on the device and make corrections or approvals as necessary.

[1320] Terminal: Sends user modifications and approvals to the server.

[1321] Server: Reflects changes and approvals in the database.

[1322] Responding to inquiries from the field.

[1323] Step 1: Enter your inquiry

[1324] User: Enter the inquiry details from the field into the terminal and send it (e.g., "I don't know today's work procedure").

[1325] Terminal: Sends the inquiry details to the server.

[1326] Step 2: Inquiry Analysis

[1327] Server: Uses generation AI to analyze inquiry content and extract and generate relevant answers and information.

[1328] Server: Saves the generated responses to the database.

[1329] Step 3: Provide your response

[1330] Server: Sends the answers stored in the database to the user's terminal.

[1331] Terminal: Displays the answer to the inquiry.

[1332] User: Review the displayed answer and proceed with the task.

[1333] Specific example

[1334] Step 1: Setting up the business workflow

[1335] User: The construction site manager logs into the system on their PC and sets up workflows such as "order management," "inventory check," and "delivery management."

[1336] Terminal: Sends configuration information to the server.

[1337] Server: Saves the received data to the database.

[1338] Step 2: Data Entry

[1339] User: The sales representative enters information about a new order into the "Order Management" screen on their terminal.

[1340] Terminal: Sends input data to the server.

[1341] Server: Stores order information in the database.

[1342] Step 3: Processing by Generator AI

[1343] Server: The generation AI checks inventory based on order information and automatically places orders according to the required quantity.

[1344] Server: Saves the results (inventory check and order details) generated by the AI ​​and notifies the user of these results.

[1345] Step 4: Review the results and take appropriate action.

[1346] User: The site manager reviews the results and verifies whether the order details are correct.

[1347] Terminal: Sends user confirmation details to the server.

[1348] Server: Reflect the verification results in the database.

[1349] Examples of how to handle inquiries

[1350] Step 1: Enter your inquiry

[1351] User: Field workers enter their questions about today's work procedures into the terminal and send them.

[1352] Terminal: Sends the inquiry details to the server.

[1353] Step 2: Inquiry Analysis

[1354] Server: The AI ​​generates responses by analyzing the inquiry and producing answers such as, "Today, we will proceed with the work according to the following steps."

[1355] Server: Saves the generated responses to the database.

[1356] Step 3: Provide your response

[1357] Server: Sends the generated response to the user's device.

[1358] Terminal: Displays the answer to the inquiry.

[1359] User: Review the answer and proceed with the task.

[1360] This system enables the digitalization and automation of business processes, as well as providing quick and accurate responses to inquiries from the field.

[1361] (Example 1)

[1362] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1363] Currently, many industries are demanding the digitalization and automation of business procedures, but the labor of field workers and managers, as well as errors caused by manual processes, remain major problems. Furthermore, there are challenges in responding quickly and accurately to inquiries. In particular, industries with many analog operations, such as construction, require increased efficiency in workflows and reduced errors, but achieving this presents significant cost and technical hurdles.

[1364] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1365] This invention includes a server that includes means for automating business procedures using generative artificial intelligence, means for saving user-input data to a database, and means for the generative artificial intelligence to execute business procedures by analyzing the data stored in the database. This enables automation and efficiency of business procedures. It also includes means for the user to input business data using a terminal, means for making inquiries from the field using a terminal, means for the server to analyze the inquiry content using generative artificial intelligence and generate an answer, and means for displaying the generated answer on the user's terminal. This enables a quick and accurate response to inquiries. It also includes means for the user to operate a business flow setting screen via a terminal, means for saving the business flow settings to a database, means for the user to check and modify the saved business flow on a terminal, and means for the business data stored in the database to be sent to the server in real time. This enables easy setting and updating of business flows. It also includes means for the server to automatically perform inventory checks and orders using a generative AI model based on the business data received, means for notifying the user of the generated inventory check and order results, and means for the user to check the notified results and make corrections or approvals as necessary. This achieves efficiency and accuracy in inventory management and ordering operations.

[1366] "Generative artificial intelligence" refers to systems that use machine learning and natural language processing technologies to perform intelligent tasks like humans.

[1367] "Automating business procedures" refers to automatically executing business processes that were previously performed manually, using systems and software.

[1368] A "database" refers to a system for efficiently storing, managing, and retrieving large amounts of data.

[1369] "User" refers to a person who uses this system to input business data, make inquiries, and check the results, or a person with a similar role.

[1370] "Terminal" refers to a hardware device used by a user (e.g., PC, smartphone, tablet).

[1371] A "server" refers to a computer system that plays a central role in storing, managing, and analyzing data, and connecting users and their devices.

[1372] "Inquiry" refers to a question that a user asks via their device to resolve doubts or uncertainties regarding the field or the performance of their work.

[1373] "Answer" refers to information or solutions generated by the server using artificial intelligence and provided to the user.

[1374] The "settings screen" refers to the interface that allows users to configure and modify business workflows and processes.

[1375] "Inventory check" refers to verifying the current inventory status based on inventory information stored in a database.

[1376] "Placement" refers to the business process of ordering necessary goods or materials from suppliers.

[1377] "Notification" refers to the real-time transmission of results or responses generated by the server to the user.

[1378] This invention is a system that digitizes and automates the workflows of industries with many analog operations, such as the construction industry. This system has the function of automating work procedures using generative artificial intelligence, the function of saving and analyzing user-entered data in a database, and the function of responding quickly and accurately to inquiries from the field.

[1379] System configuration and operation

[1380] Digitalization and automation of business processes

[1381] 1. Server

[1382] The server plays a central role in this system. This server incorporates a database (e.g., MySQL) for storing and managing business procedures. The server receives business data sent by users and stores it in the database. It also uses generative artificial intelligence (e.g., GPT-4) to execute automated tasks based on business procedures and notifies the user of the results.

[1383] 2. Terminal

[1384] A terminal is a device used by users to input, verify, and modify business data. Typically, a PC or smart device is used. Data entered on the terminal is transmitted to the server in real time, where it is analyzed and processed.

[1385] 3. User

[1386] Users are field workers or managers who input, verify, and modify business data through terminals. For example, a user might use a PC to input product codes, quantities, and delivery dates on the "Order Management" screen. This data is sent to the server via the terminal, where automated tasks are executed.

[1387] Responding to inquiries from the field.

[1388] 1. User

[1389] Users input inquiries from the field using their devices (PCs, smartphones, etc.). For example, they might input a question like, "What should I do if there is insufficient stock?"

[1390] 2. Terminal

[1391] The terminal sends the inquiry to the server and displays the response sent from the server.

[1392] 3. Server

[1393] The server receives the inquiry and analyzes the content using a generative AI model (e.g., GPT-4). It generates an appropriate response from the analysis results and saves it to a database. The generated response is notified to the user in real time. For example, a response such as "If inventory is low, an additional order is required" might be provided.

[1394] Specific example of the operation flow

[1395] 1. Setting up the business workflow

[1396] Users access the workflow settings screen using their PCs and configure business processes such as "order management," "inventory check," and "delivery management."

[1397] The server saves these settings to the database.

[1398] The terminal displays the workflow configured by the user and allows them to modify it as needed.

[1399] 2. Data entry and automation

[1400] The user enters order information into the "Order Management" screen using their device. For example, they might enter the product code, quantity, and delivery date.

[1401] The terminal sends the entered information to the server.

[1402] The server saves order information to a database and uses AI to automatically check inventory and place necessary orders. The results are saved in the database and notified to the user.

[1403] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[1404] 3. Handling inquiries

[1405] Users input inquiries from the field using a terminal and send questions, for example, about "today's work procedures."

[1406] The terminal sends the inquiry details to the server.

[1407] The server uses AI to analyze the inquiry and generate an appropriate response. For example, it may provide instructions on how to perform tasks or answers to related FAQs.

[1408] The responses generated by the server are stored in a database and notified to the user in real time.

[1409] The user reviews the answers displayed on their device and incorporates that information into their work.

[1410] Example of a prompt

[1411] "Product code: ABC123, Quantity: 10, Delivery date: 2023-10-15. Please check inventory and process the order for this item."

[1412] "Please tell me today's work procedure."

[1413] As a result, this system digitizes and automates business processes, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[1414] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1415] Step 1:

[1416] The user enters business data using a terminal. For example, they enter the product code, quantity, and delivery date. Specifically, the entered data is product code "ABC123", quantity "10", and delivery date "2023-10-15".

[1417] input:

[1418] Product code, quantity, delivery date

[1419] output:

[1420] Input data displayed on the terminal

[1421] Step 2:

[1422] The terminal sends the entered business data to the server. The data is sent to the server as an HTTP POST request. Specifically, the data sent from the terminal includes the product code "ABC123", quantity "10", and delivery date "2023-10-15".

[1423] input:

[1424] Business data entered into the terminal

[1425] output:

[1426] Business data sent to the server

[1427] Step 3:

[1428] The server analyzes the received business data and saves it to the database. Specifically, the server saves the product code "ABC123", quantity "10", and delivery date "2023-10-15" to the MySQL database.

[1429] input:

[1430] Business data sent to the server

[1431] output:

[1432] Business data stored in the database

[1433] Step 4:

[1434] The server uses a generated AI model (e.g., GPT-4) based on the stored data to check inventory and automatically place necessary orders. For example, the AI ​​model might determine that "there are 50 units in stock, so no additional orders are needed."

[1435] input:

[1436] Business data stored in the database

[1437] Inventory data required by the generative AI model

[1438] output:

[1439] The decision was made that an order is not necessary.

[1440] Step 5:

[1441] The server saves the results of tasks automated by the generated AI model to a database and notifies the user of those results. For example, a notification such as "Inventory check results indicate no additional orders are needed" is sent via email or system notification.

[1442] input:

[1443] Inventory check results

[1444] output:

[1445] Results notified to the user

[1446] Step 6:

[1447] The user checks the notification results using their device. If necessary, they can modify or approve the results on the system screen. For example, the user might check a notification on their smartphone stating "No additional order is needed" and approve it without making any changes.

[1448] input:

[1449] Notified results

[1450] output:

[1451] User verification and modification / approval results

[1452] Step 7:

[1453] Users input inquiries from the field using a terminal. For example, they might input a question like, "What are today's work procedures?"

[1454] input:

[1455] Inquiry details

[1456] output:

[1457] Inquiry content displayed on the device

[1458] Step 8:

[1459] The terminal sends the inquiry details to the server. The data is sent to the server as an HTTP POST request.

[1460] input:

[1461] Inquiry content entered on the terminal

[1462] output:

[1463] Inquiry content sent to the server

[1464] Step 9:

[1465] The server receives the inquiry and analyzes the content using a generation AI model. An appropriate answer is generated from the analysis results. For example, the AI ​​model might generate the answer: "Today's work procedure is as follows: 1. Arrive at the site 2. Prepare equipment 3. Begin work."

[1466] input:

[1467] Inquiry content sent to the server

[1468] Business procedure data required by the generated AI model

[1469] output:

[1470] Generated answer

[1471] Step 10:

[1472] The server saves the generated response to a database and notifies the user in real time. For example, the response might say, "Today's work procedure is as follows."

[1473] input:

[1474] Generated answer

[1475] output:

[1476] Responses notified to the user

[1477] Step 11:

[1478] The user checks the answers displayed on the device and incorporates that information into their work. For example, they might start on-site work following the work procedure displayed on the device.

[1479] input:

[1480] Notified response

[1481] output:

[1482] Tasks performed by the user

[1483] As a result, this system digitizes and automates business processes, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[1484] (Application Example 1)

[1485] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1486] In existing factory operations, work procedures and workflows are often managed manually, resulting in insufficient efficiency and automation. This leads to problems such as manual errors, wasted time, and delays in responding to inquiries, ultimately reducing productivity and quality. The objective of this invention is to solve these problems and realize the digitalization and automation of workflows.

[1487] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1488] In this invention, the server includes means for automating work procedures using generative artificial intelligence, means for storing user-input data in a database, means for transmitting data to the server in real time, means for optimizing work procedures using generative AI, and means for automating operations on a factory production line. This enables more efficient workflows, reduced errors, and faster response times to inquiries.

[1489] "Generative artificial intelligence" is an advanced artificial intelligence technology used to automate business procedures, analyze data, and generate appropriate responses.

[1490] A "database" is a digital information repository where information such as business data, workflows, and inquiry details are centrally managed and stored and analyzed as needed.

[1491] "A means of sending data to a server in real time" refers to a system configuration that instantly sends data entered by a user to a server, enabling immediate processing and analysis of the data.

[1492] "Generative AI" is a type of artificial intelligence technology that automatically provides appropriate responses and optimizes work procedures based on user questions and data.

[1493] "Methods for optimizing work procedures" refers to technologies that use generative AI to automatically plan and propose efficient and error-free work procedures.

[1494] "Methods for automating factory production line operations" refer to systems in which robots and automated equipment perform production activities without human intervention, based on business flows and work procedures stored in a database.

[1495] "Users" refer to people such as field workers and managers who input and verify business data and use the system to perform their duties.

[1496] A "terminal" is a device used by users to input, verify, and modify business data, and includes PCs and smartphones.

[1497] A "server" is a computer system that plays a central role in this system, comprehensively managing data storage and analysis, execution of generating AI, and notification of results.

[1498] This invention is a system aimed at automating and digitizing work procedures and workflows in factories. This system stores user-inputted data in a database, and based on that data, generative artificial intelligence (generative AI) optimizes and automatically executes work procedures. It also includes means for sharing work procedures with robots within the factory and for quickly responding to inquiries from the factory floor.

[1499] Hardware and software configuration

[1500] server

[1501] The server plays a central role in the system. It performs the following functions:

[1502] Data Storage: User-entered data is saved to a database. SQLite is used as the database.

[1503] Data Analysis: Analyze data stored in the database and optimize work procedures using generative AI. OpenAI's GPT-3 is used for generative AI.

[1504] Result Notification: Notifies the user of the results generated by the AI.

[1505] terminal

[1506] A terminal is a device used by users to input, verify, and modify business data. It has the following functions:

[1507] Data entry: Provide a screen for entering business data. This could be a smartphone or computer, for example.

[1508] Inquiry Submission: A function that allows users to input inquiries from the field and send them to the server.

[1509] Results display: Displays notifications from the server and responses generated by the AI ​​in real time.

[1510] robot

[1511] The robots in the factory are responsible for automatically performing tasks based on work procedures shared from a server. The robots perform the following functions:

[1512] Task Execution: Perform tasks on the production line according to the specified work procedures.

[1513] Data transmission: Sends the progress of the work to the server in real time.

[1514] Specific examples of actions

[1515] Setting up business workflows

[1516] 1. Users access the business workflow settings screen using their smartphones. For example, they can set up business processes such as "order management," "inventory check," and "delivery management."

[1517] 2. The server saves these settings to the database.

[1518] Data entry and automation

[1519] 1. The user enters order information into the "Order Management" screen using their terminal. For example, they enter information such as product code, quantity, and delivery date.

[1520] 2. The terminal sends the entered information to the server.

[1521] 3. The server stores order information in a database and uses AI generation to automatically check inventory and place necessary orders.

[1522] 4. The server saves the results to the database and notifies the user.

[1523] 5. The user checks the notified results on their device and makes corrections or approvals as necessary.

[1524] Inquiry response

[1525] 1. Users input inquiries from the field using a terminal and send, for example, "Today's work procedure."

[1526] 2. The terminal sends the inquiry details to the server.

[1527] 3. The server uses a generation AI to analyze the inquiry and generate an appropriate response. For example, it may provide a work procedure guide or answers to related FAQs.

[1528] 4. The server saves the generated responses to a database and notifies the user in real time.

[1529] 5. The user reviews the answers displayed on the device and incorporates them into their work.

[1530] Example of a prompt

[1531] Working process:

[1532] Product order registration

[1533] Check stock availability

[1534] Order Placement

[1535] Preparation for delivery

[1536] Question: Please explain today's work procedure.

[1537] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1538] Step 1:

[1539] Users access the workflow settings screen using their smartphones. Users configure business processes such as "order management," "inventory check," and "delivery management."

[1540] Input: Business flow settings (e.g., order management, inventory check, delivery management)

[1541] Operation: Entering content on the business flow settings screen.

[1542] Output: Data from the configured business flow

[1543] Step 2:

[1544] The server saves the user's entered settings to a database.

[1545] Input: Data from the configured business flow

[1546] Operation: Saving flow configuration data to the database

[1547] Output: Saved business flow data

[1548] Step 3:

[1549] The user uses a terminal to enter order information into the "Order Management" screen. For example, they enter information such as product code, quantity, and delivery date.

[1550] Input: Order information (product code, quantity, delivery date, etc.)

[1551] Operation: Entering order information on the screen

[1552] Output: Input order data

[1553] Step 4:

[1554] The terminal sends the entered information to the server.

[1555] Input: Entered order data

[1556] Operation: Sending data to the server

[1557] Output: Order data received by the server

[1558] Step 5:

[1559] The server stores order information in a database and uses AI generation to automatically check inventory and place necessary orders.

[1560] Input: Order data received by the server

[1561] Operation: Saves order information to the database and uses AI to check inventory and automatically place orders.

[1562] Output: Inventory status, order placement information

[1563] Step 6:

[1564] The server saves the results to the database and notifies the user.

[1565] Input: Inventory status, order placement information

[1566] Operation: Save results to a database and notify the user.

[1567] Output: Processing results notified to the user

[1568] Step 7:

[1569] Users can check the notified results on their devices and make corrections or approvals as needed.

[1570] Input: Processing result notified to the user

[1571] Action: Review results, make necessary corrections and approvals.

[1572] Output: Corrected and approved data

[1573] Step 8:

[1574] Users input inquiries from the field using a terminal and send, for example, "Today's work procedure."

[1575] Input: Inquiry details (e.g., "Today's work procedure")

[1576] Operation: Input and send inquiry content to the terminal.

[1577] Output: Query content sent to the server

[1578] Step 9:

[1579] The server uses a generation AI to analyze the inquiry and generate an appropriate response.

[1580] Input: Inquiry received by the server

[1581] Operation: Analysis of inquiry content and generation of answers using a generation AI.

[1582] Output: Generated answer

[1583] Step 10:

[1584] The server saves the generated responses to a database and notifies the user in real time.

[1585] Input: Generated answer

[1586] Operation: Saves responses to the database and provides real-time notifications to users.

[1587] Output: Response notified to the user

[1588] Step 11:

[1589] The user checks the answers displayed on their device and incorporates that information into their work.

[1590] Input: Response notified to the user

[1591] Action: Confirmation of notified responses and implementation of the work.

[1592] Output: Results of the work

[1593] This enables the efficient execution of a series of processes and achieves the automation and digitalization of the workflow and work procedures within the factory.

[1594] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1595] This invention relates to a system for digitizing and automating business workflows by combining an emotion engine. This system uses generative artificial intelligence to automate business procedures and leverages user emotion data to provide more appropriate and effective support.

[1596] System configuration and operation

[1597] Digitalization and automation of business processes

[1598] Server: This server plays a central role in this system. It incorporates a database for storing work procedures, generative artificial intelligence, and an emotion engine for analyzing user sentiment data. The server receives work data sent by users and stores it in the database. It also uses generative artificial intelligence to execute automated tasks based on work procedures and notifies the user of the results.

[1599] Terminal: A device (e.g., PC or smart device) used by users to input, verify, and modify business data. Data entered on the terminal is sent to the server in real time, where it is analyzed and processed. In addition, user emotional data is collected in conjunction with the emotion engine.

[1600] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[1601] Collection and analysis of emotional data

[1602] Server: The emotion engine collects emotional data from the user's facial expressions, voice, and language use, and analyzes this data. The analysis results are fed back to the generating AI and used to adjust work procedures and the content of responses to inquiries.

[1603] Terminal: Along with the business data entered by the user, the emotion engine sends collected emotion data to the server. The user's emotion data is analyzed in real time, and the results are reflected in the progress of the work.

[1604] Specific examples of operation

[1605] Setting up business workflows

[1606] Users access a workflow configuration screen using their PCs and set up processes such as "order management," "inventory check," and "delivery management."

[1607] The terminal sends information about the configured workflow to the server.

[1608] The server saves the received business flow information to the database.

[1609] Data entry and automation

[1610] The user enters information into the "Order Management" screen using their device (e.g., product code, quantity, delivery date).

[1611] The device sends the entered information to the server. Simultaneously, the emotion engine collects the user's emotional data.

[1612] The server stores order information and sentiment data in a database and uses a generating AI to check inventory and issue ordering instructions. The results are stored in the database and notified to the user.

[1613] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[1614] Use of emotional data

[1615] Server: Based on the user's emotional data analyzed by the emotion engine, the generating AI adjusts the work procedures and responses. For example, if a user is feeling stressed, it can suggest simplifying the operation.

[1616] Device: By displaying emotional data in real time while the user is operating the device, administrators can more easily provide appropriate support.

[1617] Responding to inquiries from the field.

[1618] The user enters the content of the inquiry from the field into the terminal and sends it (e.g., "Question about today's work procedure").

[1619] The device sends the inquiry details to the server. Simultaneously, the emotion engine collects the user's emotional data.

[1620] The server uses a generative AI to analyze the inquiry content and sentiment data, and generates an appropriate response. For example, if the user is feeling anxious, it will provide a response that takes that into consideration.

[1621] The responses generated by the server are stored in a database and notified to the user in real time.

[1622] The user checks the answers displayed on the device and incorporates that information into their work.

[1623] This enables the system to digitize and automate business processes, as well as provide prompt and accurate support through user sentiment data. This results in reduced manual errors, increased operational efficiency, and higher user satisfaction.

[1624] The following describes the processing flow.

[1625] Program processing

[1626] Digitalization and automation of business processes

[1627] Step 1: Setting up the business workflow

[1628] User: Use a PC to access the workflow settings screen and configure workflows such as "Order Management," "Inventory Check," and "Delivery Management."

[1629] Terminal: Sends information about the configured workflow to the server.

[1630] Server: Saves the received business flow information to the database.

[1631] Step 2: Data Entry

[1632] User: Use your device to enter information into the "Order Management" screen (e.g., product code, quantity, delivery date).

[1633] Terminal: Sends the entered order information to the server.

[1634] Server: Stores order information in the database.

[1635] Step 3: Collecting emotional data

[1636] Terminal: While the user is inputting data, the terminal's camera and microphone are used to collect facial expressions and voice.

[1637] Server: Analyzes facial expressions and voice data sent from terminals using an emotion engine and generates emotion data.

[1638] Server: Stores emotional data in a database.

[1639] Step 4: Processing by Generator AI

[1640] Server: Passes business data and emotional data received from the database to the AI ​​for inventory checks and ordering instructions.

[1641] Server: Saves the processing results of the generated AI (inventory check results and order details) to the database.

[1642] Server: Notifies the user's terminal of the processing results.

[1643] Step 5: Review the results and take appropriate action.

[1644] User: Check the processing results notified on the device and make corrections or approvals as necessary.

[1645] Terminal: Sends user modifications and approvals to the server.

[1646] Server: Reflects changes and approvals in the database.

[1647] Responding to inquiries from the field.

[1648] Step 1: Enter your inquiry

[1649] User: Enter the inquiry details from the field into the terminal and send it (e.g., "I don't know today's work procedure").

[1650] Terminal: Sends the inquiry details to the server.

[1651] Step 2: Analyzing inquiry and sentiment data

[1652] Terminal: Collects facial expressions and voice data from the user while they are entering their inquiry, and sends it to the server.

[1653] Server: The emotion engine analyzes the user's facial expressions and voice data to generate emotion data.

[1654] Server: Uses emotional data to generate inquiry content. An AI analyzes the data and generates relevant answers and information.

[1655] Server: Saves the generated responses to the database.

[1656] Step 3: Provide your response

[1657] Server: Sends the generated response to the user's device.

[1658] Terminal: Displays the answer to the inquiry.

[1659] User: Review the displayed answer and proceed with the task.

[1660] Specific example

[1661] Step 1: Setting up the business workflow

[1662] User: The construction site manager logs into the system on their PC and sets up workflows such as "order management," "inventory check," and "delivery management."

[1663] Terminal: Sends configuration information to the server.

[1664] Server: Saves the received data to the database.

[1665] Step 2: Data Entry

[1666] User: The sales representative enters information about a new order into the "Order Management" screen on their terminal.

[1667] Terminal: Sends input data to the server.

[1668] Server: Stores order information in the database.

[1669] Step 3: Collecting emotional data

[1670] Terminal: The camera and microphone collect the facial expressions and voices of sales representatives entering order information.

[1671] Server: The emotion engine analyzes the collected data and generates emotion data.

[1672] Server: Stores emotional data in a database.

[1673] Step 4: Processing by Generator AI

[1674] Server: The generating AI checks inventory based on order information and sentiment data, and automatically places orders according to the required quantity.

[1675] Server: Saves the results (inventory check and order details) generated by the AI ​​and notifies the user of these results.

[1676] Step 5: Review the results and take appropriate action.

[1677] User: The site manager reviews the results and verifies whether the order details are correct.

[1678] Terminal: Sends user confirmation details to the server.

[1679] Server: Reflect the verification results in the database.

[1680] Examples of how to handle inquiries

[1681] Step 1: Enter your inquiry

[1682] User: Field workers enter their questions about today's work procedures into the terminal and send them.

[1683] Terminal: Sends the inquiry details to the server.

[1684] Step 2: Analyzing inquiry and sentiment data

[1685] Terminal: Collects facial expressions and voice recordings from the user while they are entering their inquiry and sends them to the server.

[1686] Server: The emotion engine analyzes facial expressions and voice data to generate emotion data.

[1687] Server: The generation AI analyzes the inquiry content and sentiment data to generate an appropriate response.

[1688] Step 3: Provide your response

[1689] Server: Saves the generated response to the database and notifies the user.

[1690] Terminal: Displays the answer to the inquiry.

[1691] User: Review the answer and proceed with the task.

[1692] This enables the system to digitize and automate business processes, while also providing meticulous support that takes user emotions into consideration.

[1693] (Example 2)

[1694] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1695] Conventional business process management systems have suffered from inefficiency due to the frequent use of manual operations. Furthermore, they often fail to consider user emotions when providing procedures and support, resulting in low user satisfaction. This invention aims to provide a system that achieves high efficiency and user satisfaction by automating business procedures and utilizing user emotion data.

[1696] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1697] In this invention, the server includes means for automating work procedures using generative artificial intelligence, means for saving user-inputted data to a database, and means for analyzing the data stored in the database and having the generative artificial intelligence execute the work procedures. By combining this with means for collecting and analyzing user emotional data and means for adjusting work procedures based on emotional data, rapid and accurate support becomes possible.

[1698] "Generative artificial intelligence" is a type of artificial intelligence that performs self-learning based on given data to optimize and automate business procedures.

[1699] "Business procedures" refer to a series of steps and procedures necessary to perform a specific task or process.

[1700] A "database" is a system for organizing and storing data, allowing for the quick retrieval of necessary information.

[1701] "Emotional data" refers to information that indicates a user's emotional state, obtained from their facial expressions, voice, and choice of words.

[1702] An "emotion engine" is a part of the software or hardware used to collect and analyze emotional data.

[1703] A "server" is a computer system used to store, process, and transmit data over a network.

[1704] A "terminal" is a device (e.g., a PC or smart device) used by a user to input, verify, and modify business data.

[1705] "Analysis" is the process of examining data in detail and finding its meaning and patterns.

[1706] "Notification" refers to the act of a system informing a user of processing results or other information.

[1707] This invention relates to a system for digitizing and automating business workflows by combining an emotion engine. This system uses generative artificial intelligence (generative AI) to automate business procedures and leverages user emotion data to provide more appropriate and effective support.

[1708] Digitalization and automation of business processes

[1709] Server Configuration

[1710] The server plays a central role in this system. It incorporates a database for storing work procedures, generative artificial intelligence, and an emotion engine for analyzing user sentiment data. The server receives work data sent by users and stores it in the database. It also uses generative AI to execute automated tasks based on work procedures and notifies the user of the results.

[1711] Device configuration

[1712] These are devices (e.g., PCs and smart devices) that users use to input, verify, and modify business data. Data entered on the terminal is transmitted to the server in real time, where it is analyzed and processed. Furthermore, user emotional data is collected in conjunction with an emotion engine.

[1713] Collection and analysis of emotional data

[1714] Collection of emotional data

[1715] The device collects emotional data in real time through facial expressions and voice during user interaction. For example, it uses a facial recognition camera and microphone. The collected emotional data is sent to a server.

[1716] Analysis of emotional data

[1717] The server uses an emotion engine to analyze the received emotional data. The analysis results are fed back to the generating AI, which adjusts the work procedures and responses according to the user's emotions.

[1718] Specific examples of operation

[1719] Setting up business workflows

[1720] User: Access the workflow settings screen using a PC and configure processes such as "Order Management," "Inventory Check," and "Delivery Management."

[1721] Terminal: Sends information about the configured workflow to the server.

[1722] Server: Saves the received business flow information to the database.

[1723] Data entry and automation

[1724] User: Use the terminal to enter information into the "Order Management" screen. For example, enter order information such as product code, quantity, and delivery date.

[1725] Terminal: Collects emotional data along with the entered order information and sends it to the server.

[1726] Server: Stores submitted order information and sentiment data in a database and uses generated AI to check inventory and issue ordering instructions. For example, it automatically instructs ordering procedures for items with insufficient stock.

[1727] Server: Stores inventory check and order instruction results in a database and notifies users.

[1728] User: Review the results notified via the device and make corrections or approvals as necessary.

[1729] Use of emotional data

[1730] Server: Based on the user's emotional data analyzed by the emotion engine, the generating AI adjusts the work procedures and responses. For example, if a user is feeling stressed, it can suggest simplifying the operation.

[1731] Terminal: Displays emotional data in real time while the user is operating the device, making it easier for administrators to provide appropriate support.

[1732] Responding to inquiries from the field.

[1733] Inquiry reception

[1734] User: Enter the inquiry from the field into the terminal and send it. For example, enter "Question about today's work procedure."

[1735] Terminal: Sends emotional data along with the inquiry content to the server.

[1736] Answer generation

[1737] Server: Uses a generation AI to analyze inquiry content and sentiment data to generate appropriate responses. For example, if anxiety is felt, it will create content that provides reassurance.

[1738] Submit and confirm your response.

[1739] Server: Generated responses are stored in a database and users are notified in real time.

[1740] User: Check the answers on the device and incorporate the information into the work.

[1741] Example of a prompt

[1742] "The generating AI checks the inventory of product code 12345 and issues order instructions as needed."

[1743] "If a user is feeling anxious, we will provide an answer that takes that into consideration."

[1744] "Generate suggestions to simplify operations for users who are experiencing stress."

[1745] This enables efficient and user-satisfying business operations through detailed procedures and specific actions.

[1746] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1747] Step 1:

[1748] Users access a business workflow settings screen and configure business procedures such as "order management," "inventory check," and "delivery management." For example, in "order management," a user might input "product code," "quantity," and "delivery date." The entered data is then used to configure the business workflow settings.

[1749] Input: Business flow configuration information (e.g., product code, quantity, delivery date)

[1750] Output: Configured business workflow (e.g., order management)

[1751] Step 2:

[1752] The terminal transmits information about the user's configured workflow to the server in real time. This transmission transfers the configuration information to the server.

[1753] Input: Configured business flow information (e.g., order management information)

[1754] Output: Business flow information sent to the server

[1755] Step 3:

[1756] The server saves the received business flow information to a database. This saving process allows configuration information to be accumulated in the database and made available for later processing.

[1757] Input: Business flow information sent to the server (e.g., order management information)

[1758] Output: Business flow information stored in the database

[1759] Step 4:

[1760] The user enters information into the "Order Management" screen based on the configured workflow. For example, they might enter product code "12345", quantity "100", and delivery date "next Monday". The entered data is then compiled into order information.

[1761] Input: Order information (e.g., product code, quantity, delivery date)

[1762] Output: Entered order information

[1763] Step 5:

[1764] The terminal collects emotional data in real time along with the entered order information and sends it to the server. The terminal collects emotional data using a facial recognition camera and microphone.

[1765] Input: Order information and emotional data (e.g., user's facial expressions, voice)

[1766] Output: Order information and sentiment data sent to the server

[1767] Step 6:

[1768] The server stores the submitted order information and sentiment data in a database.

[1769] Input: Order information and sentiment data

[1770] Output: Order information and sentiment data stored in the database

[1771] Step 7:

[1772] The server uses a generating AI based on stored order information to check inventory and issue ordering instructions. For example, the generating AI automatically instructs ordering processes for products with insufficient stock. The analysis results are stored in a database.

[1773] Input: Order information stored in the database

[1774] Output: Inventory check results and order instructions

[1775] Step 8:

[1776] The server stores the results of inventory checks and order instructions in a database, generates notification information, and notifies the user.

[1777] Input: Inventory check results and order instructions

[1778] Output: Notification Information

[1779] Step 9:

[1780] Users review the results notified via their devices and make corrections or approvals as needed. For example, a user might make changes based on inventory check results.

[1781] Input: Notification information

[1782] Output: Corrected or approved information

[1783] Step 10:

[1784] The device collects emotional data in real time through facial expressions and voice while the user is operating it. For example, it uses a facial recognition camera and microphone.

[1785] Input: User's facial expressions, voice

[1786] Output: Collected sentiment data

[1787] Step 11:

[1788] The device sends the collected emotional data to the server.

[1789] Input: Collected emotional data

[1790] Output: Sentiment data sent to the server

[1791] Step 12:

[1792] The server uses an emotion engine to analyze the received emotional data. The analysis results are fed back to the generating AI, which adjusts the work procedures and responses according to the user's emotions.

[1793] Input: Collected emotional data

[1794] Output: Analysis results and feedback information

[1795] Step 13:

[1796] The user enters the inquiry details from the field into the terminal and sends it. For example, they might enter "A question about today's work procedure."

[1797] Input: Inquiry details

[1798] Output: Inquiry content entered into the terminal

[1799] Step 14:

[1800] The device sends emotion data along with the inquiry content to the server.

[1801] Input: Inquiry details and sentiment data

[1802] Output: Query content and sentiment data sent to the server

[1803] Step 15:

[1804] The server uses a generative AI to analyze the inquiry content and sentiment data, and generates an appropriate response. For example, if the user is feeling anxious, it will create a response that provides reassurance.

[1805] Input: Inquiry details and sentiment data

[1806] Output: Generated answer

[1807] Step 16:

[1808] The server stores the generated responses in a database and notifies the user in real time.

[1809] Input: Generated answer

[1810] Output: Notified response

[1811] Step 17:

[1812] Users review their responses on their devices and incorporate that information into their work. For example, a user might modify their work procedures based on the generated responses.

[1813] Input: Notified response

[1814] Output: Answers reflected in the work

[1815] (Application Example 2)

[1816] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1817] The present invention aims to provide a system that digitizes and automates business workflows, while also understanding user emotions in real time and providing personalized support. Conventional systems have struggled to respond while considering user emotions, resulting in problems with operational efficiency and user satisfaction. In particular, it is necessary to provide appropriate support according to emotional states to improve operational efficiency, reduce errors, and achieve high user satisfaction.

[1818] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1819] In this invention, the server includes means for collecting and analyzing emotional data, means for providing personalized support to the user based on the emotional data, and means for providing appropriate responses based on the user's emotional data. This makes it possible to grasp the user's emotions in real time and provide appropriate support quickly.

[1820] "Generative artificial intelligence" refers to an artificial intelligence system that automatically executes tasks in response to business procedures and user inquiries, and generates appropriate answers and results.

[1821] "Emotional data" refers to information that represents a user's emotional state, obtained from their facial expressions, voice, and choice of words.

[1822] An "emotion engine" is a system that collects and analyzes user emotional data and uses the results to adjust work procedures and support content.

[1823] "Personalized support" refers to specific assistance and content provided according to each user's individual emotional state and needs.

[1824] A "terminal" is a device used by a user to input, verify, and modify business data.

[1825] A "database" is an information management system used to centrally store and manage business procedures, user input data, emotional data, and other similar information.

[1826] A "business process flow" is a sequence of processes and tasks that make up a business procedure.

[1827] A "server" is a central processing unit that processes and analyzes business procedures and emotional data, and manages and notifies the generated results.

[1828] An "inquiry" is a question or request made by a user to seek support or address doubts regarding the work environment or procedures.

[1829] An "answer" is a response to a generated inquiry, providing appropriate solutions and information to the user's questions or requests.

[1830] This invention is a system for digitizing and automating business workflows using a combination of generative AI and an emotion engine. This system utilizes the following hardware and software to enhance user work efficiency and provide personalized support.

[1831] System configuration and operation

[1832] Digitalization and automation of business processes

[1833] Server: Plays a central role in the system. The server incorporates a database for storing business procedures, a generative AI model, and an emotion engine. The server receives business data sent by users and stores it in the database. It also uses generative AI to execute automated tasks based on business procedures and notifies the user of the results.

[1834] Software used: Database management system (e.g., MySQL), AI model (e.g., TensorFlow / Keras), request processing (e.g., Flask).

[1835] Terminal: A device used by users to input, verify, and modify business data (e.g., PC or smart device). Data entered on the terminal is sent to the server in real time, where it is analyzed and processed. It also has a function to collect user emotion data in conjunction with the emotion engine.

[1836] Software to be used: Face recognition libraries (e.g., OpenCV, dlib), emotion recognition models (e.g., TensorFlow / Keras).

[1837] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[1838] Collection and analysis of emotional data

[1839] Server: The emotion engine collects emotional data from the user's facial expressions, voice, and language use, and analyzes this data. The analysis results are fed back to the generating AI and used to adjust work procedures and the content of responses to inquiries.

[1840] Software to be used: Emotion recognition library (e.g., TensorFlow / Keras).

[1841] Terminal: Along with the business data entered by the user, the emotion engine sends collected emotion data to the server. The user's emotion data is analyzed in real time, and the results are reflected in the progress of the work.

[1842] Specific example

[1843] For example, when a user is searching for products in a virtual store, their smartphone camera captures their facial expressions, and an emotion engine detects that the user is having trouble. This information is sent to a server, and an appropriate support message is displayed.

[1844] Example of a prompt:

[1845] "Based on emotion recognition, generate appropriate support messages to display when a user is experiencing difficulties."

[1846] This allows the system to understand users' emotions in real time and provide appropriate support. In addition, the digitalization and automation of workflows improves user work efficiency, reduces errors, and enables faster task completion.

[1847] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1848] Step 1:

[1849] Terminal: Users input business data. Specifically, users use a terminal (PC or smart device) to input information such as product code, quantity, and delivery date into the order management screen. The entered data is temporarily stored on the terminal.

[1850] Input: Business data entered by the user (e.g., product code, quantity, delivery date)

[1851] Output: Business data temporarily stored on the terminal

[1852] Step 2:

[1853] Terminal: Sends entered business data to the server. Simultaneously, it uses the terminal's camera to capture user facial data and collects emotional data in real time using an emotion engine. The collected emotional data is also sent to the server.

[1854] Input: Business data, user facial expression data

[1855] Output: Business data and sentiment data sent to the server

[1856] Step 3:

[1857] Server: Stores received business data and sentiment data in the database. Business data is stored according to the business flow, and sentiment data is stored linked to the user session.

[1858] Input: Business data and emotional data sent from the terminal.

[1859] Output: Business data and sentiment data stored in the database

[1860] Step 4:

[1861] Server: Analyzes stored business data using a generation AI model and automatically generates necessary business procedures. It also adjusts the workflow as needed based on emotional data. For example, if a user is experiencing stress, it simplifies the business procedures.

[1862] Input: Business data and emotional data stored in the database

[1863] Output: Business procedures and adjusted workflows analyzed and generated by the AI ​​model.

[1864] Step 5:

[1865] Server: Executes the generated business procedures. Specifically, it automates tasks such as inventory checks and order placement, and generates the results.

[1866] Input: Generated business procedure

[1867] Output: Automated task results (e.g., inventory check results, order instructions)

[1868] Step 6:

[1869] Server: Notifies the user of the results of automated tasks. Simultaneously, it generates appropriate feedback and support messages for the user based on sentiment data. For example, if the user is having trouble, it displays a support message to help resolve the issue.

[1870] Input: Automated task results, sentiment data

[1871] Output: Results notified to the user, support messages

[1872] Step 7:

[1873] User: Check the results and support messages notified on the device. Modify or approve the results as needed.

[1874] Input: Notified results, support message

[1875] Output: User review, modification, and approval of results

[1876] This enables the system to provide swift and accurate support within a digitized workflow, while taking user emotions into consideration.

[1877] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1878] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1879] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1880] [Fourth Embodiment]

[1881] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1882] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1883] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1884] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1885] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1886] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1887] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1888] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1889] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1890] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1891] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1892] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1893] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1894] This invention is a system that digitizes and automates the workflows of industries with many analog operations, such as the construction industry. This system has the function of automating work procedures using generative artificial intelligence, the function of saving and analyzing user-entered data in a database, and the function of responding quickly and accurately to inquiries from the field.

[1895] System configuration and operation

[1896] Digitalization and automation of business processes

[1897] Server: This server plays a central role in this system. It incorporates a database for storing and managing business procedures. The server receives business data sent by users and stores it in the database. It also uses generative artificial intelligence to execute automated tasks based on business procedures and notifies users of the results.

[1898] Terminal: A device (e.g., PC or smart device) used by users to input, verify, and modify business data. Data entered on the terminal is sent to the server in real time, where it is analyzed and processed.

[1899] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[1900] Responding to inquiries from the field.

[1901] Server: Receives the inquiry content and analyzes it using a generation AI. Generates an appropriate answer from the analysis results and saves that answer in the database. The generated answer is notified to the user in real time.

[1902] Terminal: This is the device on which the user enters and submits their inquiry. It displays the response sent from the server.

[1903] User: Inputs and sends inquiries from the field using a terminal, and checks the generated response.

[1904] Specific examples of operation

[1905] Setting up business workflows

[1906] Users access the workflow settings screen using their PCs. For example, they can configure business processes such as "order management," "inventory check," and "delivery management."

[1907] The server saves these settings to the database.

[1908] The terminal displays the workflow configured by the user and allows them to modify it as needed.

[1909] Data entry and automation

[1910] The user uses a terminal to enter order information into the "Order Management" screen. For example, they might enter the product code, quantity, delivery date, etc.

[1911] The terminal sends the entered information to the server.

[1912] The server stores order information in a database and uses AI to automatically check inventory and place necessary orders. The results are stored in the database and notified to the user.

[1913] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[1914] Inquiry response

[1915] Users input inquiries from the field using a terminal and send questions, for example, about "today's work procedures."

[1916] The terminal sends the inquiry details to the server.

[1917] The server uses generation AI to analyze the inquiry and generate an appropriate response. For example, it can provide instructions for work procedures or answers to related FAQs.

[1918] The responses generated by the server are stored in a database and notified to the user in real time.

[1919] The user checks the answers displayed on the device and incorporates that information into their work.

[1920] This system digitizes and automates business processes using the procedures described above, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[1921] The following describes the processing flow.

[1922] Program processing

[1923] Digitalization and automation of business processes

[1924] Step 1: Setting up the business workflow

[1925] User: Access the workflow settings screen using a PC and configure workflows such as "Order Management," "Inventory Check," and "Delivery Management."

[1926] Terminal: Sends information about the configured workflow to the server.

[1927] Server: Saves the received business flow information to the database.

[1928] Step 2: Data Entry

[1929] User: Use your device to enter information into the "Order Management" screen (e.g., product code, quantity, delivery date).

[1930] Terminal: Sends the entered order information to the server.

[1931] Server: Stores order information in the database.

[1932] Step 3: Processing by Generator AI

[1933] Server: Receives data from the database and passes it to the AI ​​for inventory checks and ordering instructions.

[1934] Server: Saves the processing results of the generated AI (inventory check results and order details) to the database.

[1935] Server: Notifies the user's terminal of the processing results.

[1936] Step 4: Review the results and take appropriate action.

[1937] User: Check the processing results notified on the device and make corrections or approvals as necessary.

[1938] Terminal: Sends user modifications and approvals to the server.

[1939] Server: Reflects changes and approvals in the database.

[1940] Responding to inquiries from the field.

[1941] Step 1: Enter your inquiry

[1942] User: Enter the inquiry details from the field into the terminal and send it (e.g., "I don't know today's work procedure").

[1943] Terminal: Sends the inquiry details to the server.

[1944] Step 2: Inquiry Analysis

[1945] Server: Uses generation AI to analyze inquiry content and extract and generate relevant answers and information.

[1946] Server: Saves the generated responses to the database.

[1947] Step 3: Provide your response

[1948] Server: Sends the answers stored in the database to the user's terminal.

[1949] Terminal: Displays the answer to the inquiry.

[1950] User: Review the displayed answer and proceed with the task.

[1951] Specific example

[1952] Step 1: Setting up the business workflow

[1953] User: The construction site manager logs into the system on their PC and sets up workflows such as "order management," "inventory check," and "delivery management."

[1954] Terminal: Sends configuration information to the server.

[1955] Server: Saves the received data to the database.

[1956] Step 2: Data Entry

[1957] User: The sales representative enters information about a new order into the "Order Management" screen on their terminal.

[1958] Terminal: Sends input data to the server.

[1959] Server: Stores order information in the database.

[1960] Step 3: Processing by Generator AI

[1961] Server: The generation AI checks inventory based on order information and automatically places orders according to the required quantity.

[1962] Server: Saves the results (inventory check and order details) generated by the AI ​​and notifies the user of these results.

[1963] Step 4: Review the results and take appropriate action.

[1964] User: The site manager reviews the results and verifies whether the order details are correct.

[1965] Terminal: Sends user confirmation details to the server.

[1966] Server: Reflect the verification results in the database.

[1967] Examples of how to handle inquiries

[1968] Step 1: Enter your inquiry

[1969] User: Field workers enter their questions about today's work procedures into the terminal and send them.

[1970] Terminal: Sends the inquiry details to the server.

[1971] Step 2: Inquiry Analysis

[1972] Server: The AI ​​generates responses by analyzing the inquiry and producing answers such as, "Today, we will proceed with the work according to the following steps."

[1973] Server: Saves the generated responses to the database.

[1974] Step 3: Provide your response

[1975] Server: Sends the generated response to the user's device.

[1976] Terminal: Displays the answer to the inquiry.

[1977] User: Review the answer and proceed with the task.

[1978] This system enables the digitalization and automation of business processes, as well as providing quick and accurate responses to inquiries from the field.

[1979] (Example 1)

[1980] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1981] Currently, many industries are demanding the digitalization and automation of business procedures, but the labor of field workers and managers, as well as errors caused by manual processes, remain major problems. Furthermore, there are challenges in responding quickly and accurately to inquiries. In particular, industries with many analog operations, such as construction, require increased efficiency in workflows and reduced errors, but achieving this presents significant cost and technical hurdles.

[1982] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1983] This invention includes a server that includes means for automating business procedures using generative artificial intelligence, means for saving user-input data to a database, and means for the generative artificial intelligence to execute business procedures by analyzing the data stored in the database. This enables automation and efficiency of business procedures. It also includes means for the user to input business data using a terminal, means for making inquiries from the field using a terminal, means for the server to analyze the inquiry content using generative artificial intelligence and generate an answer, and means for displaying the generated answer on the user's terminal. This enables a quick and accurate response to inquiries. It also includes means for the user to operate a business flow setting screen via a terminal, means for saving the business flow settings to a database, means for the user to check and modify the saved business flow on a terminal, and means for the business data stored in the database to be sent to the server in real time. This enables easy setting and updating of business flows. It also includes means for the server to automatically perform inventory checks and orders using a generative AI model based on the business data received, means for notifying the user of the generated inventory check and order results, and means for the user to check the notified results and make corrections or approvals as necessary. This achieves efficiency and accuracy in inventory management and ordering operations.

[1984] "Generative artificial intelligence" refers to systems that use machine learning and natural language processing technologies to perform intelligent tasks like humans.

[1985] "Automating business procedures" refers to automatically executing business processes that were previously performed manually, using systems and software.

[1986] A "database" refers to a system for efficiently storing, managing, and retrieving large amounts of data.

[1987] "User" refers to a person who uses this system to input business data, make inquiries, and check the results, or a person with a similar role.

[1988] "Terminal" refers to a hardware device used by a user (e.g., PC, smartphone, tablet).

[1989] A "server" refers to a computer system that plays a central role in storing, managing, and analyzing data, and connecting users and their devices.

[1990] "Inquiry" refers to a question that a user asks via their device to resolve doubts or uncertainties regarding the field or the performance of their work.

[1991] "Answer" refers to information or solutions generated by the server using artificial intelligence and provided to the user.

[1992] The "settings screen" refers to the interface that allows users to configure and modify business workflows and processes.

[1993] "Inventory check" refers to verifying the current inventory status based on inventory information stored in a database.

[1994] "Placement" refers to the business process of ordering necessary goods or materials from suppliers.

[1995] "Notification" refers to the real-time transmission of results or responses generated by the server to the user.

[1996] This invention is a system that digitizes and automates the workflows of industries with many analog operations, such as the construction industry. This system has the function of automating work procedures using generative artificial intelligence, the function of saving and analyzing user-entered data in a database, and the function of responding quickly and accurately to inquiries from the field.

[1997] System configuration and operation

[1998] Digitalization and automation of business processes

[1999] 1. Server

[2000] The server plays a central role in this system. This server incorporates a database (e.g., MySQL) for storing and managing business procedures. The server receives business data sent by users and stores it in the database. It also uses generative artificial intelligence (e.g., GPT-4) to execute automated tasks based on business procedures and notifies the user of the results.

[2001] 2. Terminal

[2002] A terminal is a device used by users to input, verify, and modify business data. Typically, a PC or smart device is used. Data entered on the terminal is transmitted to the server in real time, where it is analyzed and processed.

[2003] 3. User

[2004] Users are field workers or managers who input, verify, and modify business data through terminals. For example, a user might use a PC to input product codes, quantities, and delivery dates on the "Order Management" screen. This data is sent to the server via the terminal, where automated tasks are executed.

[2005] Responding to inquiries from the field.

[2006] 1. User

[2007] Users input inquiries from the field using their devices (PCs, smartphones, etc.). For example, they might input a question like, "What should I do if there is insufficient stock?"

[2008] 2. Terminal

[2009] The terminal sends the inquiry to the server and displays the response sent from the server.

[2010] 3. Server

[2011] The server receives the inquiry and analyzes the content using a generative AI model (e.g., GPT-4). It generates an appropriate response from the analysis results and saves it to a database. The generated response is notified to the user in real time. For example, a response such as "If inventory is low, an additional order is required" might be provided.

[2012] Specific example of the operation flow

[2013] 1. Setting up the business workflow

[2014] Users access the workflow settings screen using their PCs and configure business processes such as "order management," "inventory check," and "delivery management."

[2015] The server saves these settings to the database.

[2016] The terminal displays the workflow configured by the user and allows them to modify it as needed.

[2017] 2. Data entry and automation

[2018] The user enters order information into the "Order Management" screen using their device. For example, they might enter the product code, quantity, and delivery date.

[2019] The terminal sends the entered information to the server.

[2020] The server saves order information to a database and uses AI to automatically check inventory and place necessary orders. The results are saved in the database and notified to the user.

[2021] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[2022] 3. Handling inquiries

[2023] Users input inquiries from the field using a terminal and send questions, for example, about "today's work procedures."

[2024] The terminal sends the inquiry details to the server.

[2025] The server uses AI to analyze the inquiry and generate an appropriate response. For example, it may provide instructions on how to perform tasks or answers to related FAQs.

[2026] The responses generated by the server are stored in a database and notified to the user in real time.

[2027] The user reviews the answers displayed on their device and incorporates that information into their work.

[2028] Example of a prompt

[2029] "Product code: ABC123, Quantity: 10, Delivery date: 2023-10-15. Please check inventory and process the order for this item."

[2030] "Please tell me today's work procedure."

[2031] As a result, this system digitizes and automates business processes, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[2032] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2033] Step 1:

[2034] The user enters business data using a terminal. For example, they enter the product code, quantity, and delivery date. Specifically, the entered data is product code "ABC123", quantity "10", and delivery date "2023-10-15".

[2035] input:

[2036] Product code, quantity, delivery date

[2037] output:

[2038] Input data displayed on the terminal

[2039] Step 2:

[2040] The terminal sends the entered business data to the server. The data is sent to the server as an HTTP POST request. Specifically, the data sent from the terminal includes the product code "ABC123", quantity "10", and delivery date "2023-10-15".

[2041] input:

[2042] Business data entered into the terminal

[2043] output:

[2044] Business data sent to the server

[2045] Step 3:

[2046] The server analyzes the received business data and saves it to the database. Specifically, the server saves the product code "ABC123", quantity "10", and delivery date "2023-10-15" to the MySQL database.

[2047] input:

[2048] Business data sent to the server

[2049] output:

[2050] Business data stored in the database

[2051] Step 4:

[2052] The server uses a generated AI model (e.g., GPT-4) based on the stored data to check inventory and automatically place necessary orders. For example, the AI ​​model might determine that "there are 50 units in stock, so no additional orders are needed."

[2053] input:

[2054] Business data stored in the database

[2055] Inventory data required by the generative AI model

[2056] output:

[2057] The decision was made that an order is not necessary.

[2058] Step 5:

[2059] The server saves the results of tasks automated by the generated AI model to a database and notifies the user of those results. For example, a notification such as "Inventory check results indicate no additional orders are needed" is sent via email or system notification.

[2060] input:

[2061] Inventory check results

[2062] output:

[2063] Results notified to the user

[2064] Step 6:

[2065] The user checks the notification results using their device. If necessary, they can modify or approve the results on the system screen. For example, the user might check a notification on their smartphone stating "No additional order is needed" and approve it without making any changes.

[2066] input:

[2067] Notified results

[2068] output:

[2069] User verification and modification / approval results

[2070] Step 7:

[2071] Users input inquiries from the field using a terminal. For example, they might input a question like, "What are today's work procedures?"

[2072] input:

[2073] Inquiry details

[2074] output:

[2075] Inquiry content displayed on the device

[2076] Step 8:

[2077] The terminal sends the inquiry details to the server. The data is sent to the server as an HTTP POST request.

[2078] input:

[2079] Inquiry content entered on the terminal

[2080] output:

[2081] Inquiry content sent to the server

[2082] Step 9:

[2083] The server receives the inquiry and analyzes the content using a generation AI model. An appropriate answer is generated from the analysis results. For example, the AI ​​model might generate the answer: "Today's work procedure is as follows: 1. Arrive at the site 2. Prepare equipment 3. Begin work."

[2084] input:

[2085] Inquiry content sent to the server

[2086] Business procedure data required by the generated AI model

[2087] output:

[2088] Generated answer

[2089] Step 10:

[2090] The server saves the generated response to a database and notifies the user in real time. For example, the response might say, "Today's work procedure is as follows."

[2091] input:

[2092] Generated answer

[2093] output:

[2094] Responses notified to the user

[2095] Step 11:

[2096] The user checks the answers displayed on the device and incorporates that information into their work. For example, they might start on-site work following the work procedure displayed on the device.

[2097] input:

[2098] Notified response

[2099] output:

[2100] Tasks performed by the user

[2101] As a result, this system digitizes and automates business processes, enabling quick and accurate responses to inquiries from the field. This reduces manual errors and improves operational efficiency.

[2102] (Application Example 1)

[2103] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2104] In existing factory operations, work procedures and workflows are often managed manually, resulting in insufficient efficiency and automation. This leads to problems such as manual errors, wasted time, and delays in responding to inquiries, ultimately reducing productivity and quality. The objective of this invention is to solve these problems and realize the digitalization and automation of workflows.

[2105] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[2106] In this invention, the server includes means for automating work procedures using generative artificial intelligence, means for storing user-input data in a database, means for transmitting data to the server in real time, means for optimizing work procedures using generative AI, and means for automating operations on a factory production line. This enables more efficient workflows, reduced errors, and faster response times to inquiries.

[2107] "Generative artificial intelligence" is an advanced artificial intelligence technology used to automate business procedures, analyze data, and generate appropriate responses.

[2108] A "database" is a digital information repository where information such as business data, workflows, and inquiry details are centrally managed and stored and analyzed as needed.

[2109] "A means of sending data to a server in real time" refers to a system configuration that instantly sends data entered by a user to a server, enabling immediate processing and analysis of the data.

[2110] "Generative AI" is a type of artificial intelligence technology that automatically provides appropriate responses and optimizes work procedures based on user questions and data.

[2111] "Methods for optimizing work procedures" refers to technologies that use generative AI to automatically plan and propose efficient and error-free work procedures.

[2112] "Methods for automating factory production line operations" refer to systems in which robots and automated equipment perform production activities without human intervention, based on business flows and work procedures stored in a database.

[2113] "Users" refer to people such as field workers and managers who input and verify business data and use the system to perform their duties.

[2114] A "terminal" is a device used by users to input, verify, and modify business data, and includes PCs and smartphones.

[2115] A "server" is a computer system that plays a central role in this system, comprehensively managing data storage and analysis, execution of generating AI, and notification of results.

[2116] This invention is a system aimed at automating and digitizing work procedures and workflows in factories. This system stores user-inputted data in a database, and based on that data, generative artificial intelligence (generative AI) optimizes and automatically executes work procedures. It also includes means for sharing work procedures with robots within the factory and for quickly responding to inquiries from the factory floor.

[2117] Hardware and software configuration

[2118] server

[2119] The server plays a central role in the system. It performs the following functions:

[2120] Data Storage: User-entered data is saved to a database. SQLite is used as the database.

[2121] Data Analysis: Analyze data stored in the database and optimize work procedures using generative AI. OpenAI's GPT-3 is used for generative AI.

[2122] Result Notification: Notifies the user of the results generated by the AI.

[2123] terminal

[2124] A terminal is a device used by users to input, verify, and modify business data. It has the following functions:

[2125] Data entry: Provide a screen for entering business data. This could be a smartphone or computer, for example.

[2126] Inquiry Submission: A function that allows users to input inquiries from the field and send them to the server.

[2127] Results display: Displays notifications from the server and responses generated by the AI ​​in real time.

[2128] robot

[2129] The robots in the factory are responsible for automatically performing tasks based on work procedures shared from a server. The robots perform the following functions:

[2130] Task Execution: Perform tasks on the production line according to the specified work procedures.

[2131] Data transmission: Sends the progress of the work to the server in real time.

[2132] Specific examples of actions

[2133] Setting up business workflows

[2134] 1. Users access the business workflow settings screen using their smartphones. For example, they can set up business processes such as "order management," "inventory check," and "delivery management."

[2135] 2. The server saves these settings to the database.

[2136] Data entry and automation

[2137] 1. The user enters order information into the "Order Management" screen using their terminal. For example, they enter information such as product code, quantity, and delivery date.

[2138] 2. The terminal sends the entered information to the server.

[2139] 3. The server stores order information in a database and uses AI generation to automatically check inventory and place necessary orders.

[2140] 4. The server saves the results to the database and notifies the user.

[2141] 5. The user checks the notified results on their device and makes corrections or approvals as necessary.

[2142] Inquiry response

[2143] 1. Users input inquiries from the field using a terminal and send, for example, "Today's work procedure."

[2144] 2. The terminal sends the inquiry details to the server.

[2145] 3. The server uses a generation AI to analyze the inquiry and generate an appropriate response. For example, it may provide a work procedure guide or answers to related FAQs.

[2146] 4. The server saves the generated responses to a database and notifies the user in real time.

[2147] 5. The user reviews the answers displayed on the device and incorporates them into their work.

[2148] Example of a prompt

[2149] Working process:

[2150] Product order registration

[2151] Check stock availability

[2152] Order Placement

[2153] Preparation for delivery

[2154] Question: Please explain today's work procedure.

[2155] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2156] Step 1:

[2157] Users access the workflow settings screen using their smartphones. Users configure business processes such as "order management," "inventory check," and "delivery management."

[2158] Input: Business flow settings (e.g., order management, inventory check, delivery management)

[2159] Operation: Entering content on the business flow settings screen.

[2160] Output: Data from the configured business flow

[2161] Step 2:

[2162] The server saves the user's entered settings to a database.

[2163] Input: Data from the configured business flow

[2164] Operation: Saving flow configuration data to the database

[2165] Output: Saved business flow data

[2166] Step 3:

[2167] The user uses a terminal to enter order information into the "Order Management" screen. For example, they enter information such as product code, quantity, and delivery date.

[2168] Input: Order information (product code, quantity, delivery date, etc.)

[2169] Operation: Entering order information on the screen

[2170] Output: Input order data

[2171] Step 4:

[2172] The terminal sends the entered information to the server.

[2173] Input: Entered order data

[2174] Operation: Sending data to the server

[2175] Output: Order data received by the server

[2176] Step 5:

[2177] The server stores order information in a database and uses AI generation to automatically check inventory and place necessary orders.

[2178] Input: Order data received by the server

[2179] Operation: Saves order information to the database and uses AI to check inventory and automatically place orders.

[2180] Output: Inventory status, order placement information

[2181] Step 6:

[2182] The server saves the results to the database and notifies the user.

[2183] Input: Inventory status, order placement information

[2184] Operation: Save results to a database and notify the user.

[2185] Output: Processing results notified to the user

[2186] Step 7:

[2187] Users can check the notified results on their devices and make corrections or approvals as needed.

[2188] Input: Processing result notified to the user

[2189] Action: Review results, make necessary corrections and approvals.

[2190] Output: Corrected and approved data

[2191] Step 8:

[2192] Users input inquiries from the field using a terminal and send, for example, "Today's work procedure."

[2193] Input: Inquiry details (e.g., "Today's work procedure")

[2194] Operation: Input and send inquiry content to the terminal.

[2195] Output: Query content sent to the server

[2196] Step 9:

[2197] The server uses a generation AI to analyze the inquiry and generate an appropriate response.

[2198] Input: Inquiry received by the server

[2199] Operation: Analysis of inquiry content and generation of answers using a generation AI.

[2200] Output: Generated answer

[2201] Step 10:

[2202] The server saves the generated responses to a database and notifies the user in real time.

[2203] Input: Generated answer

[2204] Operation: Saves responses to the database and provides real-time notifications to users.

[2205] Output: Response notified to the user

[2206] Step 11:

[2207] The user checks the answers displayed on their device and incorporates that information into their work.

[2208] Input: Response notified to the user

[2209] Action: Confirmation of notified responses and implementation of the work.

[2210] Output: Results of the work

[2211] This enables the efficient execution of a series of processes and achieves the automation and digitalization of the workflow and work procedures within the factory.

[2212] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[2213] This invention relates to a system for digitizing and automating business workflows by combining an emotion engine. This system uses generative artificial intelligence to automate business procedures and leverages user emotion data to provide more appropriate and effective support.

[2214] System configuration and operation

[2215] Digitalization and automation of business processes

[2216] Server: This server plays a central role in this system. It incorporates a database for storing work procedures, generative artificial intelligence, and an emotion engine for analyzing user sentiment data. The server receives work data sent by users and stores it in the database. It also uses generative artificial intelligence to execute automated tasks based on work procedures and notifies the user of the results.

[2217] Terminal: A device (e.g., PC or smart device) used by users to input, verify, and modify business data. Data entered on the terminal is sent to the server in real time, where it is analyzed and processed. In addition, user emotional data is collected in conjunction with the emotion engine.

[2218] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[2219] Collection and analysis of emotional data

[2220] Server: The emotion engine collects emotional data from the user's facial expressions, voice, and language use, and analyzes this data. The analysis results are fed back to the generating AI and used to adjust work procedures and the content of responses to inquiries.

[2221] Terminal: Along with the business data entered by the user, the emotion engine sends collected emotion data to the server. The user's emotion data is analyzed in real time, and the results are reflected in the progress of the work.

[2222] Specific examples of operation

[2223] Setting up business workflows

[2224] Users access a workflow configuration screen using their PCs and set up processes such as "order management," "inventory check," and "delivery management."

[2225] The terminal sends information about the configured workflow to the server.

[2226] The server saves the received business flow information to the database.

[2227] Data entry and automation

[2228] The user enters information into the "Order Management" screen using their device (e.g., product code, quantity, delivery date).

[2229] The device sends the entered information to the server. Simultaneously, the emotion engine collects the user's emotional data.

[2230] The server stores order information and sentiment data in a database and uses a generating AI to check inventory and issue ordering instructions. The results are stored in the database and notified to the user.

[2231] Users can review the results notified on their PCs or smart devices and make corrections or approvals as needed.

[2232] Use of emotional data

[2233] Server: Based on the user's emotional data analyzed by the emotion engine, the generating AI adjusts the work procedures and responses. For example, if a user is feeling stressed, it can suggest simplifying the operation.

[2234] Device: By displaying emotional data in real time while the user is operating the device, administrators can more easily provide appropriate support.

[2235] Responding to inquiries from the field.

[2236] The user enters the content of the inquiry from the field into the terminal and sends it (e.g., "Question about today's work procedure").

[2237] The device sends the inquiry details to the server. Simultaneously, the emotion engine collects the user's emotional data.

[2238] The server uses a generative AI to analyze the inquiry content and sentiment data, and generates an appropriate response. For example, if the user is feeling anxious, it will provide a response that takes that into consideration.

[2239] The responses generated by the server are stored in a database and notified to the user in real time.

[2240] The user checks the answers displayed on the device and incorporates that information into their work.

[2241] This enables the system to digitize and automate business processes, as well as provide prompt and accurate support through user sentiment data. This results in reduced manual errors, increased operational efficiency, and higher user satisfaction.

[2242] The following describes the processing flow.

[2243] Program processing

[2244] Digitalization and automation of business processes

[2245] Step 1: Setting up the business workflow

[2246] User: Use a PC to access the workflow settings screen and configure workflows such as "Order Management," "Inventory Check," and "Delivery Management."

[2247] Terminal: Sends information about the configured workflow to the server.

[2248] Server: Saves the received business flow information to the database.

[2249] Step 2: Data Entry

[2250] User: Use your device to enter information into the "Order Management" screen (e.g., product code, quantity, delivery date).

[2251] Terminal: Sends the entered order information to the server.

[2252] Server: Stores order information in the database.

[2253] Step 3: Collecting emotional data

[2254] Terminal: While the user is inputting data, the terminal's camera and microphone are used to collect facial expressions and voice.

[2255] Server: Analyzes facial expressions and voice data sent from terminals using an emotion engine and generates emotion data.

[2256] Server: Stores emotional data in a database.

[2257] Step 4: Processing by Generator AI

[2258] Server: Passes business data and emotional data received from the database to the AI ​​for inventory checks and ordering instructions.

[2259] Server: Saves the processing results of the generated AI (inventory check results and order details) to the database.

[2260] Server: Notifies the user's terminal of the processing results.

[2261] Step 5: Review the results and take appropriate action.

[2262] User: Check the processing results notified on the device and make corrections or approvals as necessary.

[2263] Terminal: Sends user modifications and approvals to the server.

[2264] Server: Reflects changes and approvals in the database.

[2265] Responding to inquiries from the field.

[2266] Step 1: Enter your inquiry

[2267] User: Enter the inquiry details from the field into the terminal and send it (e.g., "I don't know today's work procedure").

[2268] Terminal: Sends the inquiry details to the server.

[2269] Step 2: Analyzing inquiry and sentiment data

[2270] Terminal: Collects facial expressions and voice data from the user while they are entering their inquiry, and sends it to the server.

[2271] Server: The emotion engine analyzes the user's facial expressions and voice data to generate emotion data.

[2272] Server: Uses emotional data to generate inquiry content. An AI analyzes the data and generates relevant answers and information.

[2273] Server: Saves the generated responses to the database.

[2274] Step 3: Provide your response

[2275] Server: Sends the generated response to the user's device.

[2276] Terminal: Displays the answer to the inquiry.

[2277] User: Review the displayed answer and proceed with the task.

[2278] Specific example

[2279] Step 1: Setting up the business workflow

[2280] User: The construction site manager logs into the system on their PC and sets up workflows such as "order management," "inventory check," and "delivery management."

[2281] Terminal: Sends configuration information to the server.

[2282] Server: Saves the received data to the database.

[2283] Step 2: Data Entry

[2284] User: The sales representative enters information about a new order into the "Order Management" screen on their terminal.

[2285] Terminal: Sends input data to the server.

[2286] Server: Stores order information in the database.

[2287] Step 3: Collecting emotional data

[2288] Terminal: The camera and microphone collect the facial expressions and voices of sales representatives entering order information.

[2289] Server: The emotion engine analyzes the collected data and generates emotion data.

[2290] Server: Stores emotional data in a database.

[2291] Step 4: Processing by Generator AI

[2292] Server: The generating AI checks inventory based on order information and sentiment data, and automatically places orders according to the required quantity.

[2293] Server: Saves the results (inventory check and order details) generated by the AI ​​and notifies the user of these results.

[2294] Step 5: Review the results and take appropriate action.

[2295] User: The site manager reviews the results and verifies whether the order details are correct.

[2296] Terminal: Sends user confirmation details to the server.

[2297] Server: Reflect the verification results in the database.

[2298] Examples of how to handle inquiries

[2299] Step 1: Enter your inquiry

[2300] User: Field workers enter their questions about today's work procedures into the terminal and send them.

[2301] Terminal: Sends the inquiry details to the server.

[2302] Step 2: Analyzing inquiry and sentiment data

[2303] Terminal: Collects facial expressions and voice recordings from the user while they are entering their inquiry and sends them to the server.

[2304] Server: The emotion engine analyzes facial expressions and voice data to generate emotion data.

[2305] Server: The generation AI analyzes the inquiry content and sentiment data to generate an appropriate response.

[2306] Step 3: Provide your response

[2307] Server: Saves the generated response to the database and notifies the user.

[2308] Terminal: Displays the answer to the inquiry.

[2309] User: Review the answer and proceed with the task.

[2310] This enables the system to digitize and automate business processes, while also providing meticulous support that takes user emotions into consideration.

[2311] (Example 2)

[2312] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2313] Conventional business process management systems have suffered from inefficiency due to the frequent use of manual operations. Furthermore, they often fail to consider user emotions when providing procedures and support, resulting in low user satisfaction. This invention aims to provide a system that achieves high efficiency and user satisfaction by automating business procedures and utilizing user emotion data.

[2314] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[2315] In this invention, the server includes means for automating work procedures using generative artificial intelligence, means for saving user-inputted data to a database, and means for analyzing the data stored in the database and having the generative artificial intelligence execute the work procedures. By combining this with means for collecting and analyzing user emotional data and means for adjusting work procedures based on emotional data, rapid and accurate support becomes possible.

[2316] "Generative artificial intelligence" is a type of artificial intelligence that performs self-learning based on given data to optimize and automate business procedures.

[2317] "Business procedures" refer to a series of steps and procedures necessary to perform a specific task or process.

[2318] A "database" is a system for organizing and storing data, allowing for the quick retrieval of necessary information.

[2319] "Emotional data" refers to information that indicates a user's emotional state, obtained from their facial expressions, voice, and choice of words.

[2320] An "emotion engine" is a part of the software or hardware used to collect and analyze emotional data.

[2321] A "server" is a computer system used to store, process, and transmit data over a network.

[2322] A "terminal" is a device (e.g., a PC or smart device) used by a user to input, verify, and modify business data.

[2323] "Analysis" is the process of examining data in detail and finding its meaning and patterns.

[2324] "Notification" refers to the act of a system informing a user of processing results or other information.

[2325] This invention relates to a system for digitizing and automating business workflows by combining an emotion engine. This system uses generative artificial intelligence (generative AI) to automate business procedures and leverages user emotion data to provide more appropriate and effective support.

[2326] Digitalization and automation of business processes

[2327] Server Configuration

[2328] The server plays a central role in this system. It incorporates a database for storing work procedures, generative artificial intelligence, and an emotion engine for analyzing user sentiment data. The server receives work data sent by users and stores it in the database. It also uses generative AI to execute automated tasks based on work procedures and notifies the user of the results.

[2329] Device configuration

[2330] These are devices (e.g., PCs and smart devices) that users use to input, verify, and modify business data. Data entered on the terminal is transmitted to the server in real time, where it is analyzed and processed. Furthermore, user emotional data is collected in conjunction with an emotion engine.

[2331] Collection and analysis of emotional data

[2332] Collection of emotional data

[2333] The device collects emotional data in real time through facial expressions and voice during user interaction. For example, it uses a facial recognition camera and microphone. The collected emotional data is sent to a server.

[2334] Analysis of emotional data

[2335] The server uses an emotion engine to analyze the received emotional data. The analysis results are fed back to the generating AI, which adjusts the work procedures and responses according to the user's emotions.

[2336] Specific examples of operation

[2337] Setting up business workflows

[2338] User: Access the workflow settings screen using a PC and configure processes such as "Order Management," "Inventory Check," and "Delivery Management."

[2339] Terminal: Sends information about the configured workflow to the server.

[2340] Server: Saves the received business flow information to the database.

[2341] Data entry and automation

[2342] User: Use the terminal to enter information into the "Order Management" screen. For example, enter order information such as product code, quantity, and delivery date.

[2343] Terminal: Collects emotional data along with the entered order information and sends it to the server.

[2344] Server: Stores submitted order information and sentiment data in a database and uses generated AI to check inventory and issue ordering instructions. For example, it automatically instructs ordering procedures for items with insufficient stock.

[2345] Server: Stores inventory check and order instruction results in a database and notifies users.

[2346] User: Review the results notified via the device and make corrections or approvals as necessary.

[2347] Use of emotional data

[2348] Server: Based on the user's emotional data analyzed by the emotion engine, the generating AI adjusts the work procedures and responses. For example, if a user is feeling stressed, it can suggest simplifying the operation.

[2349] Terminal: Displays emotional data in real time while the user is operating the device, making it easier for administrators to provide appropriate support.

[2350] Responding to inquiries from the field.

[2351] Inquiry reception

[2352] User: Enter the inquiry from the field into the terminal and send it. For example, enter "Question about today's work procedure."

[2353] Terminal: Sends emotional data along with the inquiry content to the server.

[2354] Answer generation

[2355] Server: Uses a generation AI to analyze inquiry content and sentiment data to generate appropriate responses. For example, if anxiety is felt, it will create content that provides reassurance.

[2356] Submit and confirm your response.

[2357] Server: Generated responses are stored in a database and users are notified in real time.

[2358] User: Check the answers on the device and incorporate the information into the work.

[2359] Example of a prompt

[2360] "The generating AI checks the inventory of product code 12345 and issues order instructions as needed."

[2361] "If a user is feeling anxious, we will provide an answer that takes that into consideration."

[2362] "Generate suggestions to simplify operations for users who are experiencing stress."

[2363] This enables efficient and user-satisfying business operations through detailed procedures and specific actions.

[2364] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2365] Step 1:

[2366] Users access a business workflow settings screen and configure business procedures such as "order management," "inventory check," and "delivery management." For example, in "order management," a user might input "product code," "quantity," and "delivery date." The entered data is then used to configure the business workflow settings.

[2367] Input: Business flow configuration information (e.g., product code, quantity, delivery date)

[2368] Output: Configured business workflow (e.g., order management)

[2369] Step 2:

[2370] The terminal transmits information about the user's configured workflow to the server in real time. This transmission transfers the configuration information to the server.

[2371] Input: Configured business flow information (e.g., order management information)

[2372] Output: Business flow information sent to the server

[2373] Step 3:

[2374] The server saves the received business flow information to a database. This saving process allows configuration information to be accumulated in the database and made available for later processing.

[2375] Input: Business flow information sent to the server (e.g., order management information)

[2376] Output: Business flow information stored in the database

[2377] Step 4:

[2378] The user enters information into the "Order Management" screen based on the configured workflow. For example, they might enter product code "12345", quantity "100", and delivery date "next Monday". The entered data is then compiled into order information.

[2379] Input: Order information (e.g., product code, quantity, delivery date)

[2380] Output: Entered order information

[2381] Step 5:

[2382] The terminal collects emotional data in real time along with the entered order information and sends it to the server. The terminal collects emotional data using a facial recognition camera and microphone.

[2383] Input: Order information and emotional data (e.g., user's facial expressions, voice)

[2384] Output: Order information and sentiment data sent to the server

[2385] Step 6:

[2386] The server stores the submitted order information and sentiment data in a database.

[2387] Input: Order information and sentiment data

[2388] Output: Order information and sentiment data stored in the database

[2389] Step 7:

[2390] The server uses a generating AI based on stored order information to check inventory and issue ordering instructions. For example, the generating AI automatically instructs ordering processes for products with insufficient stock. The analysis results are stored in a database.

[2391] Input: Order information stored in the database

[2392] Output: Inventory check results and order instructions

[2393] Step 8:

[2394] The server stores the results of inventory checks and order instructions in a database, generates notification information, and notifies the user.

[2395] Input: Inventory check results and order instructions

[2396] Output: Notification Information

[2397] Step 9:

[2398] Users review the results notified via their devices and make corrections or approvals as needed. For example, a user might make changes based on inventory check results.

[2399] Input: Notification information

[2400] Output: Corrected or approved information

[2401] Step 10:

[2402] The device collects emotional data in real time through facial expressions and voice while the user is operating it. For example, it uses a facial recognition camera and microphone.

[2403] Input: User's facial expressions, voice

[2404] Output: Collected sentiment data

[2405] Step 11:

[2406] The device sends the collected emotional data to the server.

[2407] Input: Collected emotional data

[2408] Output: Sentiment data sent to the server

[2409] Step 12:

[2410] The server uses an emotion engine to analyze the received emotional data. The analysis results are fed back to the generating AI, which adjusts the work procedures and responses according to the user's emotions.

[2411] Input: Collected emotional data

[2412] Output: Analysis results and feedback information

[2413] Step 13:

[2414] The user enters the inquiry details from the field into the terminal and sends it. For example, they might enter "A question about today's work procedure."

[2415] Input: Inquiry details

[2416] Output: Inquiry content entered into the terminal

[2417] Step 14:

[2418] The device sends emotion data along with the inquiry content to the server.

[2419] Input: Inquiry details and sentiment data

[2420] Output: Query content and sentiment data sent to the server

[2421] Step 15:

[2422] The server uses a generative AI to analyze the inquiry content and sentiment data, and generates an appropriate response. For example, if the user is feeling anxious, it will create a response that provides reassurance.

[2423] Input: Inquiry details and sentiment data

[2424] Output: Generated answer

[2425] Step 16:

[2426] The server stores the generated responses in a database and notifies the user in real time.

[2427] Input: Generated answer

[2428] Output: Notified response

[2429] Step 17:

[2430] Users review their responses on their devices and incorporate that information into their work. For example, a user might modify their work procedures based on the generated responses.

[2431] Input: Notified response

[2432] Output: Answers reflected in the work

[2433] (Application Example 2)

[2434] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2435] The present invention aims to provide a system that digitizes and automates business workflows, while also understanding user emotions in real time and providing personalized support. Conventional systems have struggled to respond while considering user emotions, resulting in problems with operational efficiency and user satisfaction. In particular, it is necessary to provide appropriate support according to emotional states to improve operational efficiency, reduce errors, and achieve high user satisfaction.

[2436] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[2437] In this invention, the server includes means for collecting and analyzing emotional data, means for providing personalized support to the user based on the emotional data, and means for providing appropriate responses based on the user's emotional data. This makes it possible to grasp the user's emotions in real time and provide appropriate support quickly.

[2438] "Generative artificial intelligence" refers to an artificial intelligence system that automatically executes tasks in response to business procedures and user inquiries, and generates appropriate answers and results.

[2439] "Emotional data" refers to information that represents a user's emotional state, obtained from their facial expressions, voice, and choice of words.

[2440] An "emotion engine" is a system that collects and analyzes user emotional data and uses the results to adjust work procedures and support content.

[2441] "Personalized support" refers to specific assistance and content provided according to each user's individual emotional state and needs.

[2442] A "terminal" is a device used by a user to input, verify, and modify business data.

[2443] A "database" is an information management system used to centrally store and manage business procedures, user input data, emotional data, and other similar information.

[2444] A "business process flow" is a sequence of processes and tasks that make up a business procedure.

[2445] A "server" is a central processing unit that processes and analyzes business procedures and emotional data, and manages and notifies the generated results.

[2446] An "inquiry" is a question or request made by a user to seek support or address doubts regarding the work environment or procedures.

[2447] An "answer" is a response to a generated inquiry, providing appropriate solutions and information to the user's questions or requests.

[2448] This invention is a system for digitizing and automating business workflows using a combination of generative AI and an emotion engine. This system utilizes the following hardware and software to enhance user work efficiency and provide personalized support.

[2449] System configuration and operation

[2450] Digitalization and automation of business processes

[2451] Server: Plays a central role in the system. The server incorporates a database for storing business procedures, a generative AI model, and an emotion engine. The server receives business data sent by users and stores it in the database. It also uses generative AI to execute automated tasks based on business procedures and notifies the user of the results.

[2452] Software used: Database management system (e.g., MySQL), AI model (e.g., TensorFlow / Keras), request processing (e.g., Flask).

[2453] Terminal: A device used by users to input, verify, and modify business data (e.g., PC or smart device). Data entered on the terminal is sent to the server in real time, where it is analyzed and processed. It also has a function to collect user emotion data in conjunction with the emotion engine.

[2454] Software to be used: Face recognition libraries (e.g., OpenCV, dlib), emotion recognition models (e.g., TensorFlow / Keras).

[2455] Users: Primarily field workers and managers who input and verify work data via terminals. They also review results and make necessary corrections and approvals.

[2456] Collection and analysis of emotional data

[2457] Server: The emotion engine collects emotional data from the user's facial expressions, voice, and language use, and analyzes this data. The analysis results are fed back to the generating AI and used to adjust work procedures and the content of responses to inquiries.

[2458] Software to be used: Emotion recognition library (e.g., TensorFlow / Keras).

[2459] Terminal: Along with the business data entered by the user, the emotion engine sends collected emotion data to the server. The user's emotion data is analyzed in real time, and the results are reflected in the progress of the work.

[2460] Specific example

[2461] For example, when a user is searching for products in a virtual store, their smartphone camera captures their facial expressions, and an emotion engine detects that the user is having trouble. This information is sent to a server, and an appropriate support message is displayed.

[2462] Example of a prompt:

[2463] "Based on emotion recognition, generate appropriate support messages to display when a user is experiencing difficulties."

[2464] This allows the system to understand users' emotions in real time and provide appropriate support. In addition, the digitalization and automation of workflows improves user work efficiency, reduces errors, and enables faster task completion.

[2465] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2466] Step 1:

[2467] Terminal: Users input business data. Specifically, users use a terminal (PC or smart device) to input information such as product code, quantity, and delivery date into the order management screen. The entered data is temporarily stored on the terminal.

[2468] Input: Business data entered by the user (e.g., product code, quantity, delivery date)

[2469] Output: Business data temporarily stored on the terminal

[2470] Step 2:

[2471] Terminal: Sends entered business data to the server. Simultaneously, it uses the terminal's camera to capture user facial data and collects emotional data in real time using an emotion engine. The collected emotional data is also sent to the server.

[2472] Input: Business data, user facial expression data

[2473] Output: Business data and sentiment data sent to the server

[2474] Step 3:

[2475] Server: Stores received business data and sentiment data in the database. Business data is stored according to the business flow, and sentiment data is stored linked to the user session.

[2476] Input: Business data and emotional data sent from the terminal.

[2477] Output: Business data and sentiment data stored in the database

[2478] Step 4:

[2479] Server: Analyzes stored business data using a generation AI model and automatically generates necessary business procedures. It also adjusts the workflow as needed based on emotional data. For example, if a user is experiencing stress, it simplifies the business procedures.

[2480] Input: Business data and emotional data stored in the database

[2481] Output: Business procedures and adjusted workflows analyzed and generated by the AI ​​model.

[2482] Step 5:

[2483] Server: Executes the generated business procedures. Specifically, it automates tasks such as inventory checks and order placement, and generates the results.

[2484] Input: Generated business procedure

[2485] Output: Automated task results (e.g., inventory check results, order instructions)

[2486] Step 6:

[2487] Server: Notifies the user of the results of automated tasks. Simultaneously, it generates appropriate feedback and support messages for the user based on sentiment data. For example, if the user is having trouble, it displays a support message to help resolve the issue.

[2488] Input: Automated task results, sentiment data

[2489] Output: Results notified to the user, support messages

[2490] Step 7:

[2491] User: Check the results and support messages notified on the device. Modify or approve the results as needed.

[2492] Input: Notified results, support message

[2493] Output: User review, modification, and approval of results

[2494] This enables the system to provide swift and accurate support within a digitized workflow, while taking user emotions into consideration.

[2495] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2496] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2497] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2498] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2499] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2500] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2501] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2502] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situati...

Claims

1. Methods for automating business procedures using generative artificial intelligence, A means of saving user-entered data to a database, A means by which artificial intelligence analyzes data stored in a database to generate business procedures and executes them, A means of notifying the user of the results performed by the generative artificial intelligence, A system that includes this.

2. A means by which users input business data using a terminal, A means of making inquiries from the field using a terminal, A means by which a server uses artificial intelligence to analyze the content of an inquiry and generate a response, A means of displaying the generated response on the user's device, The system according to claim 1, including the following:

3. A means of providing a business flow configuration screen, A means of saving the configured business flow to a database, A means for users to view and modify business workflows stored in a database on their devices, The system according to claim 1, including the following:

Images