System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting business information; means for causing a AI model to learn the input business information; means for automatically generating a business flow based on the learned business information; means for reading a plurality of business flows, analyzing duplication and mismatch, and generating an improvement proposal; and means for presenting the generated improvement proposal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Creating and modifying a workflow takes time and requires detailed business knowledge, making it difficult for anyone other than a specialist to handle. Furthermore, while there may be overlaps with other departments' work or the workflow can be improved by reviewing collaboration with other departments, implementing such an approach requires a great deal of effort. This can hinder the overall efficiency of the workflow. The objective of this invention is to solve these problems. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems with a system that includes a means for inputting business information, a means for training an AI model to learn the input business information, a means for automatically generating a business flow based on the learned business information, a means for reading multiple business flows, analyzing overlaps and inconsistencies, and generating improvement proposals, and a means for presenting the generated improvement proposals. Furthermore, the system also includes a means for monitoring the implementation status of the business flow in real time, detecting anomalies and bottlenecks, and a means for re-proposing improvements based on the detected anomalies and bottlenecks, thereby achieving continuous optimization of the business flow. Furthermore, by combining a means for presenting a revised business flow for the user to evaluate and confirm, and a means for updating and implementing the business flow after the user's confirmation, more flexible and effective business improvement is possible.

[0006] "Business information" refers to all information necessary to build a business flow, such as the content of the business, work procedures, dependencies, responsible parties, and resources.

[0007] An "AI model" refers to a computational model that uses artificial intelligence technology to learn patterns from input data and perform tasks such as prediction and classification.

[0008] A "business flow" is a diagram or model that shows the sequence and dependencies of a series of business processes, visualizing the relationships and flow of each step.

[0009] "Automatic generation" refers to the process where a system generates an output based on various data and information without manual intervention.

[0010] "Overlap" refers to the repeated execution of the same task or procedure within different workflows or the same workflow.

[0011] "Inconsistency" refers to inconsistent information or procedures, which can lead to contradictions or unexpected problems in business processes.

[0012] "Improvement proposals" refer to proposals aimed at streamlining and optimizing existing business processes, and are intended to improve business performance.

[0013] "Real-time monitoring" refers to the immediate monitoring of the progress of business processes, providing timely data and detecting anomalies.

[0014] A "bottleneck" refers to the step or element within a business process that consumes the most time and resources and reduces overall efficiency.

[0015] The "revised workflow" refers to a new workflow that has been updated by incorporating the improvement suggestions, and represents the optimized work procedures and their dependencies. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention is a system that inputs business information, automatically generates business flows by learning them into an AI model, and then analyzes multiple business flows to propose improvement plans. This system is implemented as follows.

[0038] 1. Entering and learning business information

[0039] User

[0040] The user uses a terminal to input task information, including the name of each step, detailed procedure content, dependencies, and person in charge.

[0041] Specific examples

[0042] For example, a user inputs the following business procedure through a terminal: "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order."

[0043] server

[0044] The server receives the business information sent from the device and inputs it into the AI ​​model, which uses this data to learn about dependencies and efficient workflows.

[0045] 2. Automatic creation of business flows

[0046] server

[0047] The server automatically generates a workflow based on the business information learned by AI. The generated workflow takes into account the dependencies between each step, creating the most efficient workflow.

[0048] Specific examples

[0049] The server efficiently arranges the steps of "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order" and creates a business flow diagram.

[0050] Terminal

[0051] The terminal presents the generated workflow diagram to the user, allowing the user to grasp the overall picture of the workflow.

[0052] 3. Integration of multiple workflows and proposal of improvements

[0053] User

[0054] Users can upload multiple existing business processes to the server via their terminals.

[0055] server

[0056] The server analyzes these workflows to detect duplication and inconsistencies, and based on the results, generates improvement proposals for improving efficiency.

[0057] Specific examples

[0058] For example, if the "inventory check" procedure overlaps between Department A's "customer management flow" and Department B's "inventory management flow," the server will detect this overlap and generate an improvement proposal to "consolidate the inventory check step."

[0059] Terminal

[0060] The terminal presents the improvement proposals generated by the server to the user, who can then check and evaluate them.

[0061] 4. Evaluation and implementation of improvement plans

[0062] User

[0063] The user evaluates the proposed improvement plan and decides whether to apply it. If the improvement plan is applied, a confirmation is sent to the server via the terminal.

[0064] server

[0065] The server receives the user's confirmation and updates the workflow, which is then put into action and made live for the user to use.

[0066] 5. Collaboration and Monitoring

[0067] server

[0068] The server monitors the execution status of the updated business flow in real time, and immediately detects any abnormalities or bottlenecks that occur during the business process.

[0069] Terminal

[0070] The terminal displays a notification of any detected abnormalities or bottlenecks to the user, allowing the user to confirm that there is a problem with the progress of the business flow.

[0071] server

[0072] The server generates new improvement proposals based on the anomalies and bottlenecks and presents them to the user again.

[0073] Specific examples

[0074] For example, if the server detects that "inventory check" in the new workflow is taking longer than expected, a notification will be displayed on the terminal. The server will then suggest a new improvement plan: "Move inventory check to an automated system."

[0075] In this way, by executing a series of processes based on the present invention, from inputting business information to automatically generating a flow, proposing improvements, implementing them, and monitoring them, it is possible to improve business efficiency and strengthen cooperation.

[0076] The processing flow will be explained below.

[0077] Step 1:

[0078] The user inputs business information through a terminal. Business information includes the name of each procedure, detailed procedure content, dependencies, and person in charge. For example, the user might input procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation."

[0079] Step 2:

[0080] The terminal sends the entered business information to the server. The data is transmitted using a secure communication protocol.

[0081] Step 3:

[0082] The server inputs the business information received from the device into the AI ​​model, which uses this data to learn business dependencies and efficient processing sequences.

[0083] Step 4:

[0084] The server automatically generates a workflow based on the information learned by the AI ​​model. The generated workflow reflects the optimal dependencies between each step.

[0085] Step 5:

[0086] The server sends the generated business flow diagram to the terminal, where the user can view the diagram on the terminal screen.

[0087] Step 6:

[0088] Users can upload multiple existing business processes to the server via their terminals.

[0089] Step 7:

[0090] The server analyzes multiple workflows and detects duplications and inconsistencies. For example, it detects duplication of the "Stock Check" step between the "Customer Management Flow" and the "Inventory Management Flow."

[0091] Step 8:

[0092] Based on the analysis results, the server generates improvement proposals to improve business efficiency, such as "centralizing the inventory check step."

[0093] Step 9:

[0094] The server sends the generated improvement proposal to the terminal, which then presents it to the user, who then checks the contents of the improvement proposal.

[0095] Step 10:

[0096] The user evaluates the improvement plan and decides whether to apply it. If so, the terminal sends a confirmation to the server.

[0097] Step 11:

[0098] The server receives the user's confirmation and updates the workflow, making the new workflow available for execution.

[0099] Step 12:

[0100] The server monitors the execution status of the updated business flow in real time, and immediately detects any abnormalities or bottlenecks that occur.

[0101] Step 13:

[0102] The server generates new improvement proposals based on the detected anomalies and bottlenecks, such as "shift inventory checks to an automated system."

[0103] Step 14:

[0104] The server sends new improvement proposals to the terminal and presents them to the user again, who then checks them and considers how to respond.

[0105] Example 1

[0106] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0107] In today's business environment, streamlining and improving workflows is extremely important. However, conventional methods require a significant amount of time and effort to manually input and analyze business information, resulting in low accuracy in automatically generating workflows and improving proposals. Furthermore, it is difficult to integrate multiple workflows, detect overlaps and inconsistencies, and generate efficient improvement proposals. The present invention aims to solve these problems and provide a system that streamlines and optimizes workflows in real time.

[0108] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0109] In this invention, the server includes means for inputting business information, means for training a generative AI model on the input business information, means for automatically generating a business flow based on the trained business information, means for presenting the generated business flow, means for integrating and analyzing multiple business flows, detecting duplications and inconsistencies, and generating improvement proposals, and means for presenting the generated improvement proposals. This enables automatic input of business information, automatic generation of efficient workflows, integrated analysis of multiple business flows, and generation and presentation of optimized improvement proposals.

[0110] "Business information" is data such as business-related procedures, detailed procedure content, dependencies, and personnel in charge.

[0111] A "generative AI model" is an algorithm or machine learning model that learns business information and automatically generates optimal business flows and proposes improvements.

[0112] A "business flow" refers to the flow of a series of procedures or processes for carrying out a specific business operation.

[0113] "Automatic generation" means that the system automatically creates a business flow based on the input information without human intervention.

[0114] "Integration" means combining multiple business flows into one entity.

[0115] "Duplicate" refers to the occurrence of the same procedure multiple times in different business processes, which can lead to inefficiency.

[0116] "Inconsistency" refers to a state in which the order or content of a business flow is inconsistent.

[0117] "Improvement proposals" are specific proposals aimed at streamlining and optimizing business processes.

[0118] "Presentation" refers to the display of system-generated information or data in a form that is visible to the user.

[0119] "Monitoring" means continuously observing the execution status of a business flow and checking for any abnormalities or problems.

[0120] An "abnormality" is an unexpected problem or obstacle that occurs in the normal course of business.

[0121] A "bottleneck" is a procedure in a business flow that is slower to execute than other procedures and that causes a decrease in overall efficiency.

[0122] The present invention is a system that automatically generates workflows by inputting business information and training a generative AI model, and then analyzes multiple workflows to propose improvements. This system is implemented as follows.

[0123] Entering and learning business information

[0124] User

[0125] The user uses the terminal to input business information. This information includes the name of each step, detailed procedure content, dependencies, and the person in charge. For example, the user inputs the business procedure "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order" through the terminal. After completing the input, the user clicks the "Send button" to send the business information to the server.

[0126] server

[0127] The server receives business information sent from the device and inputs the data into a generative AI model using Python, TensorFlow, etc. This model retrains based on the received data, learning dependencies between business processes and efficient workflows.

[0128] Automatic creation of business flows

[0129] server

[0130] The server obtains the optimized business flow from the generative AI model that has completed training, and automatically generates a business flow diagram based on that data. Specifically, it uses libraries such as Graphviz to generate a diagram that can be displayed visually.

[0131] Presentation of business flow

[0132] Terminal

[0133] The terminal displays the generated business flow diagram to the user. The user can check the generated flow and make any necessary corrections. For example, the user can check the generated business flow diagram on the terminal and click the "Confirm" button to confirm the contents.

[0134] Integration and analysis of multiple workflows

[0135] User

[0136] Users upload multiple existing business processes collected from different departments and projects to the server via their terminal in CSV or Excel format.

[0137] server

[0138] The server analyzes the multiple workflows uploaded and detects duplication, inconsistencies, and unnecessary steps. For example, it uses the Python "Pandas" library to analyze the data and identify duplicate steps and inconsistencies.

[0139] Generate and present improvement proposals

[0140] server

[0141] Based on the analysis results, the server integrates each business flow and generates improvement proposals for efficiency. The generated improvement proposals are then optimized again through the generative AI model. For example, it generates an efficiency proposal such as "centralizing inventory confirmation procedures."

[0142] Terminal

[0143] The device displays the generated improvement proposal to the user, who can then review it and provide feedback. Specifically, the device displays the improvement proposal on the screen, and the user submits feedback by pressing the "improvement proposal approval button."

[0144] Evaluating and applying improvements

[0145] User

[0146] The user evaluates the proposed improvement plan, and if they decide to apply it, they send a confirmation to the server via their device.

[0147] server

[0148] The server receives the user's confirmation, updates the workflow, and makes the new workflow executable. For example, the user evaluates the improvement proposal from their terminal, and after approval, presses the "Confirm and Send" button to send it to the server. The server updates the workflow and generates a new workflow.

[0149] Implementing and monitoring updated workflows

[0150] server

[0151] The server executes the new workflow and monitors its execution in real time. The monitoring data is saved in a log for later analysis.

[0152] Terminal

[0153] The terminal displays the execution status data received from the server to the user in real time. For example, the terminal displays the progress status of the business flow being executed in real time, and the user can check it.

[0154] Anomaly detection and generation of new improvement suggestions

[0155] server

[0156] The server detects anomalies and bottlenecks while the business flow is in progress, and generates an alert if a certain performance indicator cannot be exceeded. When an anomaly or bottleneck is detected, a new improvement proposal is generated. For example, the server detects that the time taken for "inventory check" is abnormally long and generates an alert. Based on this, a new improvement proposal to "transfer inventory checks to an automated system" is generated and presented to the user.

[0157] Prompt Sentence Examples

[0158] Please tell me how to enter customer information.

[0159] "Please suggest ways to automate inventory checks."

[0160] "Please tell me the efficient order processing flow."

[0161] In this way, the present invention executes a series of processes from inputting business information to automatically generating a flow, integrating and analyzing multiple business flows, generating and presenting improvement proposals for efficiency, implementing and monitoring the revised business flow, detecting anomalies, and generating new improvement proposals, thereby achieving improved and optimized business efficiency.

[0162] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0163] Step 1: Enter your business information

[0164] User

[0165] The user uses the terminal to input business information such as the name of each procedure, detailed procedure content, dependencies, and person in charge. After inputting the information, the user clicks the "Send" button to send the business information to the server.

[0166] Specific actions

[0167] The user enters the business procedure into the terminal, such as "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order", and clicks the "Send button".

[0168] input

[0169] Business procedures, detailed procedure content, dependencies, and person information.

[0170] output

[0171] Sending business information to the server.

[0172] Step 2: Send data to the AI ​​model and train it

[0173] server

[0174] The server receives business information sent from the device and inputs the data into the generative AI model using Python, TensorFlow, etc. The generative AI model learns based on this data.

[0175] Specific actions

[0176] The server inputs the received business procedure data into the AI ​​model and starts the "business flow optimization process."

[0177] input

[0178] Business information data.

[0179] output

[0180] Learned business flow dependencies and efficient flow.

[0181] Step 3: Automatic generation of business flow

[0182] server

[0183] The server obtains the optimized workflow from the generative AI model that has completed training, and automatically generates a workflow diagram based on that data. A visually displayable diagram is generated using a library such as Graphviz.

[0184] Specific actions

[0185] The server receives the optimized business procedures from the AI ​​model and generates a "business flow diagram" using Graphviz.

[0186] input

[0187] Data for optimized business flows.

[0188] output

[0189] Business flow diagram.

[0190] Step 4: Presenting the generated workflow

[0191] Terminal

[0192] The terminal displays the generated business flow diagram to the user, who can then check the generated flow and make any necessary corrections.

[0193] Specific actions

[0194] The terminal displays the generated business flow diagram on the screen, and the user clicks the "Confirm button" to confirm the contents.

[0195] input

[0196] The generated business flow diagram.

[0197] output

[0198] A workflow diagram displayed to the user.

[0199] Step 5: Integrate and analyze multiple workflows

[0200] User

[0201] Users upload multiple existing business processes collected from different departments and projects to the server via their terminal in CSV or Excel format.

[0202] server

[0203] The server analyzes the uploaded workflows to detect duplication, inconsistencies, and unnecessary steps. It uses the Python "Pandas" library to perform data analysis.

[0204] Specific actions

[0205] Users upload multiple business flow data using their devices, and the server analyzes it.

[0206] input

[0207] Data from multiple existing business processes.

[0208] output

[0209] Duplicate and inconsistency detection results.

[0210] Step 6: Generate and present improvement proposals

[0211] server

[0212] Based on the analysis results, the server integrates each business flow and generates improvement proposals for efficiency. These improvement proposals are then optimized again through the generative AI model.

[0213] Specific actions

[0214] The server generates efficiency proposals such as "centralizing inventory confirmation procedures" and provides them to the user in an optimized form.

[0215] input

[0216] Analysis results and data for generating improvement proposals.

[0217] output

[0218] Optimized improvement suggestions.

[0219] Terminal

[0220] The device displays the generated improvement suggestions to the user, who can review them and provide feedback.

[0221] Specific actions

[0222] The device displays the improvement proposal on the screen, and the user presses the "improvement proposal approval button" to submit feedback.

[0223] input

[0224] Generated improvement suggestions.

[0225] output

[0226] The suggested improvements shown to the user.

[0227] Step 7: Evaluate and apply the improvements

[0228] User

[0229] The user evaluates the proposed improvement plan and decides whether to apply it. If they decide to apply it, they send a confirmation to the server via their device.

[0230] server

[0231] The server receives the user's confirmation, updates the workflow, and makes the new workflow executable.

[0232] Specific actions

[0233] The user evaluates the improvement proposal from their device, and after approval, presses the "Confirm and Send" button to send it to the server. The server updates the workflow and creates a new workflow.

[0234] input

[0235] User feedback and confirmation.

[0236] output

[0237] A new work flow that can be implemented.

[0238] Step 8: Implement and monitor the updated workflow

[0239] server

[0240] The server executes the new workflow and monitors its execution in real time. The monitoring data is saved in a log for later analysis.

[0241] Specific actions

[0242] The server implements the new workflow and monitors its progress.

[0243] input

[0244] Data for the new business flow.

[0245] output

[0246] Monitoring log data.

[0247] Terminal

[0248] The terminal displays the execution status data received from the server to the user in real time.

[0249] Specific actions

[0250] The terminal displays the progress of the business flow being executed in real time, and the user can check it.

[0251] input

[0252] Data on the running business flow.

[0253] output

[0254] The execution status displayed to the user.

[0255] Step 9: Anomaly detection and notification

[0256] server

[0257] The server generates alerts based on performance indicators to detect anomalies and bottlenecks during the workflow, and if anomalies or bottlenecks are detected, it generates new improvement proposals.

[0258] Specific actions

[0259] The server detects that the "inventory check" time is abnormally long and generates an alert.

[0260] input

[0261] Performance data for the running business flow.

[0262] output

[0263] Anomaly detection alerts and improvement suggestions.

[0264] Step 10: Generate new improvement suggestions

[0265] server

[0266] If the server detects an anomaly or bottleneck, it generates a new improvement proposal, such as "shift inventory checks to an automated system," and presents it to the user.

[0267] Specific actions

[0268] The server detects the anomaly and generates a new improvement proposal, such as "transfer inventory checks to an automated system," and presents it to the user.

[0269] input

[0270] Anomaly detection data.

[0271] output

[0272] New improvement proposals.

[0273] (Application example 1)

[0274] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0275] Optimizing and streamlining workflows is a key issue for logistics centers. It is necessary to minimize time and cost waste and improve overall operational performance in a series of procedures, including receiving, sorting, shelving, picking, packing, and shipping. However, traditional methods make it difficult to optimize workflows, and there is a problem of being unable to quickly respond to bottlenecks or abnormalities that occur during operations.

[0276] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0277] In this invention, the server includes means for inputting business information, means for training an AI model to learn the input business information, means for automatically generating a business flow based on the learned business information, means for reading multiple business flows, analyzing overlaps and inconsistencies, and generating improvement proposals, means for presenting the generated improvement proposals, and means for optimizing procedures for receiving, sorting, shelving, picking, packing, and shipping items in logistics operations, thereby enabling optimization and improvement of business flows in logistics centers.

[0278] "Business information" refers to information such as the name of each business procedure, detailed procedure content, dependencies, and person in charge.

[0279] An "AI model" refers to an artificial intelligence system that learns from business information and generates and improves optimal business flows.

[0280] "Business flow" refers to the flow of a series of procedures or processes set up to carry out a specific task.

[0281] "Overlap" refers to a situation in which the same procedure is repeated in different business flows.

[0282] "Inconsistency" refers to a situation in which procedures and processes do not match between multiple business flows.

[0283] "Improvement proposals" refer to proposed changes or corrections to improve the efficiency and optimization of business processes.

[0284] "Logistics operations" refers to a series of business processes such as receiving, sorting, putting away, picking, packing, and shipping goods.

[0285] "Optimization" refers to building and adjusting business processes in the most efficient and effective way for specified purposes and conditions.

[0286] A "bottleneck" refers to a part or step in a business flow that hinders efficiency or progress.

[0287] The present invention is a system for optimizing and improving the workflow in a logistics center. A specific embodiment of the system is described below.

[0288] System configuration

[0289] The system consists of the following components:

[0290] A means of entering business information

[0291] A means of training an AI model based on input business information

[0292] A means of automatically generating workflows based on learned business information

[0293] A means of reading multiple business processes, analyzing overlaps and inconsistencies, and generating improvement proposals

[0294] A means of presenting generated improvement proposals

[0295] A means of optimizing the receiving, sorting, putting away, picking, packing, and shipping procedures of logistics operations

[0296] Hardware and software used

[0297] Hardware: Servers (for data processing and storage), terminals (for users to input business information)

[0298] Software: Flask (web framework), AI model (for learning and generating business flows)

[0299] Program processing explanation

[0300] User: Enters operational information using a device (such as a smartphone or tablet), including procedures for receiving, sorting, putting away, picking, packing, and shipping items.

[0301] Server: Receives business information entered by users and sends it to the AI ​​model for learning. Based on the learning data, it automatically generates efficient business flows.

[0302] AI model: Uses business information to learn about dependencies and optimal workflows within business processes, and returns the generated workflow to the server.

[0303] Server: Analyzes multiple business processes and detects duplications and inconsistencies. Based on the results, it generates improvement proposals and presents them to the user.

[0304] Terminal: Improvement proposals, anomalies, and bottlenecks are displayed to the user in real time, allowing the user to review and evaluate updates to the workflow.

[0305] Server: Updates the business flow based on user feedback and implements the optimized flow. It also monitors the implementation status in real time, detects new anomalies and bottlenecks, and makes new proposals.

[0306] Specific examples

[0307] For example, if a logistics center has the following workflow:

[0308] Receiving goods

[0309] classification

[0310] Shelving

[0311] picking

[0312] packing

[0313] shipping

[0314] When the user inputs these steps into their device, the server trains the AI ​​model. The AI ​​model learns the dependencies and efficiency of each input step and generates an optimal workflow. The generated workflow is presented to the user by the server and is further improved based on subsequent feedback.

[0315] Example prompt sentence:

[0316] You are considering optimizing the workflow at your distribution center. Follow these steps to generate the most efficient workflow:

[0317] 1. Receiving your items

[0318] 2. Classification

[0319] 3. Shelving

[0320] 4. Picking

[0321] 5. Packaging

[0322] 6. Shipping

[0323] Please also suggest improvements to the above flow to improve its efficiency.

[0324] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0325] Step 1:

[0326] The user inputs business information into the terminal.

[0327] The business information to be entered includes the procedures for receiving, sorting, putting away, picking, packing, and shipping. For example, the flow "receiving goods -> sorting -> putting away -> picking -> packing -> shipping" is entered. This collects information such as the name of the business procedure, detailed procedure content, dependencies, and person in charge.

[0328] Step 2:

[0329] The server receives the business information sent from the terminal.

[0330] The server sends the input business information to the AI ​​model, and learning begins. The input data includes the flow of business procedures and their dependencies. The AI ​​model uses this data to learn the dependencies between each procedure and the efficient flow.

[0331] Step 3:

[0332] The server automatically generates a business flow based on the learned business information.

[0333] The server receives the optimal workflow returned by the AI ​​model and automatically generates this workflow, for example, arranging the steps of "receiving goods -> sorting -> shelving -> picking -> packing -> shipping" in the most efficient way.

[0334] Step 4:

[0335] A user uploads multiple existing business processes to a server via a terminal.

[0336] To integrate different flows, the user sends an existing business flow to the server, which then integrates multiple business flows, including overlapping and inconsistent flows, into the server.

[0337] Step 5:

[0338] The server analyzes multiple business flows and detects duplications and inconsistencies.

[0339] The server uses the analyzed data to detect duplication and inconsistencies in business flows. For example, if the same procedure exists in multiple flows, it detects this and generates improvement proposals.

[0340] Step 6:

[0341] Based on the detection results, the server generates improvement proposals for efficiency.

[0342] The server generates improvement proposals to optimize the workflow based on the detected duplications and inconsistencies. For example, it may generate an improvement proposal to "consolidate inventory checks."

[0343] Step 7:

[0344] The terminal presents the generated improvement proposal to the user.

[0345] The user can then view the proposed improvements from the server via their device. The improvements are displayed visually as a workflow diagram, allowing the user to evaluate them and make any necessary changes.

[0346] Step 8:

[0347] The server monitors the implementation status of the business flow in real time.

[0348] The server monitors the execution of the updated workflow and detects anomalies and bottlenecks, for example, if a particular step takes longer than expected.

[0349] Step 9:

[0350] The device displays notifications to the user about detected anomalies and bottlenecks.

[0351] Users can receive notifications from the server via their devices and be aware of any problems with the progress of their work, enabling them to take prompt action.

[0352] Step 10:

[0353] The server generates new improvement proposals based on the anomalies and bottlenecks and presents them to the user again.

[0354] Based on the detected anomalies and bottlenecks, the server generates improvement proposals for further efficiency improvements and notifies the user via the terminal. For example, a new improvement proposal might be presented, such as "shifting inventory checks to an automated system."

[0355] This allows users to constantly optimize the progress of their work.

[0356] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0357] This invention combines a system that uses AI to automatically generate workflows based on business information and continuously improves those workflows with an emotion engine that analyzes user emotions. This system starts with the input of business information, then learns using an AI model, analyzes the automatically generated workflow and proposes improvements, and then customizes it according to the user's emotions.

[0358] 1. Entering and learning business information

[0359] User

[0360] The user uses a terminal to input business information, including the name, details, dependencies, and person in charge information for each step.

[0361] Specific examples

[0362] For example, the user inputs procedures such as "enter customer information," "confirm order," "check inventory," "place order," and "confirm order" into the terminal.

[0363] Terminal

[0364] The terminal sends the entered business information to the server, where the information is transferred using a secure communication protocol.

[0365] server

[0366] The server receives the business information and inputs it into the AI ​​model, which then learns from it and understands the dependencies and flow of each step.

[0367] 2. Automatic creation and presentation of business flows

[0368] server

[0369] The server automatically generates the optimal workflow based on the learned information, taking into account the dependencies between each step to create the most efficient workflow.

[0370] Terminal

[0371] The terminal displays the generated business flow diagram to the user, allowing the user to grasp the overall picture of the business flow.

[0372] 3. Integration of multiple workflows and proposal of improvements

[0373] User

[0374] Users can upload multiple existing business processes to the server via their terminals.

[0375] server

[0376] The server analyzes these workflows and detects duplications and inconsistencies. For example, it detects cases where the "Stock Check" step overlaps between the "Customer Management Flow" and the "Inventory Management Flow."

[0377] Specific examples

[0378] The server detects duplication of inventory check steps and generates an improvement plan to "consolidate the inventory check steps."

[0379] 4. Evaluation and implementation of improvement plans

[0380] server

[0381] The server generates improvement proposals and sends them to the terminal, which then presents the proposals to the user.

[0382] User

[0383] The user evaluates the proposed improvements and decides whether to apply them. If so, the device sends a confirmation to the server.

[0384] server

[0385] The server receives the user's confirmation, updates the workflow, and makes the new workflow available for execution.

[0386] 5. Emotional Engine Response

[0387] server

[0388] The server uses an emotion engine to identify the user's feelings toward the proposed improvement proposals, analyzing feedback, facial expressions, and voice inputs in real time as the user reviews the improvement proposals.

[0389] Specific examples

[0390] If the user responds positively to the improvement proposal (e.g., satisfaction or joy), the server reads that information and recommends implementing the improvement proposal. Conversely, if the user responds negatively (e.g., dissatisfaction or confusion), the server proposes a different improvement proposal.

[0391] Terminal

[0392] The device provides feedback to the user based on the emotion engine and offers suggestions for improvements that will increase user satisfaction, thereby increasing user motivation and helping to improve work efficiency.

[0393] 6. Real-time monitoring and re-proposal of business flows

[0394] server

[0395] The server monitors the execution status of the updated business flow in real time, immediately detecting any abnormalities or bottlenecks that occur during business operations.

[0396] Specific examples

[0397] If the server detects a bottleneck in the inventory check step, it notifies the user of the impact and uses an emotion engine to suggest new improvement ideas.

[0398] In this way, this system integrates automation and a human-centered approach, starting with the input of business information, followed by learning using an AI model, automatic generation of business flows, suggesting improvement plans, and analyzing user emotions using an emotion engine. This allows users to build and improve efficient business flows even without detailed business knowledge.

[0399] The processing flow will be explained below.

[0400] Step 1:

[0401] The user inputs business information through a terminal. Business information includes the name of each procedure, detailed procedure content, dependencies, and person in charge. For example, specific business procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation" are input.

[0402] Step 2:

[0403] The terminal sends the entered business information to the server. The data is sent using a secure communication protocol.

[0404] Step 3:

[0405] The server inputs the business information received from the device into the AI ​​model, which learns this information and understands the dependencies between each business step and the most efficient execution order.

[0406] Step 4:

[0407] The server automatically generates a workflow based on the learned business information. The generated workflow is constructed taking into account the optimal dependencies between each step.

[0408] Step 5:

[0409] The server sends the generated business flow diagram to the terminal, which displays the flow diagram to the user, allowing the user to grasp the overall picture of the business flow.

[0410] Step 6:

[0411] Users can upload multiple existing business flows to the server via their terminal. For example, they can upload the "Customer Management Flow" of Department A and the "Inventory Management Flow" of Department B.

[0412] Step 7:

[0413] The server analyzes the received workflows and detects duplications and inconsistencies. For example, it detects that the "Inventory Check" step is duplicated in both departments A and B.

[0414] Step 8:

[0415] The server generates improvement proposals based on the analysis results to improve operational efficiency, such as "centralizing the inventory check step."

[0416] Step 9:

[0417] The server sends the generated improvement plan to the terminal, which then presents the improvement plan to the user and indicates the specific changes to be made.

[0418] Step 10:

[0419] The user evaluates the proposed improvements and decides whether to apply them. If so, the user sends a confirmation from the terminal to the server.

[0420] Step 11:

[0421] The server receives confirmation from the user and updates the workflow, which is then put into effect and made available for execution.

[0422] Step 12:

[0423] The server monitors the execution status of the updated business flow in real time, and if an abnormality or bottleneck occurs, the server immediately detects it.

[0424] Step 13:

[0425] The server generates new improvement plans based on the detected anomalies and bottlenecks and presents them to the user again, further improving business efficiency.

[0426] Step 14:

[0427] The server uses an emotion engine to analyze the user's emotions regarding the proposed improvement proposals. It analyzes the user's reactions (facial expressions, voice, input content, etc.) in real time to identify emotions.

[0428] Step 15:

[0429] The device will provide feedback based on the user's emotions based on the analysis results of the emotion engine. For example, if the reaction is positive, it will recommend an improvement plan, and if the reaction is negative, it will suggest a different improvement plan.

[0430] In this way, the present invention is a system that covers everything from business information to learning using AI models, automatically generated business flows and improvement suggestions, and even responses that take user emotions into consideration, providing a comprehensive solution for maximizing business efficiency.

[0431] Example 2

[0432] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0433] Conventional business management systems were inefficient because they required manual creation of business flows and human intervention to make improvement proposals. Furthermore, they were unable to consider the user's feelings and reactions, and improvement proposals sometimes did not contribute to user satisfaction.

[0434] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting business information, a means for training an artificial intelligence model on the input business information, a means for automatically generating business procedures based on the trained business information, a means for reading multiple business procedures, analyzing overlaps and inconsistencies, and generating improvement proposals, a means for presenting the generated improvement proposals, and a means for analyzing user emotions and generating responses to the presented improvement proposals. This makes it possible to automatically generate business flows and provide improvement proposals that take user satisfaction into consideration.

[0435] "Business information" is a general term for information necessary for generating and analyzing business flows, such as business procedures, details, dependencies, and person in charge information.

[0436] An "artificial intelligence model" is a type of algorithm that learns specific tasks based on large amounts of data and automatically generates business processes and suggests improvements.

[0437] A "business procedure" refers to a series of steps or processes taken to accomplish a particular task.

[0438] "Improvement proposals" are proposed changes or advice automatically generated by the system with the aim of streamlining and optimizing business procedures.

[0439] "User emotion" refers to the emotional state that results from analyzing the feedback and reactions that the user gives to the system.

[0440] An "abnormality" refers to an unexpected event or error that occurs during the course of business procedures.

[0441] A "bottleneck" is a part of a business process that causes a decrease in efficiency or delays in work.

[0442] This invention is a system that uses artificial intelligence to automatically generate work procedures based on work information and analyzes user emotions. This system starts with the input of work information, then learns using an artificial intelligence model, analyzes the automatically generated work procedures and proposes improvements, and then customizes them according to the user's emotions.

[0443] Entering and learning business information

[0444] User

[0445] The user uses a terminal to input business information. Specific input content includes the name of the procedure, details, dependencies, and person in charge information. For example, the user inputs procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation."

[0446] Terminal

[0447] The terminal sends the entered business information to the server, using a secure communication protocol (e.g., HTTPS) to transfer the information.

[0448] server

[0449] The server stores the received business information in a database. The business information retrieved from the database is then fed into the AI ​​model, which begins the learning process. The AI ​​model analyzes the provided data and understands the dependencies and flow of each step.

[0450] Automatic creation and presentation of business procedures

[0451] server

[0452] The server automatically generates optimal business procedures based on the learned information. The generated procedures are constructed efficiently, taking into account the dependencies between procedures.

[0453] Terminal

[0454] The terminal displays the business procedure diagram generated by the server to the user. This display uses a visualization tool such as a flowchart generator, allowing the user to grasp the overall picture of the business procedure.

[0455] Integration of multiple business procedures and proposal of improvements

[0456] User

[0457] Users upload multiple existing business procedures to the server via their terminal, which makes it possible to integrate and compare multiple business procedures.

[0458] server

[0459] The server analyzes the uploaded business procedures and detects duplications and inconsistencies. For example, it detects duplication of the "inventory check" step between "customer management procedures" and "inventory management procedures." This analysis process is performed using a data analysis algorithm.

[0460] Specific examples

[0461] Based on the detection result that "the inventory check steps are duplicated," the server generates an improvement plan to "consolidate the inventory check steps."

[0462] Evaluating and implementing improvement plans

[0463] server

[0464] The server sends the generated improvement proposal to the terminal. The improvement proposal includes specific steps and benefits, and is presented in a format that is easy for the user to understand.

[0465] User

[0466] The user evaluates the proposed improvement proposals and decides whether to apply them. If the user confirms the application, the user sends feedback from the device to the server.

[0467] server

[0468] The server receives user feedback and updates the business procedures. New business procedures are constructed by referencing existing data and are set to an executable state.

[0469] Emotion engine response

[0470] server

[0471] The server uses an emotion engine to analyze the user's reactions in real time, analyzing feedback, facial expressions, and voice data to identify the user's emotional state.

[0472] Specific examples

[0473] If the user expresses positive emotions (satisfaction or joy) toward the improvement proposal, the server retains that information and recommends implementing the improvement proposal. Conversely, if the user expresses negative emotions (dissatisfaction or confusion), a different improvement proposal is presented.

[0474] Terminal

[0475] The device displays the results of the emotion engine to the user, who receives new suggestions based on the feedback and can select the improvement suggestions that best suit their needs.

[0476] Real-time monitoring and revision of business procedures

[0477] server

[0478] The server monitors the implementation status of the updated business procedures in real time, and if an abnormality or bottleneck is discovered during the business process, it immediately detects it and notifies the user.

[0479] Specific examples

[0480] If the server detects a bottleneck during the inventory check step, it immediately notifies the user of the impact and uses an emotion engine to suggest new improvement ideas.

[0481] Example prompts to be input to the generative AI model

[0482] Example prompts

[0483] "The user enters business information such as customer information, order confirmation, inventory check, order placement, and order confirmation. If there are dependencies between these steps, generate the optimal business flow. Also, based on the user's reaction to the proposed improvements, use an emotion engine to make new suggestions."

[0484] As described above, this invention is a system that starts with inputting business information, learns using an AI model, automatically generates business procedures, and then uses an emotion engine to provide user-friendly improvement suggestions. This allows users to build and improve efficient business procedures even without detailed business knowledge.

[0485] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0486] Step 1:

[0487] User

[0488] The user uses a terminal to input business information, including the name of the procedure (e.g., "Enter customer information," "Order confirmation," "Inventory check," "Place order," "Order confirmation," etc.), details, dependencies, and person in charge.

[0489] Input: Business information entered by the user (procedure name, details, dependencies, person in charge information)

[0490] Output: Business information stored on the device

[0491] Step 2:

[0492] Terminal

[0493] The terminal sends the entered business information to the server, using a secure communication protocol (e.g., HTTPS) to transfer the information.

[0494] Input: Business information entered in Step 1

[0495] Output: Business information sent to the server

[0496] Step 3:

[0497] server

[0498] The server stores the received business information in a database. The business information retrieved from the database is then fed into an AI model to begin the learning process. The AI ​​model analyzes the provided data and understands the dependencies and flow of each step.

[0499] Input: Business information sent from the terminal

[0500] Output: Data trained by the AI ​​model

[0501] Step 4:

[0502] server

[0503] The server automatically generates optimal business procedures based on the learned information. The generated procedures are constructed efficiently, taking into account the dependencies between procedures.

[0504] Input: Trained data

[0505] Output: Generated business procedures

[0506] Step 5:

[0507] Terminal

[0508] The terminal displays the business procedure diagram generated by the server to the user. This display uses a visualization tool such as a flowchart generator, allowing the user to grasp the overall picture of the business procedure.

[0509] Input: Generated business procedure

[0510] Output: Business procedure diagram displayed on the terminal

[0511] Step 6:

[0512] User

[0513] Users upload multiple existing business procedures to the server via their terminal, which makes it possible to integrate and compare multiple business procedures.

[0514] Input: Existing business procedures uploaded by the user

[0515] Output: Multiple business procedures uploaded to the server

[0516] Step 7:

[0517] server

[0518] The server analyzes the uploaded business procedures and detects duplications and inconsistencies. For example, it detects duplication of the "inventory check" step between "customer management procedures" and "inventory management procedures." This analysis process is performed using a data analysis algorithm.

[0519] Input: Multiple Business Procedures

[0520] Output: Detected duplicates and inconsistencies

[0521] Step 8:

[0522] server

[0523] Based on the detection results, the server generates appropriate improvement suggestions, such as consolidating overlapping steps.

[0524] Input: Detected duplicates and inconsistencies

[0525] Output: Improvement suggestions

[0526] Step 9:

[0527] server

[0528] The server then sends the generated improvement proposals to the terminal and presents them to the user. The proposals include specific steps and their benefits.

[0529] Input: Improvement suggestion

[0530] Output: Improvement suggestions sent to the device

[0531] Step 10:

[0532] User

[0533] The user evaluates the proposed improvement suggestions and decides whether to apply them. The evaluation results and feedback are entered into the terminal and sent to the server.

[0534] Input: User ratings and feedback

[0535] Output: Rating and feedback sent to the server

[0536] Step 11:

[0537] server

[0538] The server updates business procedures based on user feedback. New procedures are built by referencing existing data and set to executable status.

[0539] Input: Ratings and Feedback

[0540] Output: Updated business procedures

[0541] Step 12:

[0542] server

[0543] The server uses an emotion engine to analyze the user's reactions in real time, analyzing feedback, facial expressions, and voice data to identify the user's emotional state.

[0544] Input: User feedback, facial expressions, and voice data

[0545] Output: Identified emotional state

[0546] Step 13:

[0547] server

[0548] The server adjusts the improvement suggestions based on the user's emotional state: if the emotion is positive, it recommends a suggestion, and if the emotion is negative, it presents a different suggestion.

[0549] Input: Identified emotional state

[0550] Output: Adjusted improvement suggestions

[0551] Step 14:

[0552] Terminal

[0553] The device displays the results of the emotion engine to the user and provides new suggestions, allowing the user to select the improvement suggestions that best suit their needs.

[0554] Input: Adjusted improvement suggestions

[0555] Output: The new proposal displayed to the user

[0556] Step 15:

[0557] server

[0558] The server monitors the implementation status of the updated business procedures in real time, and if an abnormality or bottleneck is discovered during the business process, it immediately detects it and notifies the user.

[0559] Input: Updated business procedures

[0560] Output: Real-time monitoring results and abnormality notifications

[0561] (Application example 2)

[0562] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0563] Conventional workflow automatic generation systems have limitations in terms of improving and optimizing workflow efficiency. Furthermore, continuous improvements that take user emotions and feedback into account are rare, making continuous improvement of workflows difficult. Furthermore, when robots perform work in factories, real-time monitoring and improvement proposals are necessary to improve the effectiveness of the workflow, but efficient methods for doing this have not yet been established. Furthermore, there is a need for a system that can determine whether proposed improvements are appropriate based on user emotions.

[0564] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0565] In this invention, the server includes means for inputting business information, means for training an AI model to learn the input business information, means for automatically generating a business flow based on the learned business information, means for reading multiple business flows, analyzing overlaps and inconsistencies, and generating improvement proposals, means for presenting the generated improvement proposals, means for analyzing user emotions, and means for evaluating the proposed improvement proposals based on the emotion analysis and re-proposing them as necessary. This makes it possible to optimize business flows while taking user emotions into consideration, and to monitor and propose improvements in real time.

[0566] "Business information" is information that includes procedures, processes, people, dependencies, etc. related to the operation of a company or organization.

[0567] An "AI model" is an algorithm and its settings that uses artificial intelligence technology to learn from data and perform pattern recognition and prediction.

[0568] A "business flow" is a set of procedures or processes set up to accomplish a specific task.

[0569] "Automatically generating" means that the system automatically generates results based on pre-set algorithms or rules.

[0570] "Duplicate" means that there are multiple identical or similar procedures or data.

[0571] An "inconsistency" is when multiple procedures or data are inconsistent or inconsistent.

[0572] "Improvements" are suggestions or changes to make current processes or procedures more efficient or effective.

[0573] "User emotions" refers to the emotional reactions and feedback given by system users.

[0574] "Analyzing" means collecting data or information and analyzing it to find meaning and patterns.

[0575] "Real time" refers to the ability to process ongoing events and actions and provide results immediately.

[0576] A "bottleneck" is a factor or obstacle that slows down the overall progress of a task or process.

[0577] A "re-proposal" is a proposal that is presented again to improve something that was previously proposed, based on new information or feedback.

[0578] "Customization" means adapting or modifying a system or process to meet specific requirements or needs.

[0579] 1. An overview of the system that realizes this application example is given below. The system automatically generates, monitors, and improves the work flow of robots used in factories in real time, and is composed of the following main components.

[0580] 2. The server has a means of inputting business information. Procedures, processes, personnel, dependencies, and other information related to the operation of a company or organization are input via a terminal. Based on this, the server trains an AI model based on the input business information. Specific AI technologies used include TensorFlow and Keras.

[0581] 3. The AI ​​model learns from the submitted business information and has the means to automatically generate a business flow. Based on the learned information, it constructs the most efficient business flow. This generated business flow is displayed on the terminal in real time by the server.

[0582] 4. The server has a means to read multiple business flows, analyze overlaps and inconsistencies, and generate improvement proposals. This allows overlaps and inconsistencies between business flows to be discovered and improvement proposals to resolve them to be proposed.

[0583] 5. The server has a means to present the generated improvement proposals and a means to analyze the user's emotions. The user inputs feedback through a device, smart glasses, or a head-mounted display, and the emotions are analyzed. OpenCV and a specific emotion analysis model are used for the analysis.

[0584] 6. The server has the means to evaluate the proposed improvement plan based on the user's sentiment analysis and re-propose it if necessary. If the user's sentiment is negative, the AI ​​model recalculates the workflow and proposes a new improvement plan.

[0585] 7. Furthermore, the server has the means to monitor the execution status of the business flow in real time and detect anomalies and bottlenecks. If an anomaly is detected, the server will again propose improvements, taking into account the user's emotional data.

[0586] 8. The user has the means to evaluate and confirm the revised workflow. After confirmation, the server updates the workflow and puts the new workflow into operation. The server can also customize the workflow based on the user's emotional data.

[0587] Examples:

[0588] In a factory, robots assemble parts one by one. To optimize this workflow, a server automatically generates a workflow and monitors it in real time. For example, a new workflow proposal might be generated to "rearrange the order of parts." However, if a worker shows a confused expression, an emotion analysis engine detects this and the server reconsiders the workflow. For example, it might suggest a different improvement, such as "changing the placement of assembly tools."

[0589] Example prompt sentence:

[0590] "A new workflow has been generated that rearranges the order of parts. The worker's emotional data revealed a confused response. Based on this response, please suggest another workflow improvement."

[0591] In this way, the invention makes it possible to optimize workflows while taking into account the user's emotions, and realizes real-time monitoring and improvement suggestions.

[0592] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0593] Step 1:

[0594] The user inputs business information into the device. The device then sends the input business information, such as procedures, processes, personnel, and dependencies, to the server. The server receives this information and inputs it into the AI ​​model. The server then uses TensorFlow and Keras to train the business information. The input is the business information, and the output is the trained business model.

[0595] Step 2:

[0596] The server automatically generates a workflow based on the learned business information. The AI ​​model constructs an optimal workflow based on the received business information. This workflow is efficiently assembled, taking into account the dependencies between steps. The generated workflow is sent from the server to the terminal, which displays it to the user. The input is the trained business model, and the output is the generated workflow.

[0597] Step 3:

[0598] The server loads multiple business processes and analyzes them for overlaps and inconsistencies. The server analyzes each step in the business process and detects any overlaps or inconsistencies. The server uses an AI model to generate improvement proposals. For example, it generates proposals to unify overlapping steps. The input is multiple business processes, and the output is improvement proposals.

[0599] Step 4:

[0600] The server sends the generated improvement proposals to the terminal and presents them to the user. The user evaluates the improvement proposals and provides feedback through the terminal. This feedback also includes the user's emotional data. The input is the improvement proposals, and the output is the user's feedback and emotional data.

[0601] Step 5:

[0602] The server analyzes the user's emotions. It uses OpenCV or a specific emotion analysis model to analyze the user's facial and voice data collected from the device, smart glasses, or head-mounted display. For example, if the user shows a dissatisfied expression, it is interpreted as a negative emotion. The input is the user's emotional data, and the output is the analysis result.

[0603] Step 6:

[0604] The server reevaluates improvement proposals based on sentiment analysis and re-proposes them if necessary. If the user's sentiment is negative, a new improvement proposal for the business process is regenerated using an AI model. This is an important means of increasing user satisfaction. The input is the sentiment analysis results, and the output is the re-proposed improvement proposal.

[0605] Step 7:

[0606] The server monitors the execution status of the business flow in real time and detects abnormalities and bottlenecks. For example, if there is a delay in the assembly of parts, the server will detect that step as a bottleneck. The input is real-time business data, and the output is detected abnormality information.

[0607] Step 8:

[0608] The server makes improvement suggestions based on the detected anomalies and bottlenecks. The detected anomalies and bottlenecks are analyzed using an AI model to generate optimal improvement suggestions. For example, improvement suggestions such as changing the placement of assembly tools are proposed. The input is the detected anomaly information, and the output is the improvement suggestions.

[0609] Step 9:

[0610] The user evaluates and confirms the revised workflow through the terminal. The confirmed workflow is updated by the server and put into execution. The workflow is customized taking into account the user's emotional data. The input is the user's confirmation and emotional data, and the output is the updated workflow.

[0611] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0612] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0613] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0614] [Second embodiment]

[0615] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0616] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0617] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0618] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0619] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0620] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0621] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0622] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0623] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0624] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0625] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0626] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0627] The present invention is a system that inputs business information, automatically generates business flows by learning them into an AI model, and then analyzes multiple business flows to propose improvement plans. This system is implemented as follows.

[0628] 1. Entering and learning business information

[0629] User

[0630] The user uses a terminal to input task information, including the name of each step, detailed procedure content, dependencies, and person in charge.

[0631] Specific examples

[0632] For example, a user inputs the following business procedure through a terminal: "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order."

[0633] server

[0634] The server receives the business information sent from the device and inputs it into the AI ​​model, which uses this data to learn about dependencies and efficient workflows.

[0635] 2. Automatic creation of business flows

[0636] server

[0637] The server automatically generates a workflow based on the business information learned by AI. The generated workflow takes into account the dependencies between each step, creating the most efficient workflow.

[0638] Specific examples

[0639] The server efficiently arranges the steps of "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order" and creates a business flow diagram.

[0640] Terminal

[0641] The terminal presents the generated workflow diagram to the user, allowing the user to grasp the overall picture of the workflow.

[0642] 3. Integration of multiple workflows and proposal of improvements

[0643] User

[0644] Users can upload multiple existing business processes to the server via their terminals.

[0645] server

[0646] The server analyzes these workflows to detect duplication and inconsistencies, and based on the results, generates improvement proposals for improving efficiency.

[0647] Specific examples

[0648] For example, if the "inventory check" procedure overlaps between Department A's "customer management flow" and Department B's "inventory management flow," the server will detect this overlap and generate an improvement proposal to "consolidate the inventory check step."

[0649] Terminal

[0650] The terminal presents the improvement proposals generated by the server to the user, who can then check and evaluate them.

[0651] 4. Evaluation and implementation of improvement plans

[0652] User

[0653] The user evaluates the proposed improvement plan and decides whether to apply it. If the improvement plan is applied, a confirmation is sent to the server via the terminal.

[0654] server

[0655] The server receives the user's confirmation and updates the workflow, which is then put into action and made live for the user to use.

[0656] 5. Collaboration and Monitoring

[0657] server

[0658] The server monitors the execution status of the updated business flow in real time, and immediately detects any abnormalities or bottlenecks that occur during the business process.

[0659] Terminal

[0660] The terminal displays a notification of any detected abnormalities or bottlenecks to the user, allowing the user to confirm that there is a problem with the progress of the business flow.

[0661] server

[0662] The server generates new improvement proposals based on the anomalies and bottlenecks and presents them to the user again.

[0663] Specific examples

[0664] For example, if the server detects that "inventory check" in the new workflow is taking longer than expected, a notification will be displayed on the terminal. The server will then suggest a new improvement plan: "Move inventory check to an automated system."

[0665] In this way, by executing a series of processes based on the present invention, from inputting business information to automatically generating a flow, proposing improvements, implementing them, and monitoring them, it is possible to improve business efficiency and strengthen cooperation.

[0666] The processing flow will be explained below.

[0667] Step 1:

[0668] The user inputs business information through a terminal. Business information includes the name of each procedure, detailed procedure content, dependencies, and person in charge. For example, the user might input procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation."

[0669] Step 2:

[0670] The terminal sends the entered business information to the server. The data is transmitted using a secure communication protocol.

[0671] Step 3:

[0672] The server inputs the business information received from the device into the AI ​​model, which uses this data to learn business dependencies and efficient processing sequences.

[0673] Step 4:

[0674] The server automatically generates a workflow based on the information learned by the AI ​​model. The generated workflow reflects the optimal dependencies between each step.

[0675] Step 5:

[0676] The server sends the generated business flow diagram to the terminal, where the user can view the diagram on the terminal screen.

[0677] Step 6:

[0678] Users can upload multiple existing business processes to the server via their terminals.

[0679] Step 7:

[0680] The server analyzes multiple workflows and detects duplications and inconsistencies. For example, it detects duplication of the "Stock Check" step between the "Customer Management Flow" and the "Inventory Management Flow."

[0681] Step 8:

[0682] Based on the analysis results, the server generates improvement proposals to improve business efficiency, such as "centralizing the inventory check step."

[0683] Step 9:

[0684] The server sends the generated improvement proposal to the terminal, which then presents it to the user, who then checks the contents of the improvement proposal.

[0685] Step 10:

[0686] The user evaluates the improvement plan and decides whether to apply it. If so, the terminal sends a confirmation to the server.

[0687] Step 11:

[0688] The server receives the user's confirmation and updates the workflow, making the new workflow available for execution.

[0689] Step 12:

[0690] The server monitors the execution status of the updated business flow in real time, and immediately detects any abnormalities or bottlenecks that occur.

[0691] Step 13:

[0692] The server generates new improvement proposals based on the detected anomalies and bottlenecks, such as "shift inventory checks to an automated system."

[0693] Step 14:

[0694] The server sends new improvement proposals to the terminal and presents them to the user again, who then checks them and considers how to respond.

[0695] Example 1

[0696] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0697] In today's business environment, streamlining and improving workflows is extremely important. However, conventional methods require a significant amount of time and effort to manually input and analyze business information, resulting in low accuracy in automatically generating workflows and improving proposals. Furthermore, it is difficult to integrate multiple workflows, detect overlaps and inconsistencies, and generate efficient improvement proposals. The present invention aims to solve these problems and provide a system that streamlines and optimizes workflows in real time.

[0698] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0699] In this invention, the server includes means for inputting business information, means for training a generative AI model on the input business information, means for automatically generating a business flow based on the trained business information, means for presenting the generated business flow, means for integrating and analyzing multiple business flows, detecting duplications and inconsistencies, and generating improvement proposals, and means for presenting the generated improvement proposals. This enables automatic input of business information, automatic generation of efficient workflows, integrated analysis of multiple business flows, and generation and presentation of optimized improvement proposals.

[0700] "Business information" is data such as business-related procedures, detailed procedure content, dependencies, and personnel in charge.

[0701] A "generative AI model" is an algorithm or machine learning model that learns business information and automatically generates optimal business flows and proposes improvements.

[0702] A "business flow" refers to the flow of a series of procedures or processes for carrying out a specific business operation.

[0703] "Automatic generation" means that the system automatically creates a business flow based on the input information without human intervention.

[0704] "Integration" means combining multiple business flows into one entity.

[0705] "Duplicate" refers to the occurrence of the same procedure multiple times in different business processes, which can lead to inefficiency.

[0706] "Inconsistency" refers to a state in which the order or content of a business flow is inconsistent.

[0707] "Improvement proposals" are specific proposals aimed at streamlining and optimizing business processes.

[0708] "Presentation" refers to the display of system-generated information or data in a form that is visible to the user.

[0709] "Monitoring" means continuously observing the execution status of a business flow and checking for any abnormalities or problems.

[0710] An "abnormality" is an unexpected problem or obstacle that occurs in the normal course of business.

[0711] A "bottleneck" is a procedure in a business flow that is slower to execute than other procedures and that causes a decrease in overall efficiency.

[0712] The present invention is a system that automatically generates workflows by inputting business information and training a generative AI model, and then analyzes multiple workflows to propose improvements. This system is implemented as follows.

[0713] Entering and learning business information

[0714] User

[0715] The user uses the terminal to input business information. This information includes the name of each step, detailed procedure content, dependencies, and the person in charge. For example, the user inputs the business procedure "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order" through the terminal. After completing the input, the user clicks the "Send button" to send the business information to the server.

[0716] server

[0717] The server receives business information sent from the device and inputs the data into a generative AI model using Python, TensorFlow, etc. This model retrains based on the received data, learning dependencies between business processes and efficient workflows.

[0718] Automatic creation of business flows

[0719] server

[0720] The server obtains the optimized business flow from the generative AI model that has completed training, and automatically generates a business flow diagram based on that data. Specifically, it uses libraries such as Graphviz to generate a diagram that can be displayed visually.

[0721] Presentation of business flow

[0722] Terminal

[0723] The terminal displays the generated business flow diagram to the user. The user can check the generated flow and make any necessary corrections. For example, the user can check the generated business flow diagram on the terminal and click the "Confirm" button to confirm the contents.

[0724] Integration and analysis of multiple workflows

[0725] User

[0726] Users upload multiple existing business processes collected from different departments and projects to the server via their terminal in CSV or Excel format.

[0727] server

[0728] The server analyzes the multiple workflows uploaded and detects duplication, inconsistencies, and unnecessary steps. For example, it uses the Python "Pandas" library to analyze the data and identify duplicate steps and inconsistencies.

[0729] Generate and present improvement proposals

[0730] server

[0731] Based on the analysis results, the server integrates each business flow and generates improvement proposals for efficiency. The generated improvement proposals are then optimized again through the generative AI model. For example, it generates an efficiency proposal such as "centralizing inventory confirmation procedures."

[0732] Terminal

[0733] The device displays the generated improvement proposal to the user, who can then review it and provide feedback. Specifically, the device displays the improvement proposal on the screen, and the user submits feedback by pressing the "improvement proposal approval button."

[0734] Evaluating and applying improvements

[0735] User

[0736] The user evaluates the proposed improvement plan, and if they decide to apply it, they send a confirmation to the server via their device.

[0737] server

[0738] The server receives the user's confirmation, updates the workflow, and makes the new workflow executable. For example, the user evaluates the improvement proposal from their terminal, and after approval, presses the "Confirm and Send" button to send it to the server. The server updates the workflow and generates a new workflow.

[0739] Implementing and monitoring updated workflows

[0740] server

[0741] The server executes the new workflow and monitors its execution in real time. The monitoring data is saved in a log for later analysis.

[0742] Terminal

[0743] The terminal displays the execution status data received from the server to the user in real time. For example, the terminal displays the progress status of the business flow being executed in real time, and the user can check it.

[0744] Anomaly detection and generation of new improvement suggestions

[0745] server

[0746] The server detects anomalies and bottlenecks while the business flow is in progress, and generates an alert if a certain performance indicator cannot be exceeded. When an anomaly or bottleneck is detected, a new improvement proposal is generated. For example, the server detects that the time taken for "inventory check" is abnormally long and generates an alert. Based on this, a new improvement proposal to "transfer inventory checks to an automated system" is generated and presented to the user.

[0747] Prompt Sentence Examples

[0748] Please tell me how to enter customer information.

[0749] "Please suggest ways to automate inventory checks."

[0750] "Please tell me the efficient order processing flow."

[0751] In this way, the present invention executes a series of processes from inputting business information to automatically generating a flow, integrating and analyzing multiple business flows, generating and presenting improvement proposals for efficiency, implementing and monitoring the revised business flow, detecting anomalies, and generating new improvement proposals, thereby achieving improved and optimized business efficiency.

[0752] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0753] Step 1: Enter your business information

[0754] User

[0755] The user uses the terminal to input business information such as the name of each procedure, detailed procedure content, dependencies, and person in charge. After inputting the information, the user clicks the "Send" button to send the business information to the server.

[0756] Specific actions

[0757] The user enters the business procedure into the terminal, such as "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order", and clicks the "Send button".

[0758] input

[0759] Business procedures, detailed procedure content, dependencies, and person information.

[0760] output

[0761] Sending business information to the server.

[0762] Step 2: Send data to the AI ​​model and train it

[0763] server

[0764] The server receives business information sent from the device and inputs the data into the generative AI model using Python, TensorFlow, etc. The generative AI model learns based on this data.

[0765] Specific actions

[0766] The server inputs the received business procedure data into the AI ​​model and starts the "business flow optimization process."

[0767] input

[0768] Business information data.

[0769] output

[0770] Learned business flow dependencies and efficient flow.

[0771] Step 3: Automatic generation of business flow

[0772] server

[0773] The server obtains the optimized workflow from the generative AI model that has completed training, and automatically generates a workflow diagram based on that data. A visually displayable diagram is generated using a library such as Graphviz.

[0774] Specific actions

[0775] The server receives the optimized business procedures from the AI ​​model and generates a "business flow diagram" using Graphviz.

[0776] input

[0777] Data for optimized business flows.

[0778] output

[0779] Business flow diagram.

[0780] Step 4: Presenting the generated workflow

[0781] Terminal

[0782] The terminal displays the generated business flow diagram to the user, who can then check the generated flow and make any necessary corrections.

[0783] Specific actions

[0784] The terminal displays the generated business flow diagram on the screen, and the user clicks the "Confirm button" to confirm the contents.

[0785] input

[0786] The generated business flow diagram.

[0787] output

[0788] A workflow diagram displayed to the user.

[0789] Step 5: Integrate and analyze multiple workflows

[0790] User

[0791] Users upload multiple existing business processes collected from different departments and projects to the server via their terminal in CSV or Excel format.

[0792] server

[0793] The server analyzes the uploaded workflows to detect duplication, inconsistencies, and unnecessary steps. It uses the Python "Pandas" library to perform data analysis.

[0794] Specific actions

[0795] Users upload multiple business flow data using their devices, and the server analyzes it.

[0796] input

[0797] Data from multiple existing business processes.

[0798] output

[0799] Duplicate and inconsistency detection results.

[0800] Step 6: Generate and present improvement proposals

[0801] server

[0802] Based on the analysis results, the server integrates each business flow and generates improvement proposals for efficiency. These improvement proposals are then optimized again through the generative AI model.

[0803] Specific actions

[0804] The server generates efficiency proposals such as "centralizing inventory confirmation procedures" and provides them to the user in an optimized form.

[0805] input

[0806] Analysis results and data for generating improvement proposals.

[0807] output

[0808] Optimized improvement suggestions.

[0809] Terminal

[0810] The device displays the generated improvement suggestions to the user, who can review them and provide feedback.

[0811] Specific actions

[0812] The device displays the improvement proposal on the screen, and the user presses the "improvement proposal approval button" to submit feedback.

[0813] input

[0814] Generated improvement suggestions.

[0815] output

[0816] The suggested improvements shown to the user.

[0817] Step 7: Evaluate and apply the improvements

[0818] User

[0819] The user evaluates the proposed improvement plan and decides whether to apply it. If they decide to apply it, they send a confirmation to the server via their device.

[0820] server

[0821] The server receives the user's confirmation, updates the workflow, and makes the new workflow executable.

[0822] Specific actions

[0823] The user evaluates the improvement proposal from their device, and after approval, presses the "Confirm and Send" button to send it to the server. The server updates the workflow and creates a new workflow.

[0824] input

[0825] User feedback and confirmation.

[0826] output

[0827] A new work flow that can be implemented.

[0828] Step 8: Implement and monitor the updated workflow

[0829] server

[0830] The server executes the new workflow and monitors its execution in real time. The monitoring data is saved in a log for later analysis.

[0831] Specific actions

[0832] The server implements the new workflow and monitors its progress.

[0833] input

[0834] Data for the new business flow.

[0835] output

[0836] Monitoring log data.

[0837] Terminal

[0838] The terminal displays the execution status data received from the server to the user in real time.

[0839] Specific actions

[0840] The terminal displays the progress of the business flow being executed in real time, and the user can check it.

[0841] input

[0842] Data on the running business flow.

[0843] output

[0844] The execution status displayed to the user.

[0845] Step 9: Anomaly detection and notification

[0846] server

[0847] The server generates alerts based on performance indicators to detect anomalies and bottlenecks during the workflow, and if anomalies or bottlenecks are detected, it generates new improvement proposals.

[0848] Specific actions

[0849] The server detects that the "inventory check" time is abnormally long and generates an alert.

[0850] input

[0851] Performance data for the running business flow.

[0852] output

[0853] Anomaly detection alerts and improvement suggestions.

[0854] Step 10: Generate new improvement suggestions

[0855] server

[0856] If the server detects an anomaly or bottleneck, it generates a new improvement proposal, such as "shift inventory checks to an automated system," and presents it to the user.

[0857] Specific actions

[0858] The server detects the anomaly and generates a new improvement proposal, such as "transfer inventory checks to an automated system," and presents it to the user.

[0859] input

[0860] Anomaly detection data.

[0861] output

[0862] New improvement proposals.

[0863] (Application example 1)

[0864] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0865] Optimizing and streamlining workflows is a key issue for logistics centers. It is necessary to minimize time and cost waste and improve overall operational performance in a series of procedures, including receiving, sorting, shelving, picking, packing, and shipping. However, traditional methods make it difficult to optimize workflows, and there is a problem of being unable to quickly respond to bottlenecks or abnormalities that occur during operations.

[0866] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0867] In this invention, the server includes means for inputting business information, means for training an AI model to learn the input business information, means for automatically generating a business flow based on the learned business information, means for reading multiple business flows, analyzing overlaps and inconsistencies, and generating improvement proposals, means for presenting the generated improvement proposals, and means for optimizing procedures for receiving, sorting, shelving, picking, packing, and shipping items in logistics operations, thereby enabling optimization and improvement of business flows in logistics centers.

[0868] "Business information" refers to information such as the name of each business procedure, detailed procedure content, dependencies, and person in charge.

[0869] An "AI model" refers to an artificial intelligence system that learns from business information and generates and improves optimal business flows.

[0870] "Business flow" refers to the flow of a series of procedures or processes set up to carry out a specific task.

[0871] "Overlap" refers to a situation in which the same procedure is repeated in different business flows.

[0872] "Inconsistency" refers to a situation in which procedures and processes do not match between multiple business flows.

[0873] "Improvement proposals" refer to proposed changes or corrections to improve the efficiency and optimization of business processes.

[0874] "Logistics operations" refers to a series of business processes such as receiving, sorting, putting away, picking, packing, and shipping goods.

[0875] "Optimization" refers to building and adjusting business processes in the most efficient and effective way for specified purposes and conditions.

[0876] A "bottleneck" refers to a part or step in a business flow that hinders efficiency or progress.

[0877] The present invention is a system for optimizing and improving the workflow in a logistics center. A specific embodiment of the system is described below.

[0878] System configuration

[0879] The system consists of the following components:

[0880] A means of entering business information

[0881] A means of training an AI model based on input business information

[0882] A means of automatically generating workflows based on learned business information

[0883] A means of reading multiple business processes, analyzing overlaps and inconsistencies, and generating improvement proposals

[0884] A means of presenting generated improvement proposals

[0885] A means of optimizing the receiving, sorting, putting away, picking, packing, and shipping procedures of logistics operations

[0886] Hardware and software used

[0887] Hardware: Servers (for data processing and storage), terminals (for users to input business information)

[0888] Software: Flask (web framework), AI model (for learning and generating business flows)

[0889] Program processing explanation

[0890] User: Enters operational information using a device (such as a smartphone or tablet), including procedures for receiving, sorting, putting away, picking, packing, and shipping items.

[0891] Server: Receives business information entered by users and sends it to the AI ​​model for learning. Based on the learning data, it automatically generates efficient business flows.

[0892] AI model: Uses business information to learn about dependencies and optimal workflows within business processes, and returns the generated workflow to the server.

[0893] Server: Analyzes multiple business processes and detects duplications and inconsistencies. Based on the results, it generates improvement proposals and presents them to the user.

[0894] Terminal: Improvement proposals, anomalies, and bottlenecks are displayed to the user in real time, allowing the user to review and evaluate updates to the workflow.

[0895] Server: Updates the business flow based on user feedback and implements the optimized flow. It also monitors the implementation status in real time, detects new anomalies and bottlenecks, and makes new proposals.

[0896] Specific examples

[0897] For example, if a logistics center has the following workflow:

[0898] Receiving goods

[0899] classification

[0900] Shelving

[0901] picking

[0902] packing

[0903] shipping

[0904] When the user inputs these steps into their device, the server trains the AI ​​model. The AI ​​model learns the dependencies and efficiency of each input step and generates an optimal workflow. The generated workflow is presented to the user by the server and is further improved based on subsequent feedback.

[0905] Example prompt sentence:

[0906] You are considering optimizing the workflow at your distribution center. Follow these steps to generate the most efficient workflow:

[0907] 1. Receiving your items

[0908] 2. Classification

[0909] 3. Shelving

[0910] 4. Picking

[0911] 5. Packaging

[0912] 6. Shipping

[0913] Please also suggest improvements to the above flow to improve its efficiency.

[0914] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0915] Step 1:

[0916] The user inputs business information into the terminal.

[0917] The business information to be entered includes the procedures for receiving, sorting, putting away, picking, packing, and shipping. For example, the flow "receiving goods -> sorting -> putting away -> picking -> packing -> shipping" is entered. This collects information such as the name of the business procedure, detailed procedure content, dependencies, and person in charge.

[0918] Step 2:

[0919] The server receives the business information sent from the terminal.

[0920] The server sends the input business information to the AI ​​model, and learning begins. The input data includes the flow of business procedures and their dependencies. The AI ​​model uses this data to learn the dependencies between each procedure and the efficient flow.

[0921] Step 3:

[0922] The server automatically generates a business flow based on the learned business information.

[0923] The server receives the optimal workflow returned by the AI ​​model and automatically generates this workflow, for example, arranging the steps of "receiving goods -> sorting -> shelving -> picking -> packing -> shipping" in the most efficient way.

[0924] Step 4:

[0925] A user uploads multiple existing business processes to a server via a terminal.

[0926] To integrate different flows, the user sends an existing business flow to the server, which then integrates multiple business flows, including overlapping and inconsistent flows, into the server.

[0927] Step 5:

[0928] The server analyzes multiple business flows and detects duplications and inconsistencies.

[0929] The server uses the analyzed data to detect duplication and inconsistencies in business flows. For example, if the same procedure exists in multiple flows, it detects this and generates improvement proposals.

[0930] Step 6:

[0931] Based on the detection results, the server generates improvement proposals for efficiency.

[0932] The server generates improvement proposals to optimize the workflow based on the detected duplications and inconsistencies. For example, it may generate an improvement proposal to "consolidate inventory checks."

[0933] Step 7:

[0934] The terminal presents the generated improvement proposal to the user.

[0935] The user can then view the proposed improvements from the server via their device. The improvements are displayed visually as a workflow diagram, allowing the user to evaluate them and make any necessary changes.

[0936] Step 8:

[0937] The server monitors the implementation status of the business flow in real time.

[0938] The server monitors the execution of the updated workflow and detects anomalies and bottlenecks, for example, if a particular step takes longer than expected.

[0939] Step 9:

[0940] The device displays notifications to the user about detected anomalies and bottlenecks.

[0941] Users can receive notifications from the server via their devices and be aware of any problems with the progress of their work, enabling them to take prompt action.

[0942] Step 10:

[0943] The server generates new improvement proposals based on the anomalies and bottlenecks and presents them to the user again.

[0944] Based on the detected anomalies and bottlenecks, the server generates improvement proposals for further efficiency improvements and notifies the user via the terminal. For example, a new improvement proposal might be presented, such as "shifting inventory checks to an automated system."

[0945] This allows users to constantly optimize the progress of their work.

[0946] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0947] This invention combines a system that uses AI to automatically generate workflows based on business information and continuously improves those workflows with an emotion engine that analyzes user emotions. This system starts with the input of business information, then learns using an AI model, analyzes the automatically generated workflow and proposes improvements, and then customizes it according to the user's emotions.

[0948] 1. Entering and learning business information

[0949] User

[0950] The user uses a terminal to input business information, including the name, details, dependencies, and person in charge information for each step.

[0951] Specific examples

[0952] For example, the user inputs procedures such as "enter customer information," "confirm order," "check inventory," "place order," and "confirm order" into the terminal.

[0953] Terminal

[0954] The terminal sends the entered business information to the server, where the information is transferred using a secure communication protocol.

[0955] server

[0956] The server receives the business information and inputs it into the AI ​​model, which then learns from it and understands the dependencies and flow of each step.

[0957] 2. Automatic creation and presentation of business flows

[0958] server

[0959] The server automatically generates the optimal workflow based on the learned information, taking into account the dependencies between each step to create the most efficient workflow.

[0960] Terminal

[0961] The terminal displays the generated business flow diagram to the user, allowing the user to grasp the overall picture of the business flow.

[0962] 3. Integration of multiple workflows and proposal of improvements

[0963] User

[0964] Users can upload multiple existing business processes to the server via their terminals.

[0965] server

[0966] The server analyzes these workflows and detects duplications and inconsistencies. For example, it detects cases where the "Stock Check" step overlaps between the "Customer Management Flow" and the "Inventory Management Flow."

[0967] Specific examples

[0968] The server detects duplication of inventory check steps and generates an improvement plan to "consolidate the inventory check steps."

[0969] 4. Evaluation and implementation of improvement plans

[0970] server

[0971] The server generates improvement proposals and sends them to the terminal, which then presents the proposals to the user.

[0972] User

[0973] The user evaluates the proposed improvements and decides whether to apply them. If so, the device sends a confirmation to the server.

[0974] server

[0975] The server receives the user's confirmation, updates the workflow, and makes the new workflow available for execution.

[0976] 5. Emotional Engine Response

[0977] server

[0978] The server uses an emotion engine to identify the user's feelings toward the proposed improvement proposals, analyzing feedback, facial expressions, and voice inputs in real time as the user reviews the improvement proposals.

[0979] Specific examples

[0980] If the user responds positively to the improvement proposal (e.g., satisfaction or joy), the server reads that information and recommends implementing the improvement proposal. Conversely, if the user responds negatively (e.g., dissatisfaction or confusion), the server proposes a different improvement proposal.

[0981] Terminal

[0982] The device provides feedback to the user based on the emotion engine and offers suggestions for improvements that will increase user satisfaction, thereby increasing user motivation and helping to improve work efficiency.

[0983] 6. Real-time monitoring and re-proposal of business flows

[0984] server

[0985] The server monitors the execution status of the updated business flow in real time, immediately detecting any abnormalities or bottlenecks that occur during business operations.

[0986] Specific examples

[0987] If the server detects a bottleneck in the inventory check step, it notifies the user of the impact and uses an emotion engine to suggest new improvement ideas.

[0988] In this way, this system integrates automation and a human-centered approach, starting with the input of business information, followed by learning using an AI model, automatic generation of business flows, suggesting improvement plans, and analyzing user emotions using an emotion engine. This allows users to build and improve efficient business flows even without detailed business knowledge.

[0989] The processing flow will be explained below.

[0990] Step 1:

[0991] The user inputs business information through a terminal. Business information includes the name of each procedure, detailed procedure content, dependencies, and person in charge. For example, specific business procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation" are input.

[0992] Step 2:

[0993] The terminal sends the entered business information to the server. The data is sent using a secure communication protocol.

[0994] Step 3:

[0995] The server inputs the business information received from the device into the AI ​​model, which learns this information and understands the dependencies between each business step and the most efficient execution order.

[0996] Step 4:

[0997] The server automatically generates a workflow based on the learned business information. The generated workflow is constructed taking into account the optimal dependencies between each step.

[0998] Step 5:

[0999] The server sends the generated business flow diagram to the terminal, which displays the flow diagram to the user, allowing the user to grasp the overall picture of the business flow.

[1000] Step 6:

[1001] Users can upload multiple existing business flows to the server via their terminal. For example, they can upload the "Customer Management Flow" of Department A and the "Inventory Management Flow" of Department B.

[1002] Step 7:

[1003] The server analyzes the received workflows and detects duplications and inconsistencies. For example, it detects that the "Inventory Check" step is duplicated in both departments A and B.

[1004] Step 8:

[1005] The server generates improvement proposals based on the analysis results to improve operational efficiency, such as "centralizing the inventory check step."

[1006] Step 9:

[1007] The server sends the generated improvement plan to the terminal, which then presents the improvement plan to the user and indicates the specific changes to be made.

[1008] Step 10:

[1009] The user evaluates the proposed improvements and decides whether to apply them. If so, the user sends a confirmation from the terminal to the server.

[1010] Step 11:

[1011] The server receives confirmation from the user and updates the workflow, which is then put into effect and made available for execution.

[1012] Step 12:

[1013] The server monitors the execution status of the updated business flow in real time, and if an abnormality or bottleneck occurs, the server immediately detects it.

[1014] Step 13:

[1015] The server generates new improvement plans based on the detected anomalies and bottlenecks and presents them to the user again, further improving business efficiency.

[1016] Step 14:

[1017] The server uses an emotion engine to analyze the user's emotions regarding the proposed improvement proposals. It analyzes the user's reactions (facial expressions, voice, input content, etc.) in real time to identify emotions.

[1018] Step 15:

[1019] The device will provide feedback based on the user's emotions based on the analysis results of the emotion engine. For example, if the reaction is positive, it will recommend an improvement plan, and if the reaction is negative, it will suggest a different improvement plan.

[1020] In this way, the present invention is a system that covers everything from business information to learning using AI models, automatically generated business flows and improvement suggestions, and even responses that take user emotions into consideration, providing a comprehensive solution for maximizing business efficiency.

[1021] Example 2

[1022] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1023] Conventional business management systems were inefficient because they required manual creation of business flows and human intervention to make improvement proposals. Furthermore, they were unable to consider the user's feelings and reactions, and improvement proposals sometimes did not contribute to user satisfaction.

[1024] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting business information, a means for training an artificial intelligence model on the input business information, a means for automatically generating business procedures based on the trained business information, a means for reading multiple business procedures, analyzing overlaps and inconsistencies, and generating improvement proposals, a means for presenting the generated improvement proposals, and a means for analyzing user emotions and generating responses to the presented improvement proposals. This makes it possible to automatically generate business flows and provide improvement proposals that take user satisfaction into consideration.

[1025] "Business information" is a general term for information necessary for generating and analyzing business flows, such as business procedures, details, dependencies, and person in charge information.

[1026] An "artificial intelligence model" is a type of algorithm that learns specific tasks based on large amounts of data and automatically generates business processes and suggests improvements.

[1027] A "business procedure" refers to a series of steps or processes taken to accomplish a particular task.

[1028] "Improvement proposals" are proposed changes or advice automatically generated by the system with the aim of streamlining and optimizing business procedures.

[1029] "User emotion" refers to the emotional state that results from analyzing the feedback and reactions that the user gives to the system.

[1030] An "abnormality" refers to an unexpected event or error that occurs during the course of business procedures.

[1031] A "bottleneck" is a part of a business process that causes a decrease in efficiency or delays in work.

[1032] This invention is a system that uses artificial intelligence to automatically generate work procedures based on work information and analyzes user emotions. This system starts with the input of work information, then learns using an artificial intelligence model, analyzes the automatically generated work procedures and proposes improvements, and then customizes them according to the user's emotions.

[1033] Entering and learning business information

[1034] User

[1035] The user uses a terminal to input business information. Specific input content includes the name of the procedure, details, dependencies, and person in charge information. For example, the user inputs procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation."

[1036] Terminal

[1037] The terminal sends the entered business information to the server, using a secure communication protocol (e.g., HTTPS) to transfer the information.

[1038] server

[1039] The server stores the received business information in a database. The business information retrieved from the database is then fed into the AI ​​model, which begins the learning process. The AI ​​model analyzes the provided data and understands the dependencies and flow of each step.

[1040] Automatic creation and presentation of business procedures

[1041] server

[1042] The server automatically generates optimal business procedures based on the learned information. The generated procedures are constructed efficiently, taking into account the dependencies between procedures.

[1043] Terminal

[1044] The terminal displays the business procedure diagram generated by the server to the user. This display uses a visualization tool such as a flowchart generator, allowing the user to grasp the overall picture of the business procedure.

[1045] Integration of multiple business procedures and proposal of improvements

[1046] User

[1047] Users upload multiple existing business procedures to the server via their terminal, which makes it possible to integrate and compare multiple business procedures.

[1048] server

[1049] The server analyzes the uploaded business procedures and detects duplications and inconsistencies. For example, it detects duplication of the "inventory check" step between "customer management procedures" and "inventory management procedures." This analysis process is performed using a data analysis algorithm.

[1050] Specific examples

[1051] Based on the detection result that "the inventory check steps are duplicated," the server generates an improvement plan to "consolidate the inventory check steps."

[1052] Evaluating and implementing improvement plans

[1053] server

[1054] The server sends the generated improvement proposal to the terminal. The improvement proposal includes specific steps and benefits, and is presented in a format that is easy for the user to understand.

[1055] User

[1056] The user evaluates the proposed improvement proposals and decides whether to apply them. If the user confirms the application, the user sends feedback from the device to the server.

[1057] server

[1058] The server receives user feedback and updates the business procedures. New business procedures are constructed by referencing existing data and are set to an executable state.

[1059] Emotion engine response

[1060] server

[1061] The server uses an emotion engine to analyze the user's reactions in real time, analyzing feedback, facial expressions, and voice data to identify the user's emotional state.

[1062] Specific examples

[1063] If the user expresses positive emotions (satisfaction or joy) toward the improvement proposal, the server retains that information and recommends implementing the improvement proposal. Conversely, if the user expresses negative emotions (dissatisfaction or confusion), a different improvement proposal is presented.

[1064] Terminal

[1065] The device displays the results of the emotion engine to the user, who receives new suggestions based on the feedback and can select the improvement suggestions that best suit their needs.

[1066] Real-time monitoring and revision of business procedures

[1067] server

[1068] The server monitors the implementation status of the updated business procedures in real time, and if an abnormality or bottleneck is discovered during the business process, it immediately detects it and notifies the user.

[1069] Specific examples

[1070] If the server detects a bottleneck during the inventory check step, it immediately notifies the user of the impact and uses an emotion engine to suggest new improvement ideas.

[1071] Example prompts to be input to the generative AI model

[1072] Example prompts

[1073] "The user enters business information such as customer information, order confirmation, inventory check, order placement, and order confirmation. If there are dependencies between these steps, generate the optimal business flow. Also, based on the user's reaction to the proposed improvements, use an emotion engine to make new suggestions."

[1074] As described above, this invention is a system that starts with inputting business information, learns using an AI model, automatically generates business procedures, and then uses an emotion engine to provide user-friendly improvement suggestions. This allows users to build and improve efficient business procedures even without detailed business knowledge.

[1075] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1076] Step 1:

[1077] User

[1078] The user uses a terminal to input business information, including the name of the procedure (e.g., "Enter customer information," "Order confirmation," "Inventory check," "Place order," "Order confirmation," etc.), details, dependencies, and person in charge.

[1079] Input: Business information entered by the user (procedure name, details, dependencies, person in charge information)

[1080] Output: Business information stored on the device

[1081] Step 2:

[1082] Terminal

[1083] The terminal sends the entered business information to the server, using a secure communication protocol (e.g., HTTPS) to transfer the information.

[1084] Input: Business information entered in Step 1

[1085] Output: Business information sent to the server

[1086] Step 3:

[1087] server

[1088] The server stores the received business information in a database. The business information retrieved from the database is then fed into an AI model to begin the learning process. The AI ​​model analyzes the provided data and understands the dependencies and flow of each step.

[1089] Input: Business information sent from the terminal

[1090] Output: Data trained by the AI ​​model

[1091] Step 4:

[1092] server

[1093] The server automatically generates optimal business procedures based on the learned information. The generated procedures are constructed efficiently, taking into account the dependencies between procedures.

[1094] Input: Trained data

[1095] Output: Generated business procedures

[1096] Step 5:

[1097] Terminal

[1098] The terminal displays the business procedure diagram generated by the server to the user. This display uses a visualization tool such as a flowchart generator, allowing the user to grasp the overall picture of the business procedure.

[1099] Input: Generated business procedure

[1100] Output: Business procedure diagram displayed on the terminal

[1101] Step 6:

[1102] User

[1103] Users upload multiple existing business procedures to the server via their terminal, which makes it possible to integrate and compare multiple business procedures.

[1104] Input: Existing business procedures uploaded by the user

[1105] Output: Multiple business procedures uploaded to the server

[1106] Step 7:

[1107] server

[1108] The server analyzes the uploaded business procedures and detects duplications and inconsistencies. For example, it detects duplication of the "inventory check" step between "customer management procedures" and "inventory management procedures." This analysis process is performed using a data analysis algorithm.

[1109] Input: Multiple Business Procedures

[1110] Output: Detected duplicates and inconsistencies

[1111] Step 8:

[1112] server

[1113] Based on the detection results, the server generates appropriate improvement suggestions, such as consolidating overlapping steps.

[1114] Input: Detected duplicates and inconsistencies

[1115] Output: Improvement suggestions

[1116] Step 9:

[1117] server

[1118] The server then sends the generated improvement proposals to the terminal and presents them to the user. The proposals include specific steps and their benefits.

[1119] Input: Improvement suggestion

[1120] Output: Improvement suggestions sent to the device

[1121] Step 10:

[1122] User

[1123] The user evaluates the proposed improvement suggestions and decides whether to apply them. The evaluation results and feedback are entered into the terminal and sent to the server.

[1124] Input: User ratings and feedback

[1125] Output: Rating and feedback sent to the server

[1126] Step 11:

[1127] server

[1128] The server updates business procedures based on user feedback. New procedures are built by referencing existing data and set to executable status.

[1129] Input: Ratings and Feedback

[1130] Output: Updated business procedures

[1131] Step 12:

[1132] server

[1133] The server uses an emotion engine to analyze the user's reactions in real time, analyzing feedback, facial expressions, and voice data to identify the user's emotional state.

[1134] Input: User feedback, facial expressions, and voice data

[1135] Output: Identified emotional state

[1136] Step 13:

[1137] server

[1138] The server adjusts the improvement suggestions based on the user's emotional state: if the emotion is positive, it recommends a suggestion, and if the emotion is negative, it presents a different suggestion.

[1139] Input: Identified emotional state

[1140] Output: Adjusted improvement suggestions

[1141] Step 14:

[1142] Terminal

[1143] The device displays the results of the emotion engine to the user and provides new suggestions, allowing the user to select the improvement suggestions that best suit their needs.

[1144] Input: Adjusted improvement suggestions

[1145] Output: The new proposal displayed to the user

[1146] Step 15:

[1147] server

[1148] The server monitors the implementation status of the updated business procedures in real time, and if an abnormality or bottleneck is discovered during the business process, it immediately detects it and notifies the user.

[1149] Input: Updated business procedures

[1150] Output: Real-time monitoring results and abnormality notifications

[1151] (Application example 2)

[1152] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1153] Conventional workflow automatic generation systems have limitations in terms of improving and optimizing workflow efficiency. Furthermore, continuous improvements that take user emotions and feedback into account are rare, making continuous improvement of workflows difficult. Furthermore, when robots perform work in factories, real-time monitoring and improvement proposals are necessary to improve the effectiveness of the workflow, but efficient methods for doing this have not yet been established. Furthermore, there is a need for a system that can determine whether proposed improvements are appropriate based on user emotions.

[1154] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1155] In this invention, the server includes means for inputting business information, means for training an AI model to learn the input business information, means for automatically generating a business flow based on the learned business information, means for reading multiple business flows, analyzing overlaps and inconsistencies, and generating improvement proposals, means for presenting the generated improvement proposals, means for analyzing user emotions, and means for evaluating the proposed improvement proposals based on the emotion analysis and re-proposing them as necessary. This makes it possible to optimize business flows while taking user emotions into consideration, and to monitor and propose improvements in real time.

[1156] "Business information" is information that includes procedures, processes, people, dependencies, etc. related to the operation of a company or organization.

[1157] An "AI model" is an algorithm and its settings that uses artificial intelligence technology to learn from data and perform pattern recognition and prediction.

[1158] A "business flow" is a set of procedures or processes set up to accomplish a specific task.

[1159] "Automatically generating" means that the system automatically generates results based on pre-set algorithms or rules.

[1160] "Duplicate" means that there are multiple identical or similar procedures or data.

[1161] An "inconsistency" is when multiple procedures or data are inconsistent or inconsistent.

[1162] "Improvements" are suggestions or changes to make current processes or procedures more efficient or effective.

[1163] "User emotions" refers to the emotional reactions and feedback given by system users.

[1164] "Analyzing" means collecting data or information and analyzing it to find meaning and patterns.

[1165] "Real time" refers to the ability to process ongoing events and actions and provide results immediately.

[1166] A "bottleneck" is a factor or obstacle that slows down the overall progress of a task or process.

[1167] A "re-proposal" is a proposal that is presented again to improve something that was previously proposed, based on new information or feedback.

[1168] "Customization" means adapting or modifying a system or process to meet specific requirements or needs.

[1169] 1. An overview of the system that realizes this application example is given below. The system automatically generates, monitors, and improves the work flow of robots used in factories in real time, and is composed of the following main components.

[1170] 2. The server has a means of inputting business information. Procedures, processes, personnel, dependencies, and other information related to the operation of a company or organization are input via a terminal. Based on this, the server trains an AI model based on the input business information. Specific AI technologies used include TensorFlow and Keras.

[1171] 3. The AI ​​model learns from the submitted business information and has the means to automatically generate a business flow. Based on the learned information, it constructs the most efficient business flow. This generated business flow is displayed on the terminal in real time by the server.

[1172] 4. The server has a means to read multiple business flows, analyze overlaps and inconsistencies, and generate improvement proposals. This allows overlaps and inconsistencies between business flows to be discovered and improvement proposals to resolve them to be proposed.

[1173] 5. The server has a means to present the generated improvement proposals and a means to analyze the user's emotions. The user inputs feedback through a device, smart glasses, or a head-mounted display, and the emotions are analyzed. OpenCV and a specific emotion analysis model are used for the analysis.

[1174] 6. The server has the means to evaluate the proposed improvement plan based on the user's sentiment analysis and re-propose it if necessary. If the user's sentiment is negative, the AI ​​model recalculates the workflow and proposes a new improvement plan.

[1175] 7. Furthermore, the server has the means to monitor the execution status of the business flow in real time and detect anomalies and bottlenecks. If an anomaly is detected, the server will again propose improvements, taking into account the user's emotional data.

[1176] 8. The user has the means to evaluate and confirm the revised workflow. After confirmation, the server updates the workflow and puts the new workflow into operation. The server can also customize the workflow based on the user's emotional data.

[1177] Examples:

[1178] In a factory, robots assemble parts one by one. To optimize this workflow, a server automatically generates a workflow and monitors it in real time. For example, a new workflow proposal might be generated to "rearrange the order of parts." However, if a worker shows a confused expression, an emotion analysis engine detects this and the server reconsiders the workflow. For example, it might suggest a different improvement, such as "changing the placement of assembly tools."

[1179] Example prompt sentence:

[1180] "A new workflow has been generated that rearranges the order of parts. The worker's emotional data revealed a confused response. Based on this response, please suggest another workflow improvement."

[1181] In this way, the invention makes it possible to optimize workflows while taking into account the user's emotions, and realizes real-time monitoring and improvement suggestions.

[1182] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1183] Step 1:

[1184] The user inputs business information into the device. The device then sends the input business information, such as procedures, processes, personnel, and dependencies, to the server. The server receives this information and inputs it into the AI ​​model. The server then uses TensorFlow and Keras to train the business information. The input is the business information, and the output is the trained business model.

[1185] Step 2:

[1186] The server automatically generates a workflow based on the learned business information. The AI ​​model constructs an optimal workflow based on the received business information. This workflow is efficiently assembled, taking into account the dependencies between steps. The generated workflow is sent from the server to the terminal, which displays it to the user. The input is the trained business model, and the output is the generated workflow.

[1187] Step 3:

[1188] The server loads multiple business processes and analyzes them for overlaps and inconsistencies. The server analyzes each step in the business process and detects any overlaps or inconsistencies. The server uses an AI model to generate improvement proposals. For example, it generates proposals to unify overlapping steps. The input is multiple business processes, and the output is improvement proposals.

[1189] Step 4:

[1190] The server sends the generated improvement proposals to the terminal and presents them to the user. The user evaluates the improvement proposals and provides feedback through the terminal. This feedback also includes the user's emotional data. The input is the improvement proposals, and the output is the user's feedback and emotional data.

[1191] Step 5:

[1192] The server analyzes the user's emotions. It uses OpenCV or a specific emotion analysis model to analyze the user's facial and voice data collected from the device, smart glasses, or head-mounted display. For example, if the user shows a dissatisfied expression, it is interpreted as a negative emotion. The input is the user's emotional data, and the output is the analysis result.

[1193] Step 6:

[1194] The server reevaluates improvement proposals based on sentiment analysis and re-proposes them if necessary. If the user's sentiment is negative, a new improvement proposal for the business process is regenerated using an AI model. This is an important means of increasing user satisfaction. The input is the sentiment analysis results, and the output is the re-proposed improvement proposal.

[1195] Step 7:

[1196] The server monitors the execution status of the business flow in real time and detects abnormalities and bottlenecks. For example, if there is a delay in the assembly of parts, the server will detect that step as a bottleneck. The input is real-time business data, and the output is detected abnormality information.

[1197] Step 8:

[1198] The server makes improvement suggestions based on the detected anomalies and bottlenecks. The detected anomalies and bottlenecks are analyzed using an AI model to generate optimal improvement suggestions. For example, improvement suggestions such as changing the placement of assembly tools are proposed. The input is the detected anomaly information, and the output is the improvement suggestions.

[1199] Step 9:

[1200] The user evaluates and confirms the revised workflow through the terminal. The confirmed workflow is updated by the server and put into execution. The workflow is customized taking into account the user's emotional data. The input is the user's confirmation and emotional data, and the output is the updated workflow.

[1201] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1202] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1203] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1204] [Third embodiment]

[1205] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1206] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1207] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1208] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1209] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1210] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1211] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1212] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1213] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1214] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1215] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1216] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1217] The present invention is a system that inputs business information, automatically generates business flows by learning them into an AI model, and then analyzes multiple business flows to propose improvement plans. This system is implemented as follows.

[1218] 1. Entering and learning business information

[1219] User

[1220] The user uses a terminal to input task information, including the name of each step, detailed procedure content, dependencies, and person in charge.

[1221] Specific examples

[1222] For example, a user inputs the following business procedure through a terminal: "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order."

[1223] server

[1224] The server receives the business information sent from the device and inputs it into the AI ​​model, which uses this data to learn about dependencies and efficient workflows.

[1225] 2. Automatic creation of business flows

[1226] server

[1227] The server automatically generates a workflow based on the business information learned by AI. The generated workflow takes into account the dependencies between each step, creating the most efficient workflow.

[1228] Specific examples

[1229] The server efficiently arranges the steps of "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order" and creates a business flow diagram.

[1230] Terminal

[1231] The terminal presents the generated workflow diagram to the user, allowing the user to grasp the overall picture of the workflow.

[1232] 3. Integration of multiple workflows and proposal of improvements

[1233] User

[1234] Users can upload multiple existing business processes to the server via their terminals.

[1235] server

[1236] The server analyzes these workflows to detect duplication and inconsistencies, and based on the results, generates improvement proposals for improving efficiency.

[1237] Specific examples

[1238] For example, if the "inventory check" procedure overlaps between Department A's "customer management flow" and Department B's "inventory management flow," the server will detect this overlap and generate an improvement proposal to "consolidate the inventory check step."

[1239] Terminal

[1240] The terminal presents the improvement proposals generated by the server to the user, who can then check and evaluate them.

[1241] 4. Evaluation and implementation of improvement plans

[1242] User

[1243] The user evaluates the proposed improvement plan and decides whether to apply it. If the improvement plan is applied, a confirmation is sent to the server via the terminal.

[1244] server

[1245] The server receives the user's confirmation and updates the workflow, which is then put into action and made live for the user to use.

[1246] 5. Collaboration and Monitoring

[1247] server

[1248] The server monitors the execution status of the updated business flow in real time, and immediately detects any abnormalities or bottlenecks that occur during the business process.

[1249] Terminal

[1250] The terminal displays a notification of any detected abnormalities or bottlenecks to the user, allowing the user to confirm that there is a problem with the progress of the business flow.

[1251] server

[1252] The server generates new improvement proposals based on the anomalies and bottlenecks and presents them to the user again.

[1253] Specific examples

[1254] For example, if the server detects that "inventory check" in the new workflow is taking longer than expected, a notification will be displayed on the terminal. The server will then suggest a new improvement plan: "Move inventory check to an automated system."

[1255] In this way, by executing a series of processes based on the present invention, from inputting business information to automatically generating a flow, proposing improvements, implementing them, and monitoring them, it is possible to improve business efficiency and strengthen cooperation.

[1256] The processing flow will be explained below.

[1257] Step 1:

[1258] The user inputs business information through a terminal. Business information includes the name of each procedure, detailed procedure content, dependencies, and person in charge. For example, the user might input procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation."

[1259] Step 2:

[1260] The terminal sends the entered business information to the server. The data is transmitted using a secure communication protocol.

[1261] Step 3:

[1262] The server inputs the business information received from the device into the AI ​​model, which uses this data to learn business dependencies and efficient processing sequences.

[1263] Step 4:

[1264] The server automatically generates a workflow based on the information learned by the AI ​​model. The generated workflow reflects the optimal dependencies between each step.

[1265] Step 5:

[1266] The server sends the generated business flow diagram to the terminal, where the user can view the diagram on the terminal screen.

[1267] Step 6:

[1268] Users can upload multiple existing business processes to the server via their terminals.

[1269] Step 7:

[1270] The server analyzes multiple workflows and detects duplications and inconsistencies. For example, it detects duplication of the "Stock Check" step between the "Customer Management Flow" and the "Inventory Management Flow."

[1271] Step 8:

[1272] Based on the analysis results, the server generates improvement proposals to improve business efficiency, such as "centralizing the inventory check step."

[1273] Step 9:

[1274] The server sends the generated improvement proposal to the terminal, which then presents it to the user, who then checks the contents of the improvement proposal.

[1275] Step 10:

[1276] The user evaluates the improvement plan and decides whether to apply it. If so, the terminal sends a confirmation to the server.

[1277] Step 11:

[1278] The server receives the user's confirmation and updates the workflow, making the new workflow available for execution.

[1279] Step 12:

[1280] The server monitors the execution status of the updated business flow in real time, and immediately detects any abnormalities or bottlenecks that occur.

[1281] Step 13:

[1282] The server generates new improvement proposals based on the detected anomalies and bottlenecks, such as "shift inventory checks to an automated system."

[1283] Step 14:

[1284] The server sends new improvement proposals to the terminal and presents them to the user again, who then checks them and considers how to respond.

[1285] Example 1

[1286] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1287] In today's business environment, streamlining and improving workflows is extremely important. However, conventional methods require a significant amount of time and effort to manually input and analyze business information, resulting in low accuracy in automatically generating workflows and improving proposals. Furthermore, it is difficult to integrate multiple workflows, detect overlaps and inconsistencies, and generate efficient improvement proposals. The present invention aims to solve these problems and provide a system that streamlines and optimizes workflows in real time.

[1288] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1289] In this invention, the server includes means for inputting business information, means for training a generative AI model on the input business information, means for automatically generating a business flow based on the trained business information, means for presenting the generated business flow, means for integrating and analyzing multiple business flows, detecting duplications and inconsistencies, and generating improvement proposals, and means for presenting the generated improvement proposals. This enables automatic input of business information, automatic generation of efficient workflows, integrated analysis of multiple business flows, and generation and presentation of optimized improvement proposals.

[1290] "Business information" is data such as business-related procedures, detailed procedure content, dependencies, and personnel in charge.

[1291] A "generative AI model" is an algorithm or machine learning model that learns business information and automatically generates optimal business flows and proposes improvements.

[1292] A "business flow" refers to the flow of a series of procedures or processes for carrying out a specific business operation.

[1293] "Automatic generation" means that the system automatically creates a business flow based on the input information without human intervention.

[1294] "Integration" means combining multiple business flows into one entity.

[1295] "Duplicate" refers to the occurrence of the same procedure multiple times in different business processes, which can lead to inefficiency.

[1296] "Inconsistency" refers to a state in which the order or content of a business flow is inconsistent.

[1297] "Improvement proposals" are specific proposals aimed at streamlining and optimizing business processes.

[1298] "Presentation" refers to the display of system-generated information or data in a form that is visible to the user.

[1299] "Monitoring" means continuously observing the execution status of a business flow and checking for any abnormalities or problems.

[1300] An "abnormality" is an unexpected problem or obstacle that occurs in the normal course of business.

[1301] A "bottleneck" is a procedure in a business flow that is slower to execute than other procedures and that causes a decrease in overall efficiency.

[1302] The present invention is a system that automatically generates workflows by inputting business information and training a generative AI model, and then analyzes multiple workflows to propose improvements. This system is implemented as follows.

[1303] Entering and learning business information

[1304] User

[1305] The user uses the terminal to input business information. This information includes the name of each step, detailed procedure content, dependencies, and the person in charge. For example, the user inputs the business procedure "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order" through the terminal. After completing the input, the user clicks the "Send button" to send the business information to the server.

[1306] server

[1307] The server receives business information sent from the device and inputs the data into a generative AI model using Python, TensorFlow, etc. This model retrains based on the received data, learning dependencies between business processes and efficient workflows.

[1308] Automatic creation of business flows

[1309] server

[1310] The server obtains the optimized business flow from the generative AI model that has completed training, and automatically generates a business flow diagram based on that data. Specifically, it uses libraries such as Graphviz to generate a diagram that can be displayed visually.

[1311] Presentation of business flow

[1312] Terminal

[1313] The terminal displays the generated business flow diagram to the user. The user can check the generated flow and make any necessary corrections. For example, the user can check the generated business flow diagram on the terminal and click the "Confirm" button to confirm the contents.

[1314] Integration and analysis of multiple workflows

[1315] User

[1316] Users upload multiple existing business processes collected from different departments and projects to the server via their terminal in CSV or Excel format.

[1317] server

[1318] The server analyzes the multiple workflows uploaded and detects duplication, inconsistencies, and unnecessary steps. For example, it uses the Python "Pandas" library to analyze the data and identify duplicate steps and inconsistencies.

[1319] Generate and present improvement proposals

[1320] server

[1321] Based on the analysis results, the server integrates each business flow and generates improvement proposals for efficiency. The generated improvement proposals are then optimized again through the generative AI model. For example, it generates an efficiency proposal such as "centralizing inventory confirmation procedures."

[1322] Terminal

[1323] The device displays the generated improvement proposal to the user, who can then review it and provide feedback. Specifically, the device displays the improvement proposal on the screen, and the user submits feedback by pressing the "improvement proposal approval button."

[1324] Evaluating and applying improvements

[1325] User

[1326] The user evaluates the proposed improvement plan, and if they decide to apply it, they send a confirmation to the server via their device.

[1327] server

[1328] The server receives the user's confirmation, updates the workflow, and makes the new workflow executable. For example, the user evaluates the improvement proposal from their terminal, and after approval, presses the "Confirm and Send" button to send it to the server. The server updates the workflow and generates a new workflow.

[1329] Implementing and monitoring updated workflows

[1330] server

[1331] The server executes the new workflow and monitors its execution in real time. The monitoring data is saved in a log for later analysis.

[1332] Terminal

[1333] The terminal displays the execution status data received from the server to the user in real time. For example, the terminal displays the progress status of the business flow being executed in real time, and the user can check it.

[1334] Anomaly detection and generation of new improvement suggestions

[1335] server

[1336] The server detects anomalies and bottlenecks while the business flow is in progress, and generates an alert if a certain performance indicator cannot be exceeded. When an anomaly or bottleneck is detected, a new improvement proposal is generated. For example, the server detects that the time taken for "inventory check" is abnormally long and generates an alert. Based on this, a new improvement proposal to "transfer inventory checks to an automated system" is generated and presented to the user.

[1337] Prompt Sentence Examples

[1338] Please tell me how to enter customer information.

[1339] "Please suggest ways to automate inventory checks."

[1340] "Please tell me the efficient order processing flow."

[1341] In this way, the present invention executes a series of processes from inputting business information to automatically generating a flow, integrating and analyzing multiple business flows, generating and presenting improvement proposals for efficiency, implementing and monitoring the revised business flow, detecting anomalies, and generating new improvement proposals, thereby achieving improved and optimized business efficiency.

[1342] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1343] Step 1: Enter your business information

[1344] User

[1345] The user uses the terminal to input business information such as the name of each procedure, detailed procedure content, dependencies, and person in charge. After inputting the information, the user clicks the "Send" button to send the business information to the server.

[1346] Specific actions

[1347] The user enters the business procedure into the terminal, such as "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order", and clicks the "Send button".

[1348] input

[1349] Business procedures, detailed procedure content, dependencies, and person information.

[1350] output

[1351] Sending business information to the server.

[1352] Step 2: Send data to the AI ​​model and train it

[1353] server

[1354] The server receives business information sent from the device and inputs the data into the generative AI model using Python, TensorFlow, etc. The generative AI model learns based on this data.

[1355] Specific actions

[1356] The server inputs the received business procedure data into the AI ​​model and starts the "business flow optimization process."

[1357] input

[1358] Business information data.

[1359] output

[1360] Learned business flow dependencies and efficient flow.

[1361] Step 3: Automatic generation of business flow

[1362] server

[1363] The server obtains the optimized workflow from the generative AI model that has completed training, and automatically generates a workflow diagram based on that data. A visually displayable diagram is generated using a library such as Graphviz.

[1364] Specific actions

[1365] The server receives the optimized business procedures from the AI ​​model and generates a "business flow diagram" using Graphviz.

[1366] input

[1367] Data for optimized business flows.

[1368] output

[1369] Business flow diagram.

[1370] Step 4: Presenting the generated workflow

[1371] Terminal

[1372] The terminal displays the generated business flow diagram to the user, who can then check the generated flow and make any necessary corrections.

[1373] Specific actions

[1374] The terminal displays the generated business flow diagram on the screen, and the user clicks the "Confirm button" to confirm the contents.

[1375] input

[1376] The generated business flow diagram.

[1377] output

[1378] A workflow diagram displayed to the user.

[1379] Step 5: Integrate and analyze multiple workflows

[1380] User

[1381] Users upload multiple existing business processes collected from different departments and projects to the server via their terminal in CSV or Excel format.

[1382] server

[1383] The server analyzes the uploaded workflows to detect duplication, inconsistencies, and unnecessary steps. It uses the Python "Pandas" library to perform data analysis.

[1384] Specific actions

[1385] Users upload multiple business flow data using their devices, and the server analyzes it.

[1386] input

[1387] Data from multiple existing business processes.

[1388] output

[1389] Duplicate and inconsistency detection results.

[1390] Step 6: Generate and present improvement proposals

[1391] server

[1392] Based on the analysis results, the server integrates each business flow and generates improvement proposals for efficiency. These improvement proposals are then optimized again through the generative AI model.

[1393] Specific actions

[1394] The server generates efficiency proposals such as "centralizing inventory confirmation procedures" and provides them to the user in an optimized form.

[1395] input

[1396] Analysis results and data for generating improvement proposals.

[1397] output

[1398] Optimized improvement suggestions.

[1399] Terminal

[1400] The device displays the generated improvement suggestions to the user, who can review them and provide feedback.

[1401] Specific actions

[1402] The device displays the improvement proposal on the screen, and the user presses the "improvement proposal approval button" to submit feedback.

[1403] input

[1404] Generated improvement suggestions.

[1405] output

[1406] The suggested improvements shown to the user.

[1407] Step 7: Evaluate and apply the improvements

[1408] User

[1409] The user evaluates the proposed improvement plan and decides whether to apply it. If they decide to apply it, they send a confirmation to the server via their device.

[1410] server

[1411] The server receives the user's confirmation, updates the workflow, and makes the new workflow executable.

[1412] Specific actions

[1413] The user evaluates the improvement proposal from their device, and after approval, presses the "Confirm and Send" button to send it to the server. The server updates the workflow and creates a new workflow.

[1414] input

[1415] User feedback and confirmation.

[1416] output

[1417] A new work flow that can be implemented.

[1418] Step 8: Implement and monitor the updated workflow

[1419] server

[1420] The server executes the new workflow and monitors its execution in real time. The monitoring data is saved in a log for later analysis.

[1421] Specific actions

[1422] The server implements the new workflow and monitors its progress.

[1423] input

[1424] Data for the new business flow.

[1425] output

[1426] Monitoring log data.

[1427] Terminal

[1428] The terminal displays the execution status data received from the server to the user in real time.

[1429] Specific actions

[1430] The terminal displays the progress of the business flow being executed in real time, and the user can check it.

[1431] input

[1432] Data on the running business flow.

[1433] output

[1434] The execution status displayed to the user.

[1435] Step 9: Anomaly detection and notification

[1436] server

[1437] The server generates alerts based on performance indicators to detect anomalies and bottlenecks during the workflow, and if anomalies or bottlenecks are detected, it generates new improvement proposals.

[1438] Specific actions

[1439] The server detects that the "inventory check" time is abnormally long and generates an alert.

[1440] input

[1441] Performance data for the running business flow.

[1442] output

[1443] Anomaly detection alerts and improvement suggestions.

[1444] Step 10: Generate new improvement suggestions

[1445] server

[1446] If the server detects an anomaly or bottleneck, it generates a new improvement proposal, such as "shift inventory checks to an automated system," and presents it to the user.

[1447] Specific actions

[1448] The server detects the anomaly and generates a new improvement proposal, such as "transfer inventory checks to an automated system," and presents it to the user.

[1449] input

[1450] Anomaly detection data.

[1451] output

[1452] New improvement proposals.

[1453] (Application example 1)

[1454] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1455] Optimizing and streamlining workflows is a key issue for logistics centers. It is necessary to minimize time and cost waste and improve overall operational performance in a series of procedures, including receiving, sorting, shelving, picking, packing, and shipping. However, traditional methods make it difficult to optimize workflows, and there is a problem of being unable to quickly respond to bottlenecks or abnormalities that occur during operations.

[1456] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1457] In this invention, the server includes means for inputting business information, means for training an AI model to learn the input business information, means for automatically generating a business flow based on the learned business information, means for reading multiple business flows, analyzing overlaps and inconsistencies, and generating improvement proposals, means for presenting the generated improvement proposals, and means for optimizing procedures for receiving, sorting, shelving, picking, packing, and shipping items in logistics operations, thereby enabling optimization and improvement of business flows in logistics centers.

[1458] "Business information" refers to information such as the name of each business procedure, detailed procedure content, dependencies, and person in charge.

[1459] An "AI model" refers to an artificial intelligence system that learns from business information and generates and improves optimal business flows.

[1460] "Business flow" refers to the flow of a series of procedures or processes set up to carry out a specific task.

[1461] "Overlap" refers to a situation in which the same procedure is repeated in different business flows.

[1462] "Inconsistency" refers to a situation in which procedures and processes do not match between multiple business flows.

[1463] "Improvement proposals" refer to proposed changes or corrections to improve the efficiency and optimization of business processes.

[1464] "Logistics operations" refers to a series of business processes such as receiving, sorting, putting away, picking, packing, and shipping goods.

[1465] "Optimization" refers to building and adjusting business processes in the most efficient and effective way for specified purposes and conditions.

[1466] A "bottleneck" refers to a part or step in a business flow that hinders efficiency or progress.

[1467] The present invention is a system for optimizing and improving the workflow in a logistics center. A specific embodiment of the system is described below.

[1468] System configuration

[1469] The system consists of the following components:

[1470] A means of entering business information

[1471] A means of training an AI model based on input business information

[1472] A means of automatically generating workflows based on learned business information

[1473] A means of reading multiple business processes, analyzing overlaps and inconsistencies, and generating improvement proposals

[1474] A means of presenting generated improvement proposals

[1475] A means of optimizing the receiving, sorting, putting away, picking, packing, and shipping procedures of logistics operations

[1476] Hardware and software used

[1477] Hardware: Servers (for data processing and storage), terminals (for users to input business information)

[1478] Software: Flask (web framework), AI model (for learning and generating business flows)

[1479] Program processing explanation

[1480] User: Enters operational information using a device (such as a smartphone or tablet), including procedures for receiving, sorting, putting away, picking, packing, and shipping items.

[1481] Server: Receives business information entered by users and sends it to the AI ​​model for learning. Based on the learning data, it automatically generates efficient business flows.

[1482] AI model: Uses business information to learn about dependencies and optimal workflows within business processes, and returns the generated workflow to the server.

[1483] Server: Analyzes multiple business processes and detects duplications and inconsistencies. Based on the results, it generates improvement proposals and presents them to the user.

[1484] Terminal: Improvement proposals, anomalies, and bottlenecks are displayed to the user in real time, allowing the user to review and evaluate updates to the workflow.

[1485] Server: Updates the business flow based on user feedback and implements the optimized flow. It also monitors the implementation status in real time, detects new anomalies and bottlenecks, and makes new proposals.

[1486] Specific examples

[1487] For example, if a logistics center has the following workflow:

[1488] Receiving goods

[1489] classification

[1490] Shelving

[1491] picking

[1492] packing

[1493] shipping

[1494] When the user inputs these steps into their device, the server trains the AI ​​model. The AI ​​model learns the dependencies and efficiency of each input step and generates an optimal workflow. The generated workflow is presented to the user by the server and is further improved based on subsequent feedback.

[1495] Example prompt sentence:

[1496] You are considering optimizing the workflow at your distribution center. Follow these steps to generate the most efficient workflow:

[1497] 1. Receiving your items

[1498] 2. Classification

[1499] 3. Shelving

[1500] 4. Picking

[1501] 5. Packaging

[1502] 6. Shipping

[1503] Please also suggest improvements to the above flow to improve its efficiency.

[1504] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1505] Step 1:

[1506] The user inputs business information into the terminal.

[1507] The business information to be entered includes the procedures for receiving, sorting, putting away, picking, packing, and shipping. For example, the flow "receiving goods -> sorting -> putting away -> picking -> packing -> shipping" is entered. This collects information such as the name of the business procedure, detailed procedure content, dependencies, and person in charge.

[1508] Step 2:

[1509] The server receives the business information sent from the terminal.

[1510] The server sends the input business information to the AI ​​model, and learning begins. The input data includes the flow of business procedures and their dependencies. The AI ​​model uses this data to learn the dependencies between each procedure and the efficient flow.

[1511] Step 3:

[1512] The server automatically generates a business flow based on the learned business information.

[1513] The server receives the optimal workflow returned by the AI ​​model and automatically generates this workflow, for example, arranging the steps of "receiving goods -> sorting -> shelving -> picking -> packing -> shipping" in the most efficient way.

[1514] Step 4:

[1515] A user uploads multiple existing business processes to a server via a terminal.

[1516] To integrate different flows, the user sends an existing business flow to the server, which then integrates multiple business flows, including overlapping and inconsistent flows, into the server.

[1517] Step 5:

[1518] The server analyzes multiple business flows and detects duplications and inconsistencies.

[1519] The server uses the analyzed data to detect duplication and inconsistencies in business flows. For example, if the same procedure exists in multiple flows, it detects this and generates improvement proposals.

[1520] Step 6:

[1521] Based on the detection results, the server generates improvement proposals for efficiency.

[1522] The server generates improvement proposals to optimize the workflow based on the detected duplications and inconsistencies. For example, it may generate an improvement proposal to "consolidate inventory checks."

[1523] Step 7:

[1524] The terminal presents the generated improvement proposal to the user.

[1525] The user can then view the proposed improvements from the server via their device. The improvements are displayed visually as a workflow diagram, allowing the user to evaluate them and make any necessary changes.

[1526] Step 8:

[1527] The server monitors the implementation status of the business flow in real time.

[1528] The server monitors the execution of the updated workflow and detects anomalies and bottlenecks, for example, if a particular step takes longer than expected.

[1529] Step 9:

[1530] The device displays notifications to the user about detected anomalies and bottlenecks.

[1531] Users can receive notifications from the server via their devices and be aware of any problems with the progress of their work, enabling them to take prompt action.

[1532] Step 10:

[1533] The server generates new improvement proposals based on the anomalies and bottlenecks and presents them to the user again.

[1534] Based on the detected anomalies and bottlenecks, the server generates improvement proposals for further efficiency improvements and notifies the user via the terminal. For example, a new improvement proposal might be presented, such as "shifting inventory checks to an automated system."

[1535] This allows users to constantly optimize the progress of their work.

[1536] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1537] This invention combines a system that uses AI to automatically generate workflows based on business information and continuously improves those workflows with an emotion engine that analyzes user emotions. This system starts with the input of business information, then learns using an AI model, analyzes the automatically generated workflow and proposes improvements, and then customizes it according to the user's emotions.

[1538] 1. Entering and learning business information

[1539] User

[1540] The user uses a terminal to input business information, including the name, details, dependencies, and person in charge information for each step.

[1541] Specific examples

[1542] For example, the user inputs procedures such as "enter customer information," "confirm order," "check inventory," "place order," and "confirm order" into the terminal.

[1543] Terminal

[1544] The terminal sends the entered business information to the server, where the information is transferred using a secure communication protocol.

[1545] server

[1546] The server receives the business information and inputs it into the AI ​​model, which then learns from it and understands the dependencies and flow of each step.

[1547] 2. Automatic creation and presentation of business flows

[1548] server

[1549] The server automatically generates the optimal workflow based on the learned information, taking into account the dependencies between each step to create the most efficient workflow.

[1550] Terminal

[1551] The terminal displays the generated business flow diagram to the user, allowing the user to grasp the overall picture of the business flow.

[1552] 3. Integration of multiple workflows and proposal of improvements

[1553] User

[1554] Users can upload multiple existing business processes to the server via their terminals.

[1555] server

[1556] The server analyzes these workflows and detects duplications and inconsistencies. For example, it detects cases where the "Stock Check" step overlaps between the "Customer Management Flow" and the "Inventory Management Flow."

[1557] Specific examples

[1558] The server detects duplication of inventory check steps and generates an improvement plan to "consolidate the inventory check steps."

[1559] 4. Evaluation and implementation of improvement plans

[1560] server

[1561] The server generates improvement proposals and sends them to the terminal, which then presents the proposals to the user.

[1562] User

[1563] The user evaluates the proposed improvements and decides whether to apply them. If so, the device sends a confirmation to the server.

[1564] server

[1565] The server receives the user's confirmation, updates the workflow, and makes the new workflow available for execution.

[1566] 5. Emotional Engine Response

[1567] server

[1568] The server uses an emotion engine to identify the user's feelings toward the proposed improvement proposals, analyzing feedback, facial expressions, and voice inputs in real time as the user reviews the improvement proposals.

[1569] Specific examples

[1570] If the user responds positively to the improvement proposal (e.g., satisfaction or joy), the server reads that information and recommends implementing the improvement proposal. Conversely, if the user responds negatively (e.g., dissatisfaction or confusion), the server proposes a different improvement proposal.

[1571] Terminal

[1572] The device provides feedback to the user based on the emotion engine and offers suggestions for improvements that will increase user satisfaction, thereby increasing user motivation and helping to improve work efficiency.

[1573] 6. Real-time monitoring and re-proposal of business flows

[1574] server

[1575] The server monitors the execution status of the updated business flow in real time, immediately detecting any abnormalities or bottlenecks that occur during business operations.

[1576] Specific examples

[1577] If the server detects a bottleneck in the inventory check step, it notifies the user of the impact and uses an emotion engine to suggest new improvement ideas.

[1578] In this way, this system integrates automation and a human-centered approach, starting with the input of business information, followed by learning using an AI model, automatic generation of business flows, suggesting improvement plans, and analyzing user emotions using an emotion engine. This allows users to build and improve efficient business flows even without detailed business knowledge.

[1579] The processing flow will be explained below.

[1580] Step 1:

[1581] The user inputs business information through a terminal. Business information includes the name of each procedure, detailed procedure content, dependencies, and person in charge. For example, specific business procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation" are input.

[1582] Step 2:

[1583] The terminal sends the entered business information to the server. The data is sent using a secure communication protocol.

[1584] Step 3:

[1585] The server inputs the business information received from the device into the AI ​​model, which learns this information and understands the dependencies between each business step and the most efficient execution order.

[1586] Step 4:

[1587] The server automatically generates a workflow based on the learned business information. The generated workflow is constructed taking into account the optimal dependencies between each step.

[1588] Step 5:

[1589] The server sends the generated business flow diagram to the terminal, which displays the flow diagram to the user, allowing the user to grasp the overall picture of the business flow.

[1590] Step 6:

[1591] Users can upload multiple existing business flows to the server via their terminal. For example, they can upload the "Customer Management Flow" of Department A and the "Inventory Management Flow" of Department B.

[1592] Step 7:

[1593] The server analyzes the received workflows and detects duplications and inconsistencies. For example, it detects that the "Inventory Check" step is duplicated in both departments A and B.

[1594] Step 8:

[1595] The server generates improvement proposals based on the analysis results to improve operational efficiency, such as "centralizing the inventory check step."

[1596] Step 9:

[1597] The server sends the generated improvement plan to the terminal, which then presents the improvement plan to the user and indicates the specific changes to be made.

[1598] Step 10:

[1599] The user evaluates the proposed improvements and decides whether to apply them. If so, the user sends a confirmation from the terminal to the server.

[1600] Step 11:

[1601] The server receives confirmation from the user and updates the workflow, which is then put into effect and made available for execution.

[1602] Step 12:

[1603] The server monitors the execution status of the updated business flow in real time, and if an abnormality or bottleneck occurs, the server immediately detects it.

[1604] Step 13:

[1605] The server generates new improvement plans based on the detected anomalies and bottlenecks and presents them to the user again, further improving business efficiency.

[1606] Step 14:

[1607] The server uses an emotion engine to analyze the user's emotions regarding the proposed improvement proposals. It analyzes the user's reactions (facial expressions, voice, input content, etc.) in real time to identify emotions.

[1608] Step 15:

[1609] The device will provide feedback based on the user's emotions based on the analysis results of the emotion engine. For example, if the reaction is positive, it will recommend an improvement plan, and if the reaction is negative, it will suggest a different improvement plan.

[1610] In this way, the present invention is a system that covers everything from business information to learning using AI models, automatically generated business flows and improvement suggestions, and even responses that take user emotions into consideration, providing a comprehensive solution for maximizing business efficiency.

[1611] Example 2

[1612] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1613] Conventional business management systems were inefficient because they required manual creation of business flows and human intervention to make improvement proposals. Furthermore, they were unable to consider the user's feelings and reactions, and improvement proposals sometimes did not contribute to user satisfaction.

[1614] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting business information, a means for training an artificial intelligence model on the input business information, a means for automatically generating business procedures based on the trained business information, a means for reading multiple business procedures, analyzing overlaps and inconsistencies, and generating improvement proposals, a means for presenting the generated improvement proposals, and a means for analyzing user emotions and generating responses to the presented improvement proposals. This makes it possible to automatically generate business flows and provide improvement proposals that take user satisfaction into consideration.

[1615] "Business information" is a general term for information necessary for generating and analyzing business flows, such as business procedures, details, dependencies, and person in charge information.

[1616] An "artificial intelligence model" is a type of algorithm that learns specific tasks based on large amounts of data and automatically generates business processes and suggests improvements.

[1617] A "business procedure" refers to a series of steps or processes taken to accomplish a particular task.

[1618] "Improvement proposals" are proposed changes or advice automatically generated by the system with the aim of streamlining and optimizing business procedures.

[1619] "User emotion" refers to the emotional state that results from analyzing the feedback and reactions that the user gives to the system.

[1620] An "abnormality" refers to an unexpected event or error that occurs during the course of business procedures.

[1621] A "bottleneck" is a part of a business process that causes a decrease in efficiency or delays in work.

[1622] This invention is a system that uses artificial intelligence to automatically generate work procedures based on work information and analyzes user emotions. This system starts with the input of work information, then learns using an artificial intelligence model, analyzes the automatically generated work procedures and proposes improvements, and then customizes them according to the user's emotions.

[1623] Entering and learning business information

[1624] User

[1625] The user uses a terminal to input business information. Specific input content includes the name of the procedure, details, dependencies, and person in charge information. For example, the user inputs procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation."

[1626] Terminal

[1627] The terminal sends the entered business information to the server, using a secure communication protocol (e.g., HTTPS) to transfer the information.

[1628] server

[1629] The server stores the received business information in a database. The business information retrieved from the database is then fed into the AI ​​model, which begins the learning process. The AI ​​model analyzes the provided data and understands the dependencies and flow of each step.

[1630] Automatic creation and presentation of business procedures

[1631] server

[1632] The server automatically generates optimal business procedures based on the learned information. The generated procedures are constructed efficiently, taking into account the dependencies between procedures.

[1633] Terminal

[1634] The terminal displays the business procedure diagram generated by the server to the user. This display uses a visualization tool such as a flowchart generator, allowing the user to grasp the overall picture of the business procedure.

[1635] Integration of multiple business procedures and proposal of improvements

[1636] User

[1637] Users upload multiple existing business procedures to the server via their terminal, which makes it possible to integrate and compare multiple business procedures.

[1638] server

[1639] The server analyzes the uploaded business procedures and detects duplications and inconsistencies. For example, it detects duplication of the "inventory check" step between "customer management procedures" and "inventory management procedures." This analysis process is performed using a data analysis algorithm.

[1640] Specific examples

[1641] Based on the detection result that "the inventory check steps are duplicated," the server generates an improvement plan to "consolidate the inventory check steps."

[1642] Evaluating and implementing improvement plans

[1643] server

[1644] The server sends the generated improvement proposal to the terminal. The improvement proposal includes specific steps and benefits, and is presented in a format that is easy for the user to understand.

[1645] User

[1646] The user evaluates the proposed improvement proposals and decides whether to apply them. If the user confirms the application, the user sends feedback from the device to the server.

[1647] server

[1648] The server receives user feedback and updates the business procedures. New business procedures are constructed by referencing existing data and are set to an executable state.

[1649] Emotion engine response

[1650] server

[1651] The server uses an emotion engine to analyze the user's reactions in real time, analyzing feedback, facial expressions, and voice data to identify the user's emotional state.

[1652] Specific examples

[1653] If the user expresses positive emotions (satisfaction or joy) toward the improvement proposal, the server retains that information and recommends implementing the improvement proposal. Conversely, if the user expresses negative emotions (dissatisfaction or confusion), a different improvement proposal is presented.

[1654] Terminal

[1655] The device displays the results of the emotion engine to the user, who receives new suggestions based on the feedback and can select the improvement suggestions that best suit their needs.

[1656] Real-time monitoring and revision of business procedures

[1657] server

[1658] The server monitors the implementation status of the updated business procedures in real time, and if an abnormality or bottleneck is discovered during the business process, it immediately detects it and notifies the user.

[1659] Specific examples

[1660] If the server detects a bottleneck during the inventory check step, it immediately notifies the user of the impact and uses an emotion engine to suggest new improvement ideas.

[1661] Example prompts to be input to the generative AI model

[1662] Example prompts

[1663] "The user enters business information such as customer information, order confirmation, inventory check, order placement, and order confirmation. If there are dependencies between these steps, generate the optimal business flow. Also, based on the user's reaction to the proposed improvements, use an emotion engine to make new suggestions."

[1664] As described above, this invention is a system that starts with inputting business information, learns using an AI model, automatically generates business procedures, and then uses an emotion engine to provide user-friendly improvement suggestions. This allows users to build and improve efficient business procedures even without detailed business knowledge.

[1665] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1666] Step 1:

[1667] User

[1668] The user uses a terminal to input business information, including the name of the procedure (e.g., "Enter customer information," "Order confirmation," "Inventory check," "Place order," "Order confirmation," etc.), details, dependencies, and person in charge.

[1669] Input: Business information entered by the user (procedure name, details, dependencies, person in charge information)

[1670] Output: Business information stored on the device

[1671] Step 2:

[1672] Terminal

[1673] The terminal sends the entered business information to the server, using a secure communication protocol (e.g., HTTPS) to transfer the information.

[1674] Input: Business information entered in Step 1

[1675] Output: Business information sent to the server

[1676] Step 3:

[1677] server

[1678] The server stores the received business information in a database. The business information retrieved from the database is then fed into an AI model to begin the learning process. The AI ​​model analyzes the provided data and understands the dependencies and flow of each step.

[1679] Input: Business information sent from the terminal

[1680] Output: Data trained by the AI ​​model

[1681] Step 4:

[1682] server

[1683] The server automatically generates optimal business procedures based on the learned information. The generated procedures are constructed efficiently, taking into account the dependencies between procedures.

[1684] Input: Trained data

[1685] Output: Generated business procedures

[1686] Step 5:

[1687] Terminal

[1688] The terminal displays the business procedure diagram generated by the server to the user. This display uses a visualization tool such as a flowchart generator, allowing the user to grasp the overall picture of the business procedure.

[1689] Input: Generated business procedure

[1690] Output: Business procedure diagram displayed on the terminal

[1691] Step 6:

[1692] User

[1693] Users upload multiple existing business procedures to the server via their terminal, which makes it possible to integrate and compare multiple business procedures.

[1694] Input: Existing business procedures uploaded by the user

[1695] Output: Multiple business procedures uploaded to the server

[1696] Step 7:

[1697] server

[1698] The server analyzes the uploaded business procedures and detects duplications and inconsistencies. For example, it detects duplication of the "inventory check" step between "customer management procedures" and "inventory management procedures." This analysis process is performed using a data analysis algorithm.

[1699] Input: Multiple Business Procedures

[1700] Output: Detected duplicates and inconsistencies

[1701] Step 8:

[1702] server

[1703] Based on the detection results, the server generates appropriate improvement suggestions, such as consolidating overlapping steps.

[1704] Input: Detected duplicates and inconsistencies

[1705] Output: Improvement suggestions

[1706] Step 9:

[1707] server

[1708] The server then sends the generated improvement proposals to the terminal and presents them to the user. The proposals include specific steps and their benefits.

[1709] Input: Improvement suggestion

[1710] Output: Improvement suggestions sent to the device

[1711] Step 10:

[1712] User

[1713] The user evaluates the proposed improvement suggestions and decides whether to apply them. The evaluation results and feedback are entered into the terminal and sent to the server.

[1714] Input: User ratings and feedback

[1715] Output: Rating and feedback sent to the server

[1716] Step 11:

[1717] server

[1718] The server updates business procedures based on user feedback. New procedures are built by referencing existing data and set to executable status.

[1719] Input: Ratings and Feedback

[1720] Output: Updated business procedures

[1721] Step 12:

[1722] server

[1723] The server uses an emotion engine to analyze the user's reactions in real time, analyzing feedback, facial expressions, and voice data to identify the user's emotional state.

[1724] Input: User feedback, facial expressions, and voice data

[1725] Output: Identified emotional state

[1726] Step 13:

[1727] server

[1728] The server adjusts the improvement suggestions based on the user's emotional state: if the emotion is positive, it recommends a suggestion, and if the emotion is negative, it presents a different suggestion.

[1729] Input: Identified emotional state

[1730] Output: Adjusted improvement suggestions

[1731] Step 14:

[1732] Terminal

[1733] The device displays the results of the emotion engine to the user and provides new suggestions, allowing the user to select the improvement suggestions that best suit their needs.

[1734] Input: Adjusted improvement suggestions

[1735] Output: The new proposal displayed to the user

[1736] Step 15:

[1737] server

[1738] The server monitors the implementation status of the updated business procedures in real time, and if an abnormality or bottleneck is discovered during the business process, it immediately detects it and notifies the user.

[1739] Input: Updated business procedures

[1740] Output: Real-time monitoring results and abnormality notifications

[1741] (Application example 2)

[1742] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1743] Conventional workflow automatic generation systems have limitations in terms of improving and optimizing workflow efficiency. Furthermore, continuous improvements that take user emotions and feedback into account are rare, making continuous improvement of workflows difficult. Furthermore, when robots perform work in factories, real-time monitoring and improvement proposals are necessary to improve the effectiveness of the workflow, but efficient methods for doing this have not yet been established. Furthermore, there is a need for a system that can determine whether proposed improvements are appropriate based on user emotions.

[1744] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1745] In this invention, the server includes means for inputting business information, means for training an AI model to learn the input business information, means for automatically generating a business flow based on the learned business information, means for reading multiple business flows, analyzing overlaps and inconsistencies, and generating improvement proposals, means for presenting the generated improvement proposals, means for analyzing user emotions, and means for evaluating the proposed improvement proposals based on the emotion analysis and re-proposing them as necessary. This makes it possible to optimize business flows while taking user emotions into consideration, and to monitor and propose improvements in real time.

[1746] "Business information" is information that includes procedures, processes, people, dependencies, etc. related to the operation of a company or organization.

[1747] An "AI model" is an algorithm and its settings that uses artificial intelligence technology to learn from data and perform pattern recognition and prediction.

[1748] A "business flow" is a set of procedures or processes set up to accomplish a specific task.

[1749] "Automatically generating" means that the system automatically generates results based on pre-set algorithms or rules.

[1750] "Duplicate" means that there are multiple identical or similar procedures or data.

[1751] An "inconsistency" is when multiple procedures or data are inconsistent or inconsistent.

[1752] "Improvements" are suggestions or changes to make current processes or procedures more efficient or effective.

[1753] "User emotions" refers to the emotional reactions and feedback given by system users.

[1754] "Analyzing" means collecting data or information and analyzing it to find meaning and patterns.

[1755] "Real time" refers to the ability to process ongoing events and actions and provide results immediately.

[1756] A "bottleneck" is a factor or obstacle that slows down the overall progress of a task or process.

[1757] A "re-proposal" is a proposal that is presented again to improve something that was previously proposed, based on new information or feedback.

[1758] "Customization" means adapting or modifying a system or process to meet specific requirements or needs.

[1759] 1. An overview of the system that realizes this application example is given below. The system automatically generates, monitors, and improves the work flow of robots used in factories in real time, and is composed of the following main components.

[1760] 2. The server has a means of inputting business information. Procedures, processes, personnel, dependencies, and other information related to the operation of a company or organization are input via a terminal. Based on this, the server trains an AI model based on the input business information. Specific AI technologies used include TensorFlow and Keras.

[1761] 3. The AI ​​model learns from the submitted business information and has the means to automatically generate a business flow. Based on the learned information, it constructs the most efficient business flow. This generated business flow is displayed on the terminal in real time by the server.

[1762] 4. The server has a means to read multiple business flows, analyze overlaps and inconsistencies, and generate improvement proposals. This allows overlaps and inconsistencies between business flows to be discovered and improvement proposals to resolve them to be proposed.

[1763] 5. The server has a means to present the generated improvement proposals and a means to analyze the user's emotions. The user inputs feedback through a device, smart glasses, or a head-mounted display, and the emotions are analyzed. OpenCV and a specific emotion analysis model are used for the analysis.

[1764] 6. The server has the means to evaluate the proposed improvement plan based on the user's sentiment analysis and re-propose it if necessary. If the user's sentiment is negative, the AI ​​model recalculates the workflow and proposes a new improvement plan.

[1765] 7. Furthermore, the server has the means to monitor the execution status of the business flow in real time and detect anomalies and bottlenecks. If an anomaly is detected, the server will again propose improvements, taking into account the user's emotional data.

[1766] 8. The user has the means to evaluate and confirm the revised workflow. After confirmation, the server updates the workflow and puts the new workflow into operation. The server can also customize the workflow based on the user's emotional data.

[1767] Examples:

[1768] In a factory, robots assemble parts one by one. To optimize this workflow, a server automatically generates a workflow and monitors it in real time. For example, a new workflow proposal might be generated to "rearrange the order of parts." However, if a worker shows a confused expression, an emotion analysis engine detects this and the server reconsiders the workflow. For example, it might suggest a different improvement, such as "changing the placement of assembly tools."

[1769] Example prompt sentence:

[1770] "A new workflow has been generated that rearranges the order of parts. The worker's emotional data revealed a confused response. Based on this response, please suggest another workflow improvement."

[1771] In this way, the invention makes it possible to optimize workflows while taking into account the user's emotions, and realizes real-time monitoring and improvement suggestions.

[1772] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1773] Step 1:

[1774] The user inputs business information into the device. The device then sends the input business information, such as procedures, processes, personnel, and dependencies, to the server. The server receives this information and inputs it into the AI ​​model. The server then uses TensorFlow and Keras to train the business information. The input is the business information, and the output is the trained business model.

[1775] Step 2:

[1776] The server automatically generates a workflow based on the learned business information. The AI ​​model constructs an optimal workflow based on the received business information. This workflow is efficiently assembled, taking into account the dependencies between steps. The generated workflow is sent from the server to the terminal, which displays it to the user. The input is the trained business model, and the output is the generated workflow.

[1777] Step 3:

[1778] The server loads multiple business processes and analyzes them for overlaps and inconsistencies. The server analyzes each step in the business process and detects any overlaps or inconsistencies. The server uses an AI model to generate improvement proposals. For example, it generates proposals to unify overlapping steps. The input is multiple business processes, and the output is improvement proposals.

[1779] Step 4:

[1780] The server sends the generated improvement proposals to the terminal and presents them to the user. The user evaluates the improvement proposals and provides feedback through the terminal. This feedback also includes the user's emotional data. The input is the improvement proposals, and the output is the user's feedback and emotional data.

[1781] Step 5:

[1782] The server analyzes the user's emotions. It uses OpenCV or a specific emotion analysis model to analyze the user's facial and voice data collected from the device, smart glasses, or head-mounted display. For example, if the user shows a dissatisfied expression, it is interpreted as a negative emotion. The input is the user's emotional data, and the output is the analysis result.

[1783] Step 6:

[1784] The server reevaluates improvement proposals based on sentiment analysis and re-proposes them if necessary. If the user's sentiment is negative, a new improvement proposal for the business process is regenerated using an AI model. This is an important means of increasing user satisfaction. The input is the sentiment analysis results, and the output is the re-proposed improvement proposal.

[1785] Step 7:

[1786] The server monitors the execution status of the business flow in real time and detects abnormalities and bottlenecks. For example, if there is a delay in the assembly of parts, the server will detect that step as a bottleneck. The input is real-time business data, and the output is detected abnormality information.

[1787] Step 8:

[1788] The server makes improvement suggestions based on the detected anomalies and bottlenecks. The detected anomalies and bottlenecks are analyzed using an AI model to generate optimal improvement suggestions. For example, improvement suggestions such as changing the placement of assembly tools are proposed. The input is the detected anomaly information, and the output is the improvement suggestions.

[1789] Step 9:

[1790] The user evaluates and confirms the revised workflow through the terminal. The confirmed workflow is updated by the server and put into execution. The workflow is customized taking into account the user's emotional data. The input is the user's confirmation and emotional data, and the output is the updated workflow.

[1791] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1792] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1793] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1794] [Fourth embodiment]

[1795] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1796] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1797] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1798] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1799] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1800] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1801] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1802] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1803] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1804] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1805] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1806] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1807] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1808] The present invention is a system that inputs business information, automatically generates business flows by learning them into an AI model, and then analyzes multiple business flows to propose improvement plans. This system is implemented as follows.

[1809] 1. Entering and learning business information

[1810] User

[1811] The user uses a terminal to input task information, including the name of each step, detailed procedure content, dependencies, and person in charge.

[1812] Specific examples

[1813] For example, a user inputs the following business procedure through a terminal: "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order."

[1814] server

[1815] The server receives the business information sent from the device and inputs it into the AI ​​model, which uses this data to learn about dependencies and efficient workflows.

[1816] 2. Automatic creation of business flows

[1817] server

[1818] The server automatically generates a workflow based on the business information learned by AI. The generated workflow takes into account the dependencies between each step, creating the most efficient workflow.

[1819] Specific examples

[1820] The server efficiently arranges the steps of "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order" and creates a business flow diagram.

[1821] Terminal

[1822] The terminal presents the generated workflow diagram to the user, allowing the user to grasp the overall picture of the workflow.

[1823] 3. Integration of multiple workflows and proposal of improvements

[1824] User

[1825] Users can upload multiple existing business processes to the server via their terminals.

[1826] server

[1827] The server analyzes these workflows to detect duplication and inconsistencies, and based on the results, generates improvement proposals for improving efficiency.

[1828] Specific examples

[1829] For example, if the "inventory check" procedure overlaps between Department A's "customer management flow" and Department B's "inventory management flow," the server will detect this overlap and generate an improvement proposal to "consolidate the inventory check step."

[1830] Terminal

[1831] The terminal presents the improvement proposals generated by the server to the user, who can then check and evaluate them.

[1832] 4. Evaluation and implementation of improvement plans

[1833] User

[1834] The user evaluates the proposed improvement plan and decides whether to apply it. If the improvement plan is applied, a confirmation is sent to the server via the terminal.

[1835] server

[1836] The server receives the user's confirmation and updates the workflow, which is then put into action and made live for the user to use.

[1837] 5. Collaboration and Monitoring

[1838] server

[1839] The server monitors the execution status of the updated business flow in real time, and immediately detects any abnormalities or bottlenecks that occur during the business process.

[1840] Terminal

[1841] The terminal displays a notification of any detected abnormalities or bottlenecks to the user, allowing the user to confirm that there is a problem with the progress of the business flow.

[1842] server

[1843] The server generates new improvement proposals based on the anomalies and bottlenecks and presents them to the user again.

[1844] Specific examples

[1845] For example, if the server detects that "inventory check" in the new workflow is taking longer than expected, a notification will be displayed on the terminal. The server will then suggest a new improvement plan: "Move inventory check to an automated system."

[1846] In this way, by executing a series of processes based on the present invention, from inputting business information to automatically generating a flow, proposing improvements, implementing them, and monitoring them, it is possible to improve business efficiency and strengthen cooperation.

[1847] The processing flow will be explained below.

[1848] Step 1:

[1849] The user inputs business information through a terminal. Business information includes the name of each procedure, detailed procedure content, dependencies, and person in charge. For example, the user might input procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation."

[1850] Step 2:

[1851] The terminal sends the entered business information to the server. The data is transmitted using a secure communication protocol.

[1852] Step 3:

[1853] The server inputs the business information received from the device into the AI ​​model, which uses this data to learn business dependencies and efficient processing sequences.

[1854] Step 4:

[1855] The server automatically generates a workflow based on the information learned by the AI ​​model. The generated workflow reflects the optimal dependencies between each step.

[1856] Step 5:

[1857] The server sends the generated business flow diagram to the terminal, where the user can view the diagram on the terminal screen.

[1858] Step 6:

[1859] Users can upload multiple existing business processes to the server via their terminals.

[1860] Step 7:

[1861] The server analyzes multiple workflows and detects duplications and inconsistencies. For example, it detects duplication of the "Stock Check" step between the "Customer Management Flow" and the "Inventory Management Flow."

[1862] Step 8:

[1863] Based on the analysis results, the server generates improvement proposals to improve business efficiency, such as "centralizing the inventory check step."

[1864] Step 9:

[1865] The server sends the generated improvement proposal to the terminal, which then presents it to the user, who then checks the contents of the improvement proposal.

[1866] Step 10:

[1867] The user evaluates the improvement plan and decides whether to apply it. If so, the terminal sends a confirmation to the server.

[1868] Step 11:

[1869] The server receives the user's confirmation and updates the workflow, making the new workflow available for execution.

[1870] Step 12:

[1871] The server monitors the execution status of the updated business flow in real time, and immediately detects any abnormalities or bottlenecks that occur.

[1872] Step 13:

[1873] The server generates new improvement proposals based on the detected anomalies and bottlenecks, such as "shift inventory checks to an automated system."

[1874] Step 14:

[1875] The server sends new improvement proposals to the terminal and presents them to the user again, who then checks them and considers how to respond.

[1876] Example 1

[1877] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1878] In today's business environment, streamlining and improving workflows is extremely important. However, conventional methods require a significant amount of time and effort to manually input and analyze business information, resulting in low accuracy in automatically generating workflows and improving proposals. Furthermore, it is difficult to integrate multiple workflows, detect overlaps and inconsistencies, and generate efficient improvement proposals. The present invention aims to solve these problems and provide a system that streamlines and optimizes workflows in real time.

[1879] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1880] In this invention, the server includes means for inputting business information, means for training a generative AI model on the input business information, means for automatically generating a business flow based on the trained business information, means for presenting the generated business flow, means for integrating and analyzing multiple business flows, detecting duplications and inconsistencies, and generating improvement proposals, and means for presenting the generated improvement proposals. This enables automatic input of business information, automatic generation of efficient workflows, integrated analysis of multiple business flows, and generation and presentation of optimized improvement proposals.

[1881] "Business information" is data such as business-related procedures, detailed procedure content, dependencies, and personnel in charge.

[1882] A "generative AI model" is an algorithm or machine learning model that learns business information and automatically generates optimal business flows and proposes improvements.

[1883] A "business flow" refers to the flow of a series of procedures or processes for carrying out a specific business operation.

[1884] "Automatic generation" means that the system automatically creates a business flow based on the input information without human intervention.

[1885] "Integration" means combining multiple business flows into one entity.

[1886] "Duplicate" refers to the occurrence of the same procedure multiple times in different business processes, which can lead to inefficiency.

[1887] "Inconsistency" refers to a state in which the order or content of a business flow is inconsistent.

[1888] "Improvement proposals" are specific proposals aimed at streamlining and optimizing business processes.

[1889] "Presentation" refers to the display of system-generated information or data in a form that is visible to the user.

[1890] "Monitoring" means continuously observing the execution status of a business flow and checking for any abnormalities or problems.

[1891] An "abnormality" is an unexpected problem or obstacle that occurs in the normal course of business.

[1892] A "bottleneck" is a procedure in a business flow that is slower to execute than other procedures and that causes a decrease in overall efficiency.

[1893] The present invention is a system that automatically generates workflows by inputting business information and training a generative AI model, and then analyzes multiple workflows to propose improvements. This system is implemented as follows.

[1894] Entering and learning business information

[1895] User

[1896] The user uses the terminal to input business information. This information includes the name of each step, detailed procedure content, dependencies, and the person in charge. For example, the user inputs the business procedure "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order" through the terminal. After completing the input, the user clicks the "Send button" to send the business information to the server.

[1897] server

[1898] The server receives business information sent from the device and inputs the data into a generative AI model using Python, TensorFlow, etc. This model retrains based on the received data, learning dependencies between business processes and efficient workflows.

[1899] Automatic creation of business flows

[1900] server

[1901] The server obtains the optimized business flow from the generative AI model that has completed training, and automatically generates a business flow diagram based on that data. Specifically, it uses libraries such as Graphviz to generate a diagram that can be displayed visually.

[1902] Presentation of business flow

[1903] Terminal

[1904] The terminal displays the generated business flow diagram to the user. The user can check the generated flow and make any necessary corrections. For example, the user can check the generated business flow diagram on the terminal and click the "Confirm" button to confirm the contents.

[1905] Integration and analysis of multiple workflows

[1906] User

[1907] Users upload multiple existing business processes collected from different departments and projects to the server via their terminal in CSV or Excel format.

[1908] server

[1909] The server analyzes the multiple workflows uploaded and detects duplication, inconsistencies, and unnecessary steps. For example, it uses the Python "Pandas" library to analyze the data and identify duplicate steps and inconsistencies.

[1910] Generate and present improvement proposals

[1911] server

[1912] Based on the analysis results, the server integrates each business flow and generates improvement proposals for efficiency. The generated improvement proposals are then optimized again through the generative AI model. For example, it generates an efficiency proposal such as "centralizing inventory confirmation procedures."

[1913] Terminal

[1914] The device displays the generated improvement proposal to the user, who can then review it and provide feedback. Specifically, the device displays the improvement proposal on the screen, and the user submits feedback by pressing the "improvement proposal approval button."

[1915] Evaluating and applying improvements

[1916] User

[1917] The user evaluates the proposed improvement plan, and if they decide to apply it, they send a confirmation to the server via their device.

[1918] server

[1919] The server receives the user's confirmation, updates the workflow, and makes the new workflow executable. For example, the user evaluates the improvement proposal from their terminal, and after approval, presses the "Confirm and Send" button to send it to the server. The server updates the workflow and generates a new workflow.

[1920] Implementing and monitoring updated workflows

[1921] server

[1922] The server executes the new workflow and monitors its execution in real time. The monitoring data is saved in a log for later analysis.

[1923] Terminal

[1924] The terminal displays the execution status data received from the server to the user in real time. For example, the terminal displays the progress status of the business flow being executed in real time, and the user can check it.

[1925] Anomaly detection and generation of new improvement suggestions

[1926] server

[1927] The server detects anomalies and bottlenecks while the business flow is in progress, and generates an alert if a certain performance indicator cannot be exceeded. When an anomaly or bottleneck is detected, a new improvement proposal is generated. For example, the server detects that the time taken for "inventory check" is abnormally long and generates an alert. Based on this, a new improvement proposal to "transfer inventory checks to an automated system" is generated and presented to the user.

[1928] Prompt Sentence Examples

[1929] Please tell me how to enter customer information.

[1930] "Please suggest ways to automate inventory checks."

[1931] "Please tell me the efficient order processing flow."

[1932] In this way, the present invention executes a series of processes from inputting business information to automatically generating a flow, integrating and analyzing multiple business flows, generating and presenting improvement proposals for efficiency, implementing and monitoring the revised business flow, detecting anomalies, and generating new improvement proposals, thereby achieving improved and optimized business efficiency.

[1933] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1934] Step 1: Enter your business information

[1935] User

[1936] The user uses the terminal to input business information such as the name of each procedure, detailed procedure content, dependencies, and person in charge. After inputting the information, the user clicks the "Send" button to send the business information to the server.

[1937] Specific actions

[1938] The user enters the business procedure into the terminal, such as "Enter customer information -> Confirm order -> Check inventory -> Place order -> Confirm order", and clicks the "Send button".

[1939] input

[1940] Business procedures, detailed procedure content, dependencies, and person information.

[1941] output

[1942] Sending business information to the server.

[1943] Step 2: Send data to the AI ​​model and train it

[1944] server

[1945] The server receives business information sent from the device and inputs the data into the generative AI model using Python, TensorFlow, etc. The generative AI model learns based on this data.

[1946] Specific actions

[1947] The server inputs the received business procedure data into the AI ​​model and starts the "business flow optimization process."

[1948] input

[1949] Business information data.

[1950] output

[1951] Learned business flow dependencies and efficient flow.

[1952] Step 3: Automatic generation of business flow

[1953] server

[1954] The server obtains the optimized workflow from the generative AI model that has completed training, and automatically generates a workflow diagram based on that data. A visually displayable diagram is generated using a library such as Graphviz.

[1955] Specific actions

[1956] The server receives the optimized business procedures from the AI ​​model and generates a "business flow diagram" using Graphviz.

[1957] input

[1958] Data for optimized business flows.

[1959] output

[1960] Business flow diagram.

[1961] Step 4: Presenting the generated workflow

[1962] Terminal

[1963] The terminal displays the generated business flow diagram to the user, who can then check the generated flow and make any necessary corrections.

[1964] Specific actions

[1965] The terminal displays the generated business flow diagram on the screen, and the user clicks the "Confirm button" to confirm the contents.

[1966] input

[1967] The generated business flow diagram.

[1968] output

[1969] A workflow diagram displayed to the user.

[1970] Step 5: Integrate and analyze multiple workflows

[1971] User

[1972] Users upload multiple existing business processes collected from different departments and projects to the server via their terminal in CSV or Excel format.

[1973] server

[1974] The server analyzes the uploaded workflows to detect duplication, inconsistencies, and unnecessary steps. It uses the Python "Pandas" library to perform data analysis.

[1975] Specific actions

[1976] Users upload multiple business flow data using their devices, and the server analyzes it.

[1977] input

[1978] Data from multiple existing business processes.

[1979] output

[1980] Duplicate and inconsistency detection results.

[1981] Step 6: Generate and present improvement proposals

[1982] server

[1983] Based on the analysis results, the server integrates each business flow and generates improvement proposals for efficiency. These improvement proposals are then optimized again through the generative AI model.

[1984] Specific actions

[1985] The server generates efficiency proposals such as "centralizing inventory confirmation procedures" and provides them to the user in an optimized form.

[1986] input

[1987] Analysis results and data for generating improvement proposals.

[1988] output

[1989] Optimized improvement suggestions.

[1990] Terminal

[1991] The device displays the generated improvement suggestions to the user, who can review them and provide feedback.

[1992] Specific actions

[1993] The device displays the improvement proposal on the screen, and the user presses the "improvement proposal approval button" to submit feedback.

[1994] input

[1995] Generated improvement suggestions.

[1996] output

[1997] The suggested improvements shown to the user.

[1998] Step 7: Evaluate and apply the improvements

[1999] User

[2000] The user evaluates the proposed improvement plan and decides whether to apply it. If they decide to apply it, they send a confirmation to the server via their device.

[2001] server

[2002] The server receives the user's confirmation, updates the workflow, and makes the new workflow executable.

[2003] Specific actions

[2004] The user evaluates the improvement proposal from their device, and after approval, presses the "Confirm and Send" button to send it to the server. The server updates the workflow and creates a new workflow.

[2005] input

[2006] User feedback and confirmation.

[2007] output

[2008] A new work flow that can be implemented.

[2009] Step 8: Implement and monitor the updated workflow

[2010] server

[2011] The server executes the new workflow and monitors its execution in real time. The monitoring data is saved in a log for later analysis.

[2012] Specific actions

[2013] The server implements the new workflow and monitors its progress.

[2014] input

[2015] Data for the new business flow.

[2016] output

[2017] Monitoring log data.

[2018] Terminal

[2019] The terminal displays the execution status data received from the server to the user in real time.

[2020] Specific actions

[2021] The terminal displays the progress of the business flow being executed in real time, and the user can check it.

[2022] input

[2023] Data on the running business flow.

[2024] output

[2025] The execution status displayed to the user.

[2026] Step 9: Anomaly detection and notification

[2027] server

[2028] The server generates alerts based on performance indicators to detect anomalies and bottlenecks during the workflow, and if anomalies or bottlenecks are detected, it generates new improvement proposals.

[2029] Specific actions

[2030] The server detects that the "inventory check" time is abnormally long and generates an alert.

[2031] input

[2032] Performance data for the running business flow.

[2033] output

[2034] Anomaly detection alerts and improvement suggestions.

[2035] Step 10: Generate new improvement suggestions

[2036] server

[2037] If the server detects an anomaly or bottleneck, it generates a new improvement proposal, such as "shift inventory checks to an automated system," and presents it to the user.

[2038] Specific actions

[2039] The server detects the anomaly and generates a new improvement proposal, such as "transfer inventory checks to an automated system," and presents it to the user.

[2040] input

[2041] Anomaly detection data.

[2042] output

[2043] New improvement proposals.

[2044] (Application example 1)

[2045] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2046] Optimizing and streamlining workflows is a key issue for logistics centers. It is necessary to minimize time and cost waste and improve overall operational performance in a series of procedures, including receiving, sorting, shelving, picking, packing, and shipping. However, traditional methods make it difficult to optimize workflows, and there is a problem of being unable to quickly respond to bottlenecks or abnormalities that occur during operations.

[2047] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2048] In this invention, the server includes means for inputting business information, means for training an AI model to learn the input business information, means for automatically generating a business flow based on the learned business information, means for reading multiple business flows, analyzing overlaps and inconsistencies, and generating improvement proposals, means for presenting the generated improvement proposals, and means for optimizing procedures for receiving, sorting, shelving, picking, packing, and shipping items in logistics operations, thereby enabling optimization and improvement of business flows in logistics centers.

[2049] "Business information" refers to information such as the name of each business procedure, detailed procedure content, dependencies, and person in charge.

[2050] An "AI model" refers to an artificial intelligence system that learns from business information and generates and improves optimal business flows.

[2051] "Business flow" refers to the flow of a series of procedures or processes set up to carry out a specific task.

[2052] "Overlap" refers to a situation in which the same procedure is repeated in different business flows.

[2053] "Inconsistency" refers to a situation in which procedures and processes do not match between multiple business flows.

[2054] "Improvement proposals" refer to proposed changes or corrections to improve the efficiency and optimization of business processes.

[2055] "Logistics operations" refers to a series of business processes such as receiving, sorting, putting away, picking, packing, and shipping goods.

[2056] "Optimization" refers to building and adjusting business processes in the most efficient and effective way for specified purposes and conditions.

[2057] A "bottleneck" refers to a part or step in a business flow that hinders efficiency or progress.

[2058] The present invention is a system for optimizing and improving the workflow in a logistics center. A specific embodiment of the system is described below.

[2059] System configuration

[2060] The system consists of the following components:

[2061] A means of entering business information

[2062] A means of training an AI model based on input business information

[2063] A means of automatically generating workflows based on learned business information

[2064] A means of reading multiple business processes, analyzing overlaps and inconsistencies, and generating improvement proposals

[2065] A means of presenting generated improvement proposals

[2066] A means of optimizing the receiving, sorting, putting away, picking, packing, and shipping procedures of logistics operations

[2067] Hardware and software used

[2068] Hardware: Servers (for data processing and storage), terminals (for users to input business information)

[2069] Software: Flask (web framework), AI model (for learning and generating business flows)

[2070] Program processing explanation

[2071] User: Enters operational information using a device (such as a smartphone or tablet), including procedures for receiving, sorting, putting away, picking, packing, and shipping items.

[2072] Server: Receives business information entered by users and sends it to the AI ​​model for learning. Based on the learning data, it automatically generates efficient business flows.

[2073] AI model: Uses business information to learn about dependencies and optimal workflows within business processes, and returns the generated workflow to the server.

[2074] Server: Analyzes multiple business processes and detects duplications and inconsistencies. Based on the results, it generates improvement proposals and presents them to the user.

[2075] Terminal: Improvement proposals, anomalies, and bottlenecks are displayed to the user in real time, allowing the user to review and evaluate updates to the workflow.

[2076] Server: Updates the business flow based on user feedback and implements the optimized flow. It also monitors the implementation status in real time, detects new anomalies and bottlenecks, and makes new proposals.

[2077] Specific examples

[2078] For example, if a logistics center has the following workflow:

[2079] Receiving goods

[2080] classification

[2081] Shelving

[2082] picking

[2083] packing

[2084] shipping

[2085] When the user inputs these steps into their device, the server trains the AI ​​model. The AI ​​model learns the dependencies and efficiency of each input step and generates an optimal workflow. The generated workflow is presented to the user by the server and is further improved based on subsequent feedback.

[2086] Example prompt sentence:

[2087] You are considering optimizing the workflow at your distribution center. Follow these steps to generate the most efficient workflow:

[2088] 1. Receiving your items

[2089] 2. Classification

[2090] 3. Shelving

[2091] 4. Picking

[2092] 5. Packaging

[2093] 6. Shipping

[2094] Please also suggest improvements to the above flow to improve its efficiency.

[2095] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2096] Step 1:

[2097] The user inputs business information into the terminal.

[2098] The business information to be entered includes the procedures for receiving, sorting, putting away, picking, packing, and shipping. For example, the flow "receiving goods -> sorting -> putting away -> picking -> packing -> shipping" is entered. This collects information such as the name of the business procedure, detailed procedure content, dependencies, and person in charge.

[2099] Step 2:

[2100] The server receives the business information sent from the terminal.

[2101] The server sends the input business information to the AI ​​model, and learning begins. The input data includes the flow of business procedures and their dependencies. The AI ​​model uses this data to learn the dependencies between each procedure and the efficient flow.

[2102] Step 3:

[2103] The server automatically generates a business flow based on the learned business information.

[2104] The server receives the optimal workflow returned by the AI ​​model and automatically generates this workflow, for example, arranging the steps of "receiving goods -> sorting -> shelving -> picking -> packing -> shipping" in the most efficient way.

[2105] Step 4:

[2106] A user uploads multiple existing business processes to a server via a terminal.

[2107] To integrate different flows, the user sends an existing business flow to the server, which then integrates multiple business flows, including overlapping and inconsistent flows, into the server.

[2108] Step 5:

[2109] The server analyzes multiple business flows and detects duplications and inconsistencies.

[2110] The server uses the analyzed data to detect duplication and inconsistencies in business flows. For example, if the same procedure exists in multiple flows, it detects this and generates improvement proposals.

[2111] Step 6:

[2112] Based on the detection results, the server generates improvement proposals for efficiency.

[2113] The server generates improvement proposals to optimize the workflow based on the detected duplications and inconsistencies. For example, it may generate an improvement proposal to "consolidate inventory checks."

[2114] Step 7:

[2115] The terminal presents the generated improvement proposal to the user.

[2116] The user can then view the proposed improvements from the server via their device. The improvements are displayed visually as a workflow diagram, allowing the user to evaluate them and make any necessary changes.

[2117] Step 8:

[2118] The server monitors the implementation status of the business flow in real time.

[2119] The server monitors the execution of the updated workflow and detects anomalies and bottlenecks, for example, if a particular step takes longer than expected.

[2120] Step 9:

[2121] The device displays notifications to the user about detected anomalies and bottlenecks.

[2122] Users can receive notifications from the server via their devices and be aware of any problems with the progress of their work, enabling them to take prompt action.

[2123] Step 10:

[2124] The server generates new improvement proposals based on the anomalies and bottlenecks and presents them to the user again.

[2125] Based on the detected anomalies and bottlenecks, the server generates improvement proposals for further efficiency improvements and notifies the user via the terminal. For example, a new improvement proposal might be presented, such as "shifting inventory checks to an automated system."

[2126] This allows users to constantly optimize the progress of their work.

[2127] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2128] This invention combines a system that uses AI to automatically generate workflows based on business information and continuously improves those workflows with an emotion engine that analyzes user emotions. This system starts with the input of business information, then learns using an AI model, analyzes the automatically generated workflow and proposes improvements, and then customizes it according to the user's emotions.

[2129] 1. Entering and learning business information

[2130] User

[2131] The user uses a terminal to input business information, including the name, details, dependencies, and person in charge information for each step.

[2132] Specific examples

[2133] For example, the user inputs procedures such as "enter customer information," "confirm order," "check inventory," "place order," and "confirm order" into the terminal.

[2134] Terminal

[2135] The terminal sends the entered business information to the server, where the information is transferred using a secure communication protocol.

[2136] server

[2137] The server receives the business information and inputs it into the AI ​​model, which then learns from it and understands the dependencies and flow of each step.

[2138] 2. Automatic creation and presentation of business flows

[2139] server

[2140] The server automatically generates the optimal workflow based on the learned information, taking into account the dependencies between each step to create the most efficient workflow.

[2141] Terminal

[2142] The terminal displays the generated business flow diagram to the user, allowing the user to grasp the overall picture of the business flow.

[2143] 3. Integration of multiple workflows and proposal of improvements

[2144] User

[2145] Users can upload multiple existing business processes to the server via their terminals.

[2146] server

[2147] The server analyzes these workflows and detects duplications and inconsistencies. For example, it detects cases where the "Stock Check" step overlaps between the "Customer Management Flow" and the "Inventory Management Flow."

[2148] Specific examples

[2149] The server detects duplication of inventory check steps and generates an improvement plan to "consolidate the inventory check steps."

[2150] 4. Evaluation and implementation of improvement plans

[2151] server

[2152] The server generates improvement proposals and sends them to the terminal, which then presents the proposals to the user.

[2153] User

[2154] The user evaluates the proposed improvements and decides whether to apply them. If so, the device sends a confirmation to the server.

[2155] server

[2156] The server receives the user's confirmation, updates the workflow, and makes the new workflow available for execution.

[2157] 5. Emotional Engine Response

[2158] server

[2159] The server uses an emotion engine to identify the user's feelings toward the proposed improvement proposals, analyzing feedback, facial expressions, and voice inputs in real time as the user reviews the improvement proposals.

[2160] Specific examples

[2161] If the user responds positively to the improvement proposal (e.g., satisfaction or joy), the server reads that information and recommends implementing the improvement proposal. Conversely, if the user responds negatively (e.g., dissatisfaction or confusion), the server proposes a different improvement proposal.

[2162] Terminal

[2163] The device provides feedback to the user based on the emotion engine and offers suggestions for improvements that will increase user satisfaction, thereby increasing user motivation and helping to improve work efficiency.

[2164] 6. Real-time monitoring and re-proposal of business flows

[2165] server

[2166] The server monitors the execution status of the updated business flow in real time, immediately detecting any abnormalities or bottlenecks that occur during business operations.

[2167] Specific examples

[2168] If the server detects a bottleneck in the inventory check step, it notifies the user of the impact and uses an emotion engine to suggest new improvement ideas.

[2169] In this way, this system integrates automation and a human-centered approach, starting with the input of business information, followed by learning using an AI model, automatic generation of business flows, suggesting improvement plans, and analyzing user emotions using an emotion engine. This allows users to build and improve efficient business flows even without detailed business knowledge.

[2170] The processing flow will be explained below.

[2171] Step 1:

[2172] The user inputs business information through a terminal. Business information includes the name of each procedure, detailed procedure content, dependencies, and person in charge. For example, specific business procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation" are input.

[2173] Step 2:

[2174] The terminal sends the entered business information to the server. The data is sent using a secure communication protocol.

[2175] Step 3:

[2176] The server inputs the business information received from the device into the AI ​​model, which learns this information and understands the dependencies between each business step and the most efficient execution order.

[2177] Step 4:

[2178] The server automatically generates a workflow based on the learned business information. The generated workflow is constructed taking into account the optimal dependencies between each step.

[2179] Step 5:

[2180] The server sends the generated business flow diagram to the terminal, which displays the flow diagram to the user, allowing the user to grasp the overall picture of the business flow.

[2181] Step 6:

[2182] Users can upload multiple existing business flows to the server via their terminal. For example, they can upload the "Customer Management Flow" of Department A and the "Inventory Management Flow" of Department B.

[2183] Step 7:

[2184] The server analyzes the received workflows and detects duplications and inconsistencies. For example, it detects that the "Inventory Check" step is duplicated in both departments A and B.

[2185] Step 8:

[2186] The server generates improvement proposals based on the analysis results to improve operational efficiency, such as "centralizing the inventory check step."

[2187] Step 9:

[2188] The server sends the generated improvement plan to the terminal, which then presents the improvement plan to the user and indicates the specific changes to be made.

[2189] Step 10:

[2190] The user evaluates the proposed improvements and decides whether to apply them. If so, the user sends a confirmation from the terminal to the server.

[2191] Step 11:

[2192] The server receives confirmation from the user and updates the workflow, which is then put into effect and made available for execution.

[2193] Step 12:

[2194] The server monitors the execution status of the updated business flow in real time, and if an abnormality or bottleneck occurs, the server immediately detects it.

[2195] Step 13:

[2196] The server generates new improvement plans based on the detected anomalies and bottlenecks and presents them to the user again, further improving business efficiency.

[2197] Step 14:

[2198] The server uses an emotion engine to analyze the user's emotions regarding the proposed improvement proposals. It analyzes the user's reactions (facial expressions, voice, input content, etc.) in real time to identify emotions.

[2199] Step 15:

[2200] The device will provide feedback based on the user's emotions based on the analysis results of the emotion engine. For example, if the reaction is positive, it will recommend an improvement plan, and if the reaction is negative, it will suggest a different improvement plan.

[2201] In this way, the present invention is a system that covers everything from business information to learning using AI models, automatically generated business flows and improvement suggestions, and even responses that take user emotions into consideration, providing a comprehensive solution for maximizing business efficiency.

[2202] Example 2

[2203] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2204] Conventional business management systems were inefficient because they required manual creation of business flows and human intervention to make improvement proposals. Furthermore, they were unable to consider the user's feelings and reactions, and improvement proposals sometimes did not contribute to user satisfaction.

[2205] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting business information, a means for training an artificial intelligence model on the input business information, a means for automatically generating business procedures based on the trained business information, a means for reading multiple business procedures, analyzing overlaps and inconsistencies, and generating improvement proposals, a means for presenting the generated improvement proposals, and a means for analyzing user emotions and generating responses to the presented improvement proposals. This makes it possible to automatically generate business flows and provide improvement proposals that take user satisfaction into consideration.

[2206] "Business information" is a general term for information necessary for generating and analyzing business flows, such as business procedures, details, dependencies, and person in charge information.

[2207] An "artificial intelligence model" is a type of algorithm that learns specific tasks based on large amounts of data and automatically generates business processes and suggests improvements.

[2208] A "business procedure" refers to a series of steps or processes taken to accomplish a particular task.

[2209] "Improvement proposals" are proposed changes or advice automatically generated by the system with the aim of streamlining and optimizing business procedures.

[2210] "User emotion" refers to the emotional state that results from analyzing the feedback and reactions that the user gives to the system.

[2211] An "abnormality" refers to an unexpected event or error that occurs during the course of business procedures.

[2212] A "bottleneck" is a part of a business process that causes a decrease in efficiency or delays in work.

[2213] This invention is a system that uses artificial intelligence to automatically generate work procedures based on work information and analyzes user emotions. This system starts with the input of work information, then learns using an artificial intelligence model, analyzes the automatically generated work procedures and proposes improvements, and then customizes them according to the user's emotions.

[2214] Entering and learning business information

[2215] User

[2216] The user uses a terminal to input business information. Specific input content includes the name of the procedure, details, dependencies, and person in charge information. For example, the user inputs procedures such as "Enter customer information," "Order confirmation," "Inventory check," "Place order," and "Order confirmation."

[2217] Terminal

[2218] The terminal sends the entered business information to the server, using a secure communication protocol (e.g., HTTPS) to transfer the information.

[2219] server

[2220] The server stores the received business information in a database. The business information retrieved from the database is then fed into the AI ​​model, which begins the learning process. The AI ​​model analyzes the provided data and understands the dependencies and flow of each step.

[2221] Automatic creation and presentation of business procedures

[2222] server

[2223] The server automatically generates optimal business procedures based on the learned information. The generated procedures are constructed efficiently, taking into account the dependencies between procedures.

[2224] Terminal

[2225] The terminal displays the business procedure diagram generated by the server to the user. This display uses a visualization tool such as a flowchart generator, allowing the user to grasp the overall picture of the business procedure.

[2226] Integration of multiple business procedures and proposal of improvements

[2227] User

[2228] Users upload multiple existing business procedures to the server via their terminal, which makes it possible to integrate and compare multiple business procedures.

[2229] server

[2230] The server analyzes the uploaded business procedures and detects duplications and inconsistencies. For example, it detects duplication of the "inventory check" step between "customer management procedures" and "inventory management procedures." This analysis process is performed using a data analysis algorithm.

[2231] Specific examples

[2232] Based on the detection result that "the inventory check steps are duplicated," the server generates an improvement plan to "consolidate the inventory check steps."

[2233] Evaluating and implementing improvement plans

[2234] server

[2235] The server sends the generated improvement proposal to the terminal. The improvement proposal includes specific steps and benefits, and is presented in a format that is easy for the user to understand.

[2236] User

[2237] The user evaluates the proposed improvement proposals and decides whether to apply them. If the user confirms the application, the user sends feedback from the device to the server.

[2238] server

[2239] The server receives user feedback and updates the business procedures. New business procedures are constructed by referencing existing data and are set to an executable state.

[2240] Emotion engine response

[2241] server

[2242] The server uses an emotion engine to analyze the user's reactions in real time, analyzing feedback, facial expressions, and voice data to identify the user's emotional state.

[2243] Specific examples

[2244] If the user expresses positive emotions (satisfaction or joy) toward the improvement proposal, the server retains that information and recommends implementing the improvement proposal. Conversely, if the user expresses negative emotions (dissatisfaction or confusion), a different improvement proposal is presented.

[2245] Terminal

[2246] The device displays the results of the emotion engine to the user, who receives new suggestions based on the feedback and can select the improvement suggestions that best suit their needs.

[2247] Real-time monitoring and revision of business procedures

[2248] server

[2249] The server monitors the implementation status of the updated business procedures in real time, and if an abnormality or bottleneck is discovered during the business process, it immediately detects it and notifies the user.

[2250] Specific examples

[2251] If the server detects a bottleneck during the inventory check step, it immediately notifies the user of the impact and uses an emotion engine to suggest new improvement ideas.

[2252] Example prompts to be input to the generative AI model

[2253] Example prompts

[2254] "The user enters business information such as customer information, order confirmation, inventory check, order placement, and order confirmation. If there are dependencies between these steps, generate the optimal business flow. Also, based on the user's reaction to the proposed improvements, use an emotion engine to make new suggestions."

[2255] As described above, this invention is a system that starts with inputting business information, learns using an AI model, automatically generates business procedures, and then uses an emotion engine to provide user-friendly improvement suggestions. This allows users to build and improve efficient business procedures even without detailed business knowledge.

[2256] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2257] Step 1:

[2258] User

[2259] The user uses a terminal to input business information, including the name of the procedure (e.g., "Enter customer information," "Order confirmation," "Inventory check," "Place order," "Order confirmation," etc.), details, dependencies, and person in charge.

[2260] Input: Business information entered by the user (procedure name, details, dependencies, person in charge information)

[2261] Output: Business information stored on the device

[2262] Step 2:

[2263] Terminal

[2264] The terminal sends the entered business information to the server, using a secure communication protocol (e.g., HTTPS) to transfer the information.

[2265] Input: Business information entered in Step 1

[2266] Output: Business information sent to the server

[2267] Step 3:

[2268] server

[2269] The server stores the received business information in a database. The business information retrieved from the database is then fed into an AI model to begin the learning process. The AI ​​model analyzes the provided data and understands the dependencies and flow of each step.

[2270] Input: Business information sent from the terminal

[2271] Output: Data trained by the AI ​​model

[2272] Step 4:

[2273] server

[2274] The server automatically generates optimal business procedures based on the learned information. The generated procedures are constructed efficiently, taking into account the dependencies between procedures.

[2275] Input: Trained data

[2276] Output: Generated business procedures

[2277] Step 5:

[2278] Terminal

[2279] The terminal displays the business procedure diagram generated by the server to the user. This display uses a visualization tool such as a flowchart generator, allowing the user to grasp the overall picture of the business procedure.

[2280] Input: Generated business procedure

[2281] Output: Business procedure diagram displayed on the terminal

[2282] Step 6:

[2283] User

[2284] Users upload multiple existing business procedures to the server via their terminal, which makes it possible to integrate and compare multiple business procedures.

[2285] Input: Existing business procedures uploaded by the user

[2286] Output: Multiple business procedures uploaded to the server

[2287] Step 7:

[2288] server

[2289] The server analyzes the uploaded business procedures and detects duplications and inconsistencies. For example, it detects duplication of the "inventory check" step between "customer management procedures" and "inventory management procedures." This analysis process is performed using a data analysis algorithm.

[2290] Input: Multiple Business Procedures

[2291] Output: Detected duplicates and inconsistencies

[2292] Step 8:

[2293] server

[2294] Based on the detection results, the server generates appropriate improvement suggestions, such as consolidating overlapping steps.

[2295] Input: Detected duplicates and inconsistencies

[2296] Output: Improvement suggestions

[2297] Step 9:

[2298] server

[2299] The server then sends the generated improvement proposals to the terminal and presents them to the user. The proposals include specific steps and their benefits.

[2300] Input: Improvement suggestion

[2301] Output: Improvement suggestions sent to the device

[2302] Step 10:

[2303] User

[2304] The user evaluates the proposed improvement suggestions and decides whether to apply them. The evaluation results and feedback are entered into the terminal and sent to the server.

[2305] Input: User ratings and feedback

[2306] Output: Rating and feedback sent to the server

[2307] Step 11:

[2308] server

[2309] The server updates business procedures based on user feedback. New procedures are built by referencing existing data and set to executable status.

[2310] Input: Ratings and Feedback

[2311] Output: Updated business procedures

[2312] Step 12:

[2313] server

[2314] The server uses an emotion engine to analyze the user's reactions in real time, analyzing feedback, facial expressions, and voice data to identify the user's emotional state.

[2315] Input: User feedback, facial expressions, and voice data

[2316] Output: Identified emotional state

[2317] Step 13:

[2318] server

[2319] The server adjusts the improvement suggestions based on the user's emotional state: if the emotion is positive, it recommends a suggestion, and if the emotion is negative, it presents a different suggestion.

[2320] Input: Identified emotional state

[2321] Output: Adjusted improvement suggestions

[2322] Step 14:

[2323] Terminal

[2324] The device displays the results of the emotion engine to the user and provides new suggestions, allowing the user to select the improvement suggestions that best suit their needs.

[2325] Input: Adjusted improvement suggestions

[2326] Output: The new proposal displayed to the user

[2327] Step 15:

[2328] server

[2329] The server monitors the implementation status of the updated business procedures in real time, and if an abnormality or bottleneck is discovered during the business process, it immediately detects it and notifies the user.

[2330] Input: Updated business procedures

[2331] Output: Real-time monitoring results and abnormality notifications

[2332] (Application example 2)

[2333] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2334] Conventional workflow automatic generation systems have limitations in terms of improving and optimizing workflow efficiency. Furthermore, continuous improvements that take user emotions and feedback into account are rare, making continuous improvement of workflows difficult. Furthermore, when robots perform work in factories, real-time monitoring and improvement proposals are necessary to improve the effectiveness of the workflow, but efficient methods for doing this have not yet been established. Furthermore, there is a need for a system that can determine whether proposed improvements are appropriate based on user emotions.

[2335] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2336] In this invention, the server includes means for inputting business information, means for training an AI model to learn the input business information, means for automatically generating a business flow based on the learned business information, means for reading multiple business flows, analyzing overlaps and inconsistencies, and generating improvement proposals, means for presenting the generated improvement proposals, means for analyzing user emotions, and means for evaluating the proposed improvement proposals based on the emotion analysis and re-proposing them as necessary. This makes it possible to optimize business flows while taking user emotions into consideration, and to monitor and propose improvements in real time.

[2337] "Business information" is information that includes procedures, processes, people, dependencies, etc. related to the operation of a company or organization.

[2338] An "AI model" is an algorithm and its settings that uses artificial intelligence technology to learn from data and perform pattern recognition and prediction.

[2339] A "business flow" is a set of procedures or processes set up to accomplish a specific task.

[2340] "Automatically generating" means that the system automatically generates results based on pre-set algorithms or rules.

[2341] "Duplicate" means that there are multiple identical or similar procedures or data.

[2342] An "inconsistency" is when multiple procedures or data are inconsistent or inconsistent.

[2343] "Improvements" are suggestions or changes to make current processes or procedures more efficient or effective.

[2344] "User emotions" refers to the emotional reactions and feedback given by system users.

[2345] "Analyzing" means collecting data or information and analyzing it to find meaning and patterns.

[2346] "Real time" refers to the ability to process ongoing events and actions and provide results immediately.

[2347] A "bottleneck" is a factor or obstacle that slows down the overall progress of a task or process.

[2348] A "re-proposal" is a proposal that is presented again to improve something that was previously proposed, based on new information or feedback.

[2349] "Customization" means adapting or modifying a system or process to meet specific requirements or needs.

[2350] 1. An overview of the system that realizes this application example is given below. The system automatically generates, monitors, and improves the work flow of robots used in factories in real time, and is composed of the following main components.

[2351] 2. The server has a means of inputting business information. Procedures, processes, personnel, dependencies, and other information related to the operation of a company or organization are input via a terminal. Based on this, the server trains an AI model based on the input business information. Specific AI technologies used include TensorFlow and Keras.

[2352] 3. The AI ​​model learns from the submitted business information and has the means to automatically generate a business flow. Based on the learned information, it constructs the most efficient business flow. This generated business flow is displayed on the terminal in real time by the server.

[2353] 4. The server has a means to read multiple business flows, analyze overlaps and inconsistencies, and generate improvement proposals. This allows overlaps and inconsistencies between business flows to be discovered and improvement proposals to resolve them to be proposed.

[2354] 5. The server has a means to present the generated improvement proposals and a means to analyze the user's emotions. The user inputs feedback through a device, smart glasses, or a head-mounted display, and the emotions are analyzed. OpenCV and a specific emotion analysis model are used for the analysis.

[2355] 6. The server has the means to evaluate the proposed improvement plan based on the user's sentiment analysis and re-propose it if necessary. If the user's sentiment is negative, the AI ​​model recalculates the workflow and proposes a new improvement plan.

[2356] 7. Furthermore, the server has the means to monitor the execution status of the business flow in real time and detect anomalies and bottlenecks. If an anomaly is detected, the server will again propose improvements, taking into account the user's emotional data.

[2357] 8. The user has the means to evaluate and confirm the revised workflow. After confirmation, the server updates the workflow and puts the new workflow into operation. The server can also customize the workflow based on the user's emotional data.

[2358] Examples:

[2359] In a factory, robots assemble parts one by one. To optimize this workflow, a server automatically generates a workflow and monitors it in real time. For example, a new workflow proposal might be generated to "rearrange the order of parts." However, if a worker shows a confused expression, an emotion analysis engine detects this and the server reconsiders the workflow. For example, it might suggest a different improvement, such as "changing the placement of assembly tools."

[2360] Example prompt sentence:

[2361] "A new workflow has been generated that rearranges the order of parts. The worker's emotional data revealed a confused response. Based on this response, please suggest another workflow improvement."

[2362] In this way, the invention makes it possible to optimize workflows while taking into account the user's emotions, and realizes real-time monitoring and improvement suggestions.

[2363] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2364] Step 1:

[2365] The user inputs business information into the device. The device then sends the input business information, such as procedures, processes, personnel, and dependencies, to the server. The server receives this information and inputs it into the AI ​​model. The server then uses TensorFlow and Keras to train the business information. The input is the business information, and the output is the trained business model.

[2366] Step 2:

[2367] The server automatically generates a workflow based on the learned business information. The AI ​​model constructs an optimal workflow based on the received business information. This workflow is efficiently assembled, taking into account the dependencies between steps. The generated workflow is sent from the server to the terminal, which displays it to the user. The input is the trained business model, and the output is the generated workflow.

[2368] Step 3:

[2369] The server loads multiple business processes and analyzes them for overlaps and inconsistencies. The server analyzes each step in the business process and detects any overlaps or inconsistencies. The server uses an AI model to generate improvement proposals. For example, it generates proposals to unify overlapping steps. The input is multiple business processes, and the output is improvement proposals.

[2370] Step 4:

[2371] The server sends the generated improvement proposals to the terminal and presents them to the user. The user evaluates the improvement proposals and provides feedback through the terminal. This feedback also includes the user's emotional data. The input is the improvement proposals, and the output is the user's feedback and emotional data.

[2372] Step 5:

[2373] The server analyzes the user's emotions. It uses OpenCV or a specific emotion analysis model to analyze the user's facial and voice data collected from the device, smart glasses, or head-mounted display. For example, if the user shows a dissatisfied expression, it is interpreted as a negative emotion. The input is the user's emotional data, and the output is the analysis result.

[2374] Step 6:

[2375] The server reevaluates improvement proposals based on sentiment analysis and re-proposes them if necessary. If the user's sentiment is negative, a new improvement proposal for the business process is regenerated using an AI model. This is an important means of increasing user satisfaction. The input is the sentiment analysis results, and the output is the re-proposed improvement proposal.

[2376] Step 7:

[2377] The server monitors the execution status of the business flow in real time and detects abnormalities and bottlenecks. For example, if there is a delay in the assembly of parts, the server will detect that step as a bottlene...

Claims

1. a means for inputting business information; A means to train the AI ​​model based on input business information, A means for automatically generating a workflow based on the learned business information; A means to read multiple business processes, analyze overlaps and inconsistencies, and generate improvement proposals. A means for presenting the generated improvement proposals; A system including:

2. 10. The system of claim 1, A means to monitor the implementation status of business flows in real time and detect abnormalities and bottlenecks, A means to make improvement suggestions again based on detected anomalies and bottlenecks, The system further comprises:

3. 10. The system of claim 1, A means for presenting the revised workflow and allowing the user to evaluate and confirm it; A means for updating and implementing the workflow after user confirmation; The system further comprises:

Images