system

Abstract

We provide the system. [Solution] An input method for entering the customer's name, A means for receiving the customer name entered through the input means, A means of sending requests to obtain customer-related information from multiple external systems, Means for analyzing customer-related information received from the aforementioned external system, means for generating a format based on the analyzed information, A means of displaying the generated format, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the modern business environment, companies use many systems and databases, and it is not easy to integrate and analyze customer-related information. Conventional methods require a lot of time and effort to manually collect such information and create a format. Furthermore, manually drawing a network configuration diagram is also a difficult task and it is difficult to keep it up-to-date. Therefore, there is a need for a system that can automatically collect relevant information by simply inputting a customer name and generate the required format and network configuration diagram.

Means for Solving the Problems

[0005] The present invention provides a system comprising: an input means for inputting a customer name; a means for receiving the customer name input through the input means; a means for sending requests to obtain customer-related information from a plurality of external systems; a means for analyzing the customer-related information received from the external systems; a means for generating a format based on the analyzed information; and a means for displaying the generated format. Furthermore, this system may include a means for generating a network configuration diagram based on the analyzed information, and may be configured to include a customer relationship management system, a corporate resource planning system, and a network management system as external systems.

[0006] "Input means" refers to devices or software that allow a user to input specific information via the user interface of a terminal.

[0007] "Means of receiving" refers to devices or software used to receive input information.

[0008] "Means of sending requests" refers to devices or software that have communication functions for requesting information from external systems.

[0009] "Means of analysis" refer to devices and software used to interpret received information and extract and organize necessary data.

[0010] "Means for generating a format" refers to devices or software that convert analyzed data into a defined format and make it a format that can be recorded or displayed.

[0011] "Means of display" refers to devices or software used to visually present the generated format to the user.

[0012] "Means for generating network configuration diagrams" refers to devices or software that create diagrams that visually represent the structure and connection status of a network based on analytical information.

[0013] A "customer relationship management system" is a system for collecting, managing, and analyzing customer information.

[0014] A "corporate resource planning system" is a system for the integrated management of a company's resources, finances, and personnel.

[0015] A "network management system" is a system used for the operation, monitoring, and management of a network. [Brief explanation of the drawing]

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

Embodiments for Carrying Out the Invention

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

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

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

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

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

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

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

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

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

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

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

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

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

[0037] The embodiments for implementing the system of the present invention will be described in detail below.

[0038] This system collects customer-related information based on customer names provided by the user, in conjunction with multiple systems and APIs, and automatically generates the necessary formats and network configuration diagrams.

[0039] Explanation of the program's processing

[0040] 1. Enter the customer's name.

[0041] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (for example, "ExampleCorp") into this input form and clicks the submit button.

[0042] 2. Data Collection

[0043] The server receives the request sent from the terminal and extracts the entered customer name. Next, it sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems, etc.) and related APIs to collect information about the customer "ExampleCorp".

[0044] Examples of data collection

[0045] The server sends a request to the Customer Relationship Management (CRM) system to retrieve ExampleCorp's transaction history information.

[0046] The server sends a request to the Enterprise Resource Planning (ERP) system to retrieve purchasing information for ExampleCorp.

[0047] The server sends a request to the network management system to retrieve the network configuration information for ExampleCorp.

[0048] Requests are also sent to other related APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[0049] 3. Information Analysis and Format Generation

[0050] The server analyzes the received data and extracts customer-related information (such as transaction history, purchase information, and network configuration information). Next, it generates the necessary format (FMT) based on this information.

[0051] Furthermore, the server uses the analyzed network information to generate a network configuration diagram. This involves creating a visual diagram using a network configuration diagram generation API.

[0052] 4. Providing the results

[0053] The server returns the generated format (FMT) and network diagram to the terminal. The user can then view the results displayed on the terminal screen.

[0054] Specific example

[0055] The user enters the customer name "ExampleCorp" and clicks the submit button. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. Simultaneously, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network configuration diagram for ExampleCorp are generated. Finally, the server sends these results to the terminal, and the user confirms the results.

[0056] In this way, users can easily obtain the necessary information and proceed with their work efficiently simply by entering the customer's name into the input form. This system automates many manual tasks, significantly reducing time and effort.

[0057] The following describes the processing flow.

[0058] Step 1:

[0059] The user accesses the input form on their device. The device displays an input screen for entering the customer's name.

[0060] Step 2:

[0061] The user enters a customer name (e.g., "ExampleCorp") into the input form on the device and clicks the submit button. The device then sends the entered customer name to the server.

[0062] Step 3:

[0063] The server receives the request sent from the terminal and extracts the customer name "ExampleCorp" from the request body.

[0064] Step 4:

[0065] The server sends a request to the Customer Relationship Management (CRM) system. This request includes the customer name "ExampleCorp" and asks to retrieve transaction history information.

[0066] Step 5:

[0067] The server sends a request to the Enterprise Resource Planning (ERP) system. This request includes the customer name "ExampleCorp" and requests the retrieval of purchasing information.

[0068] Step 6:

[0069] The server sends a request to the network management system. This request includes the customer name "ExampleCorp" and requests the retrieval of network configuration information.

[0070] Step 7:

[0071] The server sends requests to other relevant APIs (e.g., customer information API, network configuration API, etc.) to retrieve additional information.

[0072] Step 8:

[0073] The server aggregates the responses received from each system and API. Each response is received in JSON or XML format.

[0074] Step 9:

[0075] The server analyzes the received data and extracts necessary customer-related information (such as transaction history, purchase information, and network configuration information).

[0076] Step 10:

[0077] The server generates a Customer Information Format (FMT) based on the analysis results. For example, it creates a report-style document that combines transaction history and purchase information.

[0078] Step 11:

[0079] The server uses the network diagram generation API to generate the latest network diagram based on the acquired network information.

[0080] Step 12:

[0081] The server combines the generated customer information format (FMT) and network configuration diagram and sends them to the terminal.

[0082] Step 13:

[0083] The user confirms the results displayed on their terminal (customer information format and network configuration diagram). This allows the user to easily and quickly obtain the necessary information.

[0084] Through these steps, users can simply enter a customer's name into an input form, and information will be automatically collected from numerous systems, allowing them to easily obtain the necessary formats and network diagrams.

[0085] (Example 1)

[0086] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0087] Traditional data collection and analysis systems often involved manual data collection, which was time-consuming and labor-intensive. Furthermore, integrating information from multiple different systems, efficiently analyzing it, and generating visual network diagrams was not easy. This resulted in decreased operational efficiency and hindered rapid decision-making.

[0088] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0089] In this invention, the server includes an input means for entering a customer name, a means for receiving the customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for generating a network configuration diagram based on the format, and a means for displaying the generated format and network configuration diagram. This automates a series of processes, from entering a customer name to automatic information collection, analysis, format generation, and network configuration diagram generation and display, enabling increased operational efficiency and faster decision-making.

[0090] "Input method for entering customer names" refers to the interface used by users to enter customer names into an information processing terminal.

[0091] "Means for receiving customer names entered through the input means" refers to a component or mechanism for receiving customer names transmitted through the input means.

[0092] "Means of sending requests to obtain customer-related information from multiple external systems" refers to a function or process for sending requests to multiple different systems for information retrieval or data collection.

[0093] "Means for analyzing customer-related information received from the external system" refers to algorithms or processing mechanisms for processing data received from the external system and extracting useful information.

[0094] "Means for generating a format based on the analyzed information" refers to a function for creating a predetermined format or report format based on the information obtained through analysis.

[0095] "Means for generating a network configuration diagram based on the aforementioned format" refers to a function for visually illustrating the network configuration and topology based on the generated format information.

[0096] "Means for displaying the generated format and network diagram" refers to an interface or device for displaying the created format and network diagram in a way that is visible to the user.

[0097] A "customer relationship management system" refers to a system for managing relationships with customers and centrally managing customer information, transaction history, and other related data.

[0098] A "corporate resource planning system" is a system for efficiently managing a company's resources, and it refers to a system that comprehensively manages business processes such as purchasing, inventory, and manufacturing.

[0099] A "network management system" refers to a system that manages the configuration, status, and performance of a network, and aims to optimize the network.

[0100] An "information processing terminal" refers to a device such as a computer or mobile device that a user uses to interact with a system.

[0101] This invention relates to an information processing system that automatically collects and analyzes customer-related information in cooperation with multiple external systems and APIs based on customer names provided by users, and generates necessary formats and network configuration diagrams. The embodiments for carrying out this invention will be described in detail below.

[0102] Users can enter customer names using an input form displayed on their device. For example, a user might enter "ExampleCorp" as a customer name and click the submit button. The device then sends this input to the server.

[0103] The server receives a request from the terminal and extracts the entered customer name. Next, the server sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems) to collect information about the customer "ExampleCorp". It also sends requests to relevant APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[0104] Specifically, the following requests are sent to the external system:

[0105] A request is sent to the customer relationship management (CRM) system saying, "Please provide transaction history information."

[0106] A request is sent to the Enterprise Resource Planning (ERP) system saying, "Please provide purchasing information."

[0107] A request is sent to the network management system asking for "network configuration information."

[0108] The server analyzes the data received as a response to these requests. It integrates and analyzes the received customer-related information, extracting transaction history, purchase information, and network configuration information. Based on this information, it generates the necessary format.

[0109] Based on the generated format, the server further generates a network diagram. To generate the network diagram, the network diagram generation API is used. Specifically, the acquired network data is analyzed and the network diagram generation API is called to visually represent the network topology.

[0110] Finally, the server sends the generated format and network diagram to the terminal. The user can then view the results on the terminal screen. This allows users to easily obtain the necessary information and significantly improve work efficiency.

[0111] Example of a prompt

[0112] The following are examples of prompts to input into a generative AI model:

[0113] "This system collects customer-related information based on the customer name provided by the user, by integrating with multiple systems and APIs, and automatically generates the necessary formats and network diagrams. Specifically, when a user enters the customer name "ExampleCorp" into the input form and clicks the submit button, the server collects information from the CRM system, ERP system, network management system, and other related APIs, analyzes it, and generates the formats and network diagrams. These are then sent back to the terminal, where the user can review the results."

[0114] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0115] Step 1:

[0116] The user enters the customer name into the input form displayed on the terminal and clicks the submit button. The system receives the customer name entered by the user (e.g., "ExampleCorp") as input. This entered customer name is sent to the system.

[0117] Step 2:

[0118] The terminal sends the customer name "ExampleCorp" entered by the user to the server. The server receives the customer name sent from the terminal as input. The server extracts the customer name and stores it for use in the next step.

[0119] Step 3:

[0120] The server sends information retrieval requests to multiple external systems based on the entered customer name "ExampleCorp". Specifically, it sends the following requests to external systems:

[0121] Send a request to the CRM system to retrieve transaction history information.

[0122] A request is sent to the ERP system to retrieve purchasing information.

[0123] Send a request to the network management system to retrieve network configuration information.

[0124] The input is the customer's name, and the output is a process that sends requests to the respective systems.

[0125] Step 4:

[0126] The server receives responses to requests from external systems. Specifically, it receives the following information:

[0127] Receive transaction history information from the CRM system.

[0128] Receive purchasing information from the ERP system.

[0129] Receive network configuration information from the network management system.

[0130] The input is a response from an external system, and the output is a dataset of customer-related information.

[0131] Step 5:

[0132] The server analyzes the acquired customer-related information. Specifically, it performs the following processes:

[0133] We analyze transaction history information and extract useful data.

[0134] Analyze purchase information and extract the necessary data.

[0135] Analyze network configuration information to understand the network topology.

[0136] The system takes customer-related information obtained from an external system as input, performs data processing and calculations, and outputs analyzed information.

[0137] Step 6:

[0138] The server generates the necessary format based on the parsed information. Specifically, it performs the following processes:

[0139] Integrate transaction history information and purchase information, and create a report format.

[0140] It takes parsed information as input and generates formatted data as output.

[0141] Step 7:

[0142] The server generates a network configuration diagram based on the generated format. Specifically, it performs the following steps:

[0143] The network diagram generation API is called to visually create a network diagram.

[0144] It takes analyzed network configuration information as input and outputs a network configuration diagram.

[0145] Step 8:

[0146] The server sends the generated format data and network diagram to the terminal. It takes the generated format data and network diagram as input and sends this data to the terminal as output.

[0147] Step 9:

[0148] The terminal displays formatted data and a network diagram received from the server to the user. The user can check the results displayed on the terminal screen and obtain the necessary information. It takes data received from the server as input and provides information in a format that the user can easily understand as output.

[0149] (Application Example 1)

[0150] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0151] Conventional security information gathering systems required the individual collection and manual analysis of information from multiple external systems, which was extremely time-consuming and laborious. Furthermore, in situations demanding immediate response based on security incidents and network configurations, rapid information gathering and analysis are essential, but conventional systems struggled to provide adequate responses. Therefore, there is a need for a system that automatically and rapidly collects, analyzes, and visually displays security-related information.

[0152] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0153] In this invention, the server includes an input means for entering a customer name, a means for receiving the customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for displaying the generated format, a means for collecting and analyzing security-related information from external systems, and a means for generating the analyzed security-related information. As a result, security personnel can quickly collect and analyze security incident information and network configuration diagrams from multiple external systems and visually confirm them simply by entering a customer name into an input form.

[0154] "Customer name" refers to the name of the target company or organization entered in order to collect information from an external system.

[0155] An "input method" refers to a device or interface used by a user to input text or strings of characters.

[0156] "Means of receiving" refers to the function by which a server receives data and information transmitted through input means.

[0157] "Means of sending requests" refers to communication functions that allow a server to request information from an external system.

[0158] "Means of analysis" refers to software and algorithms used to process received information, extract, manipulate, and analyze necessary data.

[0159] A "means for generating formats" refers to a function that creates documents and charts based on analyzed data, arranged in a specific format and visual layout.

[0160] "Means of display" refers to devices or interfaces used to display the generated format in a way that is viewable by the user.

[0161] "Security-related information" refers to data concerning the security of a company or organization, including incident information, network configuration, and threat information.

[0162] "External systems" refer to all systems that work in conjunction with servers to provide information, such as security information management systems, customer relationship management systems, corporate resource planning systems, and network management systems.

[0163] A "security configuration diagram" is a diagram that visually shows the arrangement of a company's or organization's network and security equipment.

[0164] A "security information management system" is a system that manages various security-related data, such as incident information, threat status, and alert information.

[0165] The following describes a specific embodiment for carrying out this invention. The system described below is for collecting and analyzing security-related information from an external system based on the customer's name and displaying it visually. This system mainly consists of a server, a smartphone, and an external system.

[0166] 1. Enter the customer's name.

[0167] The user enters the customer name on the smartphone application. After entering the customer name in the input form, they click the submit button. This sends the customer name (e.g., "SecurityCorp") to the server.

[0168] 2. Data Collection

[0169] The server sends information gathering requests to external systems based on the received customer name. These external systems include customer relationship management systems, corporate resource planning systems, network management systems, and security information management systems. For example, the server may obtain security incident information and network configuration information from SIEM (Security Information and Event Management) systems, firewall management systems, and intrusion detection systems.

[0170] 3. Information Analysis and Format Generation

[0171] The server analyzes the collected information and generates security incident reports and network diagrams. This analysis utilizes programming languages ​​such as Python and PDF generation libraries such as ReportLab. The analyzed information is then converted into a visually easy-to-understand format.

[0172] 4. Providing the results

[0173] The generated format and network configuration diagram are displayed on a smartphone application. By reviewing this, users can quickly grasp information about security incidents and network configurations and take appropriate action.

[0174] Hardware and software to be used

[0175] Hardware: Linux (registered trademark) servers, smartphones

[0176] Software: Python (requests library, ReportLab), external systems (SIEM, firewall management system, intrusion detection system)

[0177] Specific example

[0178] For example, a security officer enters the customer name "SecurityCorp" and clicks the submit button. The server collects security incident information from the security information management system and network security configuration information from the firewall management system. This information is analyzed, a visually understandable PDF report is generated, and displayed on the smartphone application.

[0179] Examples of prompts for generative AI models

[0180] Please enter the customer name (e.g., "SecurityCorp"). Based on this input, we will automatically generate the latest security incident information, network security configuration diagrams, and security reports.

[0181] As described above, this system allows users to quickly collect, analyze, and visually display security-related information from multiple external systems simply by entering a customer's name. This enables security personnel to respond quickly and appropriately even in situations requiring immediate action.

[0182] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0183] Step 1:

[0184] The user enters the customer name on the smartphone application. They enter the customer name in the input form and click the submit button. The entered data (e.g., "SecurityCorp") is sent to the server.

[0185] Step 2:

[0186] The server receives requests sent by users and extracts the entered customer name. Based on this customer name, it generates data for requests to external systems (input: customer name "SecurityCorp", output: request data to each external system).

[0187] Step 3:

[0188] The server uses the generated request data to send information gathering requests to multiple external systems. These external systems include customer relationship management systems, corporate resource planning systems, network management systems, and security information management systems (input: request data, output: information from each system).

[0189] Step 4:

[0190] The external system receives requests from the server and returns information about the relevant customer. This includes transaction history information from the customer relationship management system, purchasing information from the corporate resource planning system, network configuration information from the network management system, and security incident information from the security information management system (input: request, output: customer-related information).

[0191] Step 5:

[0192] The server analyzes customer-related information received from external systems. This analysis process uses programming languages ​​such as Python and specific analysis algorithms to convert the received data into a formattable form (input: information from each system, output: analyzed data).

[0193] Step 6:

[0194] The server generates a visually easy-to-understand format based on the analyzed data. Specifically, it uses PDF generation libraries such as ReportLab to create reports that include security incident information and network configuration diagrams (input: analyzed data, output: generated format).

[0195] Step 7:

[0196] The server sends the generated format to the smartphone application. The user can view and review the report on their smartphone in a visually easy-to-understand format (Input: Generated format, Output: Displayed report).

[0197] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0198] The embodiments for implementing the system of the present invention will be described in detail below.

[0199] This system collects customer-related information based on customer names provided by the user, by linking with multiple systems and APIs, and automatically generates the necessary formats and network diagrams. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it can present information in a way that responds to the user's feelings.

[0200] Explanation of the program's processing

[0201] 1. Customer name input and sentiment recognition

[0202] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (for example, "ExampleCorp") into this form and clicks the submit button. Simultaneously with the input, the emotion engine analyzes the user's typing speed, facial expressions, or voice to recognize the user's emotions.

[0203] 2. Data Collection

[0204] The server receives the request sent from the terminal and extracts the entered customer name. Next, it sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems, etc.) and related APIs to collect information about the customer "ExampleCorp".

[0205] Examples of data collection

[0206] The server sends a request to the Customer Relationship Management (CRM) system to retrieve ExampleCorp's transaction history information.

[0207] The server sends a request to the Enterprise Resource Planning (ERP) system to retrieve purchasing information for ExampleCorp.

[0208] The server sends a request to the network management system to retrieve the network configuration information for ExampleCorp.

[0209] Requests are also sent to other related APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[0210] 3. Information Analysis and Format Generation

[0211] The server analyzes the received data and extracts customer-related information (such as transaction history, purchase information, and network configuration information). Next, it generates the necessary format (FMT) based on this information. Furthermore, the server uses the analyzed network information to generate a network configuration diagram. This involves creating a visual diagram using a network configuration diagram generation API.

[0212] 4. Emotion-based expression

[0213] The server retrieves user emotional information recognized through the emotion engine. For example, if the user is feeling anxious or stressed, the server provides information in a more concise and visual format. Conversely, if the user is relaxed, it provides information in a more detailed format, adjusting the displayed content according to the user's state.

[0214] 5. Providing results

[0215] The server returns the generated format (FMT) and network diagram to the terminal. The user can then view the results displayed on the terminal screen. Because the information is provided in a display format that suits the user's emotional state, it is possible to acquire and understand the information more efficiently.

[0216] Specific example

[0217] The user enters the customer name "ExampleCorp" and clicks the submit button. Simultaneously, the emotion engine analyzes the user's typing speed and facial expressions, recognizing that the user is feeling anxious. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. At the same time, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network diagram related to ExampleCorp are generated. The generated information is presented concisely and visually, taking into account the user's anxiety. Finally, the server sends these results to the terminal, and the user confirms them.

[0218] In this way, users can simply enter their customer name into an input form, and information will be automatically collected from many systems, allowing them to easily obtain the necessary formats and network diagrams. Furthermore, the introduction of an emotion engine enables the provision of information tailored to the user's emotions, thereby improving the user experience.

[0219] The following describes the processing flow.

[0220] Step 1:

[0221] The user accesses the input form on their device. The device displays an input screen for entering the customer's name.

[0222] Step 2:

[0223] The user enters a customer name (e.g., "ExampleCorp") into the input form on the device and clicks the submit button. The device then sends the entered customer name to the server.

[0224] Step 3:

[0225] The device activates an emotion engine to recognize the user's emotions based on their input speed, facial expressions, and voice. Analysis is performed during input and after transmission to obtain the user's emotional information.

[0226] Step 4:

[0227] The server receives the request sent from the terminal and extracts the customer name "ExampleCorp" from the request body. The server also stores the user's sentiment information obtained from the sentiment engine.

[0228] Step 5:

[0229] The server sends a request to the Customer Relationship Management (CRM) system. This request includes the customer name "ExampleCorp" and asks to retrieve transaction history information.

[0230] Step 6:

[0231] The server sends a request to the Enterprise Resource Planning (ERP) system. This request includes the customer name "ExampleCorp" and requests the retrieval of purchasing information.

[0232] Step 7:

[0233] The server sends a request to the network management system. This request includes the customer name "ExampleCorp" and requests the retrieval of network configuration information.

[0234] Step 8:

[0235] The server sends requests to other relevant APIs (e.g., customer information API, network configuration API, etc.) to retrieve additional information.

[0236] Step 9:

[0237] The server aggregates the responses received from each system and API. Each response is received in JSON or XML format.

[0238] Step 10:

[0239] The server analyzes the received data and extracts necessary customer-related information (such as transaction history, purchase information, and network configuration information).

[0240] Step 11:

[0241] The server generates a Customer Information Format (FMT) based on the analysis results. For example, it creates a report-style document that combines transaction history and purchase information.

[0242] Step 12:

[0243] The server uses the network diagram generation API to generate the latest network diagram based on the acquired network information.

[0244] Step 13:

[0245] The server retrieves user emotion information recognized through the emotion engine and adjusts the display format accordingly. For example, if the user is feeling anxious or stressed, the information is presented concisely and visually; if they are relaxed, more detailed information is provided.

[0246] Step 14:

[0247] The server sends the generated customer information format (FMT) and network configuration diagram back to the terminal, and adjusts the display based on the user's sentiment.

[0248] Step 15:

[0249] The user confirms the results displayed on the terminal (customer information format and network configuration diagram). Because the terminal presents information in a format that aligns with the user's emotional state, the user can intuitively understand the information.

[0250] Through these steps, users can simply enter their customer name into an input form, and information will be automatically collected from numerous systems, easily obtaining the necessary formats and network diagrams. Furthermore, the emotion engine enables the provision of information tailored to the user's emotions, thereby improving the user experience.

[0251] (Example 2)

[0252] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0253] Conventional systems only retrieve information by inputting the customer's name, failing to provide information tailored to the user's emotions and making it difficult to present optimal information according to the user's state. In particular, users experiencing anxiety or stress require information in a visually easy-to-understand format, but such flexible responses were insufficient.

[0254] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0255] In this invention, the server includes an input means for entering a customer name, a means for receiving a customer name entered through the input means, an emotion engine means for recognizing the user's emotions based on the entered customer name, a means for sending requests to obtain customer-related information from a plurality of external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for adjusting the display method of the format based on the emotions recognized by the emotion engine means, and a means for displaying the generated format.

[0256] This allows for the display format of information to be adjusted according to the user's emotions, enabling the provision of information that is optimal for the user's state.

[0257] "Input means" refers to a device or interface for a user to enter a customer's name.

[0258] "Receiving means" refers to a device or program that has the function of acquiring the customer name entered through the input means and transmitting it to the server.

[0259] An "emotion engine" refers to software or hardware that analyzes the user's input speed, facial expression data, or voice to recognize the user's emotions.

[0260] "Means for sending requests" refers to a device or program that uses protocols such as HTTP requests to communicate with multiple external systems in order to obtain customer-related information.

[0261] "Analysis means" refers to software or hardware for processing data received from an external system and extracting and analyzing necessary information.

[0262] "Means for generating a format" refers to software or hardware used to create a specific format or report based on analyzed information.

[0263] "Means for adjusting the display method of formatting" refers to software or hardware for changing or optimizing the display format of information based on recognized user sentiment.

[0264] "Display means" refers to a screen or device for providing users with information such as generated formats and network configuration diagrams.

[0265] The following describes in detail the embodiments for implementing the system of the present invention. This system collects and analyzes customer-related information based on the customer name provided by the user, in cooperation with multiple systems and APIs, and provides the information in the most optimal format. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to provide information that corresponds to the user's emotions.

[0266] Customer name input and sentiment recognition

[0267] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (e.g., "ExampleCorp") into this form and clicks the submit button. At this time, the emotion engine analyzes the user's input speed, facial expression data (e.g., obtained from a webcam), or voice in real time to recognize the user's emotions. TENSORFLOW®.js is used for emotion recognition and facial expression analysis.

[0268] Data collection

[0269] The server receives requests sent from the terminal, parses the HTTP requests, and extracts the entered customer name. The server uses Node.js and Express.js, among others. Next, it sends requests to multiple external systems and APIs (e.g., CRM systems, ERP systems, network management systems) to collect customer information. The retrieved data is typically received in JSON format.

[0270] Information analysis and format generation

[0271] The server analyzes the received data and extracts customer-related information (transaction history, purchase information, network configuration information, etc.). The Python pandas library is used for this analysis. Next, the necessary formats (such as reports) are generated based on the analyzed information. An Excel report is generated using pandas. Additionally, a network configuration diagram is visually created using the D3.js library.

[0272] Emotion-based display

[0273] The server retrieves user emotion information recognized through the emotion engine. The server adjusts how the information is displayed based on the user's emotions. For example, it provides information to a user who is feeling anxious in a more concise and visual format, while providing information to a relaxed user in a format that includes more detailed information.

[0274] Providing results

[0275] The server returns the generated format (such as an Excel report) and network diagram to the terminal. The terminal displays the received data in its user interface. The user can then review the results and obtain the necessary information.

[0276] Specific example

[0277] The user enters the customer name "ExampleCorp" and clicks the submit button. At this point, the emotion engine analyzes the user's typing speed and facial expressions, recognizing that the user is feeling anxious. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. Simultaneously, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network diagram related to ExampleCorp are generated. The generated information is presented concisely and visually, taking into account the user's anxiety. Finally, the server sends these results to the terminal, and the user confirms them.

[0278] Example of a prompt

[0279] Collect transaction history, purchase information, and network configuration information for a customer named 'ExampleCorp', and generate and display the necessary format and network configuration diagram based on this information. Note that if the user is feeling anxious, the information should be displayed in a concise and visual format.

[0280] Based on the customer name entered by the user, collect necessary information from relevant external systems and APIs, and automatically generate a format and network configuration diagram. Furthermore, implement a process to adjust the display format according to the user's mood.

[0281] This system allows users to automatically collect information from multiple systems and easily obtain necessary formats and network diagrams simply by entering a customer's name into an input form. Furthermore, the introduction of an emotion engine enables the provision of information tailored to the user's emotions, improving the user experience.

[0282] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0283] Step 1:

[0284] On the terminal, an input form for the user to enter the customer name is displayed. As an example, HTML and JavaScript (registered trademark) are used to construct this form. The display of this input form is the input, and the output is that the user enters the customer name on the form and clicks the send button. The user enters "Example Corp".

[0285] Step 2:

[0286] The terminal receives the customer name entered in the input form and sends it to the server as an HTTP request. The input is the customer name "ExampleCorp" entered by the user. As the output, an HTTP request containing that customer name is generated. This HTTP request is sent in JSON format.

[0287] Step 3:

[0288] The server analyzes the HTTP request sent from the terminal and extracts the customer name "ExampleCorp". The reception of this HTTP request is the input, and the extraction of the customer name specified by JSON parsing is the output.

[0289] Step 4:

[0290] The emotion engine means analyzes the user's input speed, facial expression data, or voice data in real time to recognize the user's emotion. Here, TensorFlow.js is used. The input is the user's customer name input process and its data. As the output, the user's emotion information (e.g., anxiety) can be obtained.

[0291] Step 5:

[0292] The server sends requests to multiple external systems (e.g., CRM system, ERP system, network management system) to collect information related to the customer name "ExampleCorp". The input is requests to the external systems. The output is transaction history, purchase information, and network configuration information retrieved from the external systems. This data is returned in JSON format.

[0293] Step 6:

[0294] The server analyzes the received data. For example, it processes the data using the Python pandas library. Customer-related information obtained from an external system is used as input. The output is an organized dataset containing transaction history, purchase information, and network configuration information.

[0295] Step 7:

[0296] The server generates the required format (e.g., an Excel report) based on the analyzed information. It uses the pandas library to generate the Excel file. The input is a well-organized dataset. The output is an Excel report.

[0297] Step 8:

[0298] The server uses the D3.js library to generate network diagrams. Network configuration information is taken as input. A visual network diagram is generated as output.

[0299] Step 9:

[0300] The server adjusts the display method of the format based on the emotion recognized by the emotion engine means. Specifically, when the user is feeling anxious, information is provided in a concise visual form, and when the user is relaxed, detailed information is included. As input, there is the recognized emotion data. As output, a format with the adjusted display method and a network configuration diagram are obtained.

[0301] Step 10:

[0302] The server sends the generated format and network configuration diagram to the terminal. As input, there is the generated report and network configuration diagram. As output, data transmitted as an HTTP response is obtained.

[0303] Step 11:

[0304] The terminal displays the received data on the user's screen. As input, there is the report and network configuration diagram received as an HTTP response. As output, visual information displayed on the user interface is obtained. The user can view this information and obtain the necessary details.

[0305] (Application Example 2)

[0306] Next, Application Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0307] There is a need for a method to effectively manage customer information and manufacturing status in a factory and provide it to employees at appropriate times. In particular, it is important to adjust the information according to the emotional state of employees and present it in an appropriate format. However, conventional systems have had problems such as difficulty in adjusting displays based on emotion recognition and real-time detailed information management. The present invention aims to solve such problems.

[0308] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0309] In this invention, the server includes an input means for entering a customer name, a means for receiving a customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for adjusting the display content based on emotional information recognized through the means, and a means for displaying the generated format. This enables easy real-time information gathering and processing, and further allows for information display tailored to the emotional state of employees.

[0310] A "customer name" is a name used to identify a specific customer.

[0311] An "input method" is a means by which a user enters specific information into a system.

[0312] "Means of receiving" refers to a mechanism for receiving input information.

[0313] "Multiple external systems" refers to different systems that exist externally, and examples include customer relationship management systems, corporate resource planning systems, and network management systems.

[0314] "Means for sending requests" refers to functions or devices used to send requests to external systems in order to obtain desired information.

[0315] "Customer-related information" refers to data such as transaction history, purchase information, and network configuration information related to a specific customer.

[0316] "Means of analysis" refer to devices or programs that analyze received information and convert it into meaningful data.

[0317] "Means for generating a format" refers to devices or programs used to organize analyzed information into a specific format.

[0318] "Emotional information" refers to data that indicates the user's emotional state based on factors such as facial expressions, voice, and input speed.

[0319] "Means for adjusting the displayed content" refers to devices or programs for changing the content and format of the information displayed in accordance with recognized emotional information.

[0320] A system that includes "generated formats" refers to documents or data in a specific format created based on the analyzed information.

[0321] A "network diagram" is a diagram that visually represents the connections and structure of a network.

[0322] This invention relates to a system that collects customer-related information from multiple external systems based on the customer name entered by the user, analyzes and processes that information, and generates the necessary format and network configuration diagram. Furthermore, it can provide an optimal information display method according to the user's emotional state.

[0323] This system is configured as follows:

[0324] 1. Hardware and software configuration

[0325] Hardware: Factory robots (e.g., Pepper, UR5), emotion recognition cameras and microphones (e.g., Microsoft® Azure® Kinect, Intel RealSense)

[0326] Software: Emotion recognition engines (e.g., Affectiva, Microsoft Azure Emotion API), data collection APIs (e.g., Salesforce API, SAP API), network diagram generation APIs (e.g., Lucidchart API, Draw.io API), cloud data analysis engines (e.g., AWS® Lambda, Google® Cloud Functions)

[0327] 2. User Interface

[0328] The terminal displays a form where the user can enter the customer's name. Once the user enters the customer's name and submits it, the emotion recognition camera and microphone analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[0329] 3. Data Collection

[0330] The server receives requests sent from terminals and extracts the entered customer name. It then sends requests to multiple external systems (e.g., customer relationship management systems and corporate resource planning systems) and related APIs to collect customer information. Data collection APIs are used in this collection process.

[0331] 4. Information Analysis and Format Generation

[0332] The server analyzes the received data and extracts customer-related information. Next, it generates the necessary format based on this information. It also creates network diagrams using a network diagram generation API. A cloud data analysis engine assists in this analysis and generation process.

[0333] 5. Emotion-based display adjustments

[0334] The server retrieves the user's emotional information, recognized through the emotion engine, and adjusts the format and content of the information display. For example, when the user is feeling anxious, the information is presented concisely and visually, while when they are relaxed, detailed information is provided.

[0335] 6. Displaying the results

[0336] Finally, the server sends the generated format and network diagram to the terminal for the user to review. Emotion-based adjustments improve the user experience.

[0337] For example, if a factory worker enters the customer name "XYZCorp" and a sense of urgency is detected, the server retrieves transaction history from the customer relationship management system and extracts purchasing information from the corporate resource planning system. By providing this information in a concise format and visually displaying a network diagram, workers can quickly obtain the information they need.

[0338] An example of a prompt message for a generative AI model is as follows:

[0339] "Customer Name: XYZCorp, Emotion: Impatient, Required Information: Manufacturing progress, quality control data, factory layout diagram:"

[0340] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0341] Step 1:

[0342] The device displays a form where the user can enter the customer's name. The user enters the customer's name into this form and clicks the submit button. Simultaneously with the input, the emotion recognition camera and microphone collect the user's facial expressions and voice, and send them to the emotion engine.

[0343] Input: Customer name, user's facial expression, voice

[0344] Output: User-entered customer name, collected sentiment data

[0345] Step 2:

[0346] The server receives the request sent from the terminal and extracts the entered customer name (e.g., XYZCorp). Next, the emotion engine analyzes the collected data and recognizes the user's emotion (e.g., anxiety).

[0347] Input: Request from the device, customer name, sentiment data

[0348] Output: Recognized emotion information

[0349] Step 3:

[0350] The server sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems) and associated APIs to collect customer information.

[0351] Input: Customer name, API endpoint of the external system

[0352] Output: Customer-related information obtained from each external system

[0353] Step 4:

[0354] The server analyzes the received customer-related information and extracts the necessary data (e.g., transaction history, purchase information). Next, it generates a format based on this data.

[0355] Input: Customer-related information from external systems

[0356] Output: Analyzed data, generated format

[0357] Step 5:

[0358] The server uses a network diagram generation API to generate a network diagram based on the analyzed data.

[0359] Input: Analyzed data

[0360] Output: Network Configuration Diagram

[0361] Step 6:

[0362] The server adjusts the information displayed to the user based on the recognized emotional information. For example, if it detects anxiety, it provides information in a concise and visual format. On the other hand, if the user is relaxed, it provides detailed information.

[0363] Input: Recognized emotion information, generated format, network diagram

[0364] Output: Adjusted information display content

[0365] Step 7:

[0366] The server sends the generated format and network configuration diagram to the terminal for the user to review. The user can then take appropriate action based on the displayed information.

[0367] Input: Adjusted information display content

[0368] Output: Information displayed on the terminal

[0369] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0370] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0371] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0372] [Second Embodiment]

[0373] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0374] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0375] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0376] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0377] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0378] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0379] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0380] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0381] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0382] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0383] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0384] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0385] The embodiments for implementing the system of the present invention will be described in detail below.

[0386] This system collects customer-related information based on customer names provided by the user, in conjunction with multiple systems and APIs, and automatically generates the necessary formats and network configuration diagrams.

[0387] Explanation of the program's processing

[0388] 1. Enter the customer's name.

[0389] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (for example, "ExampleCorp") into this input form and clicks the submit button.

[0390] 2. Data Collection

[0391] The server receives the request sent from the terminal and extracts the entered customer name. Next, it sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems, etc.) and related APIs to collect information about the customer "ExampleCorp".

[0392] Examples of data collection

[0393] The server sends a request to the Customer Relationship Management (CRM) system to retrieve ExampleCorp's transaction history information.

[0394] The server sends a request to the Enterprise Resource Planning (ERP) system to retrieve purchasing information for ExampleCorp.

[0395] The server sends a request to the network management system to retrieve the network configuration information for ExampleCorp.

[0396] Requests are also sent to other related APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[0397] 3. Information Analysis and Format Generation

[0398] The server analyzes the received data and extracts customer-related information (such as transaction history, purchase information, and network configuration information). Next, it generates the necessary format (FMT) based on this information.

[0399] Furthermore, the server uses the analyzed network information to generate a network configuration diagram. This involves creating a visual diagram using a network configuration diagram generation API.

[0400] 4. Providing the results

[0401] The server returns the generated format (FMT) and network diagram to the terminal. The user can then view the results displayed on the terminal screen.

[0402] Specific example

[0403] The user enters the customer name "ExampleCorp" and clicks the submit button. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. Simultaneously, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network configuration diagram for ExampleCorp are generated. Finally, the server sends these results to the terminal, and the user confirms the results.

[0404] In this way, users can easily obtain the necessary information and proceed with their work efficiently simply by entering the customer's name into the input form. This system automates many manual tasks, significantly reducing time and effort.

[0405] The following describes the processing flow.

[0406] Step 1:

[0407] The user accesses the input form on their device. The device displays an input screen for entering the customer's name.

[0408] Step 2:

[0409] The user enters a customer name (e.g., "ExampleCorp") into the input form on the device and clicks the submit button. The device then sends the entered customer name to the server.

[0410] Step 3:

[0411] The server receives the request sent from the terminal and extracts the customer name "ExampleCorp" from the request body.

[0412] Step 4:

[0413] The server sends a request to the Customer Relationship Management (CRM) system. This request includes the customer name "ExampleCorp" and asks to retrieve transaction history information.

[0414] Step 5:

[0415] The server sends a request to the Enterprise Resource Planning (ERP) system. This request includes the customer name "ExampleCorp" and requests the retrieval of purchasing information.

[0416] Step 6:

[0417] The server sends a request to the network management system. This request includes the customer name "ExampleCorp" and requests the retrieval of network configuration information.

[0418] Step 7:

[0419] The server sends requests to other relevant APIs (e.g., customer information API, network configuration API, etc.) to retrieve additional information.

[0420] Step 8:

[0421] The server aggregates the responses received from each system and API. Each response is received in JSON or XML format.

[0422] Step 9:

[0423] The server analyzes the received data and extracts necessary customer-related information (such as transaction history, purchase information, and network configuration information).

[0424] Step 10:

[0425] The server generates a Customer Information Format (FMT) based on the analysis results. For example, it creates a report-style document that combines transaction history and purchase information.

[0426] Step 11:

[0427] The server uses the network diagram generation API to generate the latest network diagram based on the acquired network information.

[0428] Step 12:

[0429] The server combines the generated customer information format (FMT) and network configuration diagram and sends them to the terminal.

[0430] Step 13:

[0431] The user confirms the results displayed on their terminal (customer information format and network configuration diagram). This allows the user to easily and quickly obtain the necessary information.

[0432] Through these steps, users can simply enter a customer's name into an input form, and information will be automatically collected from numerous systems, allowing them to easily obtain the necessary formats and network diagrams.

[0433] (Example 1)

[0434] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0435] Traditional data collection and analysis systems often involved manual data collection, which was time-consuming and labor-intensive. Furthermore, integrating information from multiple different systems, efficiently analyzing it, and generating visual network diagrams was not easy. This resulted in decreased operational efficiency and hindered rapid decision-making.

[0436] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0437] In this invention, the server includes an input means for entering a customer name, a means for receiving the customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for generating a network configuration diagram based on the format, and a means for displaying the generated format and network configuration diagram. This automates a series of processes, from entering a customer name to automatic information collection, analysis, format generation, and network configuration diagram generation and display, enabling increased operational efficiency and faster decision-making.

[0438] "Input method for entering customer names" refers to the interface used by users to enter customer names into an information processing terminal.

[0439] "Means for receiving customer names entered through the input means" refers to a component or mechanism for receiving customer names transmitted through the input means.

[0440] "Means of sending requests to obtain customer-related information from multiple external systems" refers to a function or process for sending requests to multiple different systems for information retrieval or data collection.

[0441] "Means for analyzing customer-related information received from the external system" refers to algorithms or processing mechanisms for processing data received from the external system and extracting useful information.

[0442] "Means for generating a format based on the analyzed information" refers to a function for creating a predetermined format or report format based on the information obtained through analysis.

[0443] "Means for generating a network configuration diagram based on the aforementioned format" refers to a function for visually illustrating the network configuration and topology based on the generated format information.

[0444] "Means for displaying the generated format and network diagram" refers to an interface or device for displaying the created format and network diagram in a way that is visible to the user.

[0445] A "customer relationship management system" refers to a system for managing relationships with customers and centrally managing customer information, transaction history, and other related data.

[0446] A "corporate resource planning system" is a system for efficiently managing a company's resources, and it refers to a system that comprehensively manages business processes such as purchasing, inventory, and manufacturing.

[0447] A "network management system" refers to a system that manages the configuration, status, and performance of a network, and aims to optimize the network.

[0448] An "information processing terminal" refers to a device such as a computer or mobile device that a user uses to interact with a system.

[0449] This invention relates to an information processing system that automatically collects and analyzes customer-related information in cooperation with multiple external systems and APIs based on customer names provided by users, and generates necessary formats and network configuration diagrams. The embodiments for carrying out this invention will be described in detail below.

[0450] Users can enter customer names using an input form displayed on their device. For example, a user might enter "ExampleCorp" as a customer name and click the submit button. The device then sends this input to the server.

[0451] The server receives a request from the terminal and extracts the entered customer name. Next, the server sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems) to collect information about the customer "ExampleCorp". It also sends requests to relevant APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[0452] Specifically, the following requests are sent to the external system:

[0453] A request is sent to the customer relationship management (CRM) system saying, "Please provide transaction history information."

[0454] A request is sent to the Enterprise Resource Planning (ERP) system saying, "Please provide purchasing information."

[0455] A request is sent to the network management system asking for "network configuration information."

[0456] The server analyzes the data received as a response to these requests. It integrates and analyzes the received customer-related information, extracting transaction history, purchase information, and network configuration information. Based on this information, it generates the necessary format.

[0457] Based on the generated format, the server further generates a network diagram. To generate the network diagram, the network diagram generation API is used. Specifically, the acquired network data is analyzed and the network diagram generation API is called to visually represent the network topology.

[0458] Finally, the server sends the generated format and network diagram to the terminal. The user can then view the results on the terminal screen. This allows users to easily obtain the necessary information and significantly improve work efficiency.

[0459] Example of a prompt

[0460] The following are examples of prompts to input into a generative AI model:

[0461] "This system collects customer-related information based on the customer name provided by the user, by integrating with multiple systems and APIs, and automatically generates the necessary formats and network diagrams. Specifically, when a user enters the customer name "ExampleCorp" into the input form and clicks the submit button, the server collects information from the CRM system, ERP system, network management system, and other related APIs, analyzes it, and generates the formats and network diagrams. These are then sent back to the terminal, where the user can review the results."

[0462] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0463] Step 1:

[0464] The user enters the customer name into the input form displayed on the terminal and clicks the submit button. The system receives the customer name entered by the user (e.g., "ExampleCorp") as input. This entered customer name is sent to the system.

[0465] Step 2:

[0466] The terminal sends the customer name "ExampleCorp" entered by the user to the server. The server receives the customer name sent from the terminal as input. The server extracts the customer name and stores it for use in the next step.

[0467] Step 3:

[0468] The server sends information retrieval requests to multiple external systems based on the entered customer name "ExampleCorp". Specifically, it sends the following requests to external systems:

[0469] Send a request to the CRM system to retrieve transaction history information.

[0470] A request is sent to the ERP system to retrieve purchasing information.

[0471] Send a request to the network management system to retrieve network configuration information.

[0472] The input is the customer's name, and the output is a process that sends requests to the respective systems.

[0473] Step 4:

[0474] The server receives responses to requests from external systems. Specifically, it receives the following information:

[0475] Receive transaction history information from the CRM system.

[0476] Receive purchasing information from the ERP system.

[0477] Receive network configuration information from the network management system.

[0478] The input is a response from an external system, and the output is a dataset of customer-related information.

[0479] Step 5:

[0480] The server analyzes the acquired customer-related information. Specifically, it performs the following processes:

[0481] We analyze transaction history information and extract useful data.

[0482] Analyze purchase information and extract the necessary data.

[0483] Analyze network configuration information to understand the network topology.

[0484] The system takes customer-related information obtained from an external system as input, performs data processing and calculations, and outputs analyzed information.

[0485] Step 6:

[0486] The server generates the necessary format based on the parsed information. Specifically, it performs the following processes:

[0487] Integrate transaction history information and purchase information, and create a report format.

[0488] It takes parsed information as input and generates formatted data as output.

[0489] Step 7:

[0490] The server generates a network configuration diagram based on the generated format. Specifically, it performs the following steps:

[0491] The network diagram generation API is called to visually create a network diagram.

[0492] It takes analyzed network configuration information as input and outputs a network configuration diagram.

[0493] Step 8:

[0494] The server sends the generated format data and network diagram to the terminal. It takes the generated format data and network diagram as input and sends this data to the terminal as output.

[0495] Step 9:

[0496] The terminal displays formatted data and a network diagram received from the server to the user. The user can check the results displayed on the terminal screen and obtain the necessary information. It takes data received from the server as input and provides information in a format that the user can easily understand as output.

[0497] (Application Example 1)

[0498] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0499] Conventional security information gathering systems required the individual collection and manual analysis of information from multiple external systems, which was extremely time-consuming and laborious. Furthermore, in situations demanding immediate response based on security incidents and network configurations, rapid information gathering and analysis are essential, but conventional systems struggled to provide adequate responses. Therefore, there is a need for a system that automatically and rapidly collects, analyzes, and visually displays security-related information.

[0500] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0501] In this invention, the server includes an input means for entering a customer name, a means for receiving the customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for displaying the generated format, a means for collecting and analyzing security-related information from external systems, and a means for generating the analyzed security-related information. As a result, security personnel can quickly collect and analyze security incident information and network configuration diagrams from multiple external systems and visually confirm them simply by entering a customer name into an input form.

[0502] "Customer name" refers to the name of the target company or organization entered in order to collect information from an external system.

[0503] An "input method" refers to a device or interface used by a user to input text or strings of characters.

[0504] "Means of receiving" refers to the function by which a server receives data and information transmitted through input means.

[0505] "Means of sending requests" refers to communication functions that allow a server to request information from an external system.

[0506] "Means of analysis" refers to software and algorithms used to process received information, extract, manipulate, and analyze necessary data.

[0507] A "means for generating formats" refers to a function that creates documents and charts based on analyzed data, arranged in a specific format and visual layout.

[0508] "Means of display" refers to devices or interfaces used to display the generated format in a way that is viewable by the user.

[0509] "Security-related information" refers to data concerning the security of a company or organization, including incident information, network configuration, and threat information.

[0510] "External systems" refer to all systems that work in conjunction with servers to provide information, such as security information management systems, customer relationship management systems, corporate resource planning systems, and network management systems.

[0511] A "security configuration diagram" is a diagram that visually shows the arrangement of a company's or organization's network and security equipment.

[0512] A "security information management system" is a system that manages various security-related data, such as incident information, threat status, and alert information.

[0513] The following describes a specific embodiment for carrying out this invention. The system described below is for collecting and analyzing security-related information from an external system based on the customer's name and displaying it visually. This system mainly consists of a server, a smartphone, and an external system.

[0514] 1. Enter the customer's name.

[0515] The user enters the customer name on the smartphone application. After entering the customer name in the input form, they click the submit button. This sends the customer name (e.g., "SecurityCorp") to the server.

[0516] 2. Data Collection

[0517] The server sends information gathering requests to external systems based on the received customer name. These external systems include customer relationship management systems, corporate resource planning systems, network management systems, and security information management systems. For example, the server may obtain security incident information and network configuration information from SIEM (Security Information and Event Management) systems, firewall management systems, and intrusion detection systems.

[0518] 3. Information Analysis and Format Generation

[0519] The server analyzes the collected information and generates security incident reports and network diagrams. This analysis utilizes programming languages ​​such as Python and PDF generation libraries such as ReportLab. The analyzed information is then converted into a visually easy-to-understand format.

[0520] 4. Providing the results

[0521] The generated format and network configuration diagram are displayed on a smartphone application. By reviewing this, users can quickly grasp information about security incidents and network configurations and take appropriate action.

[0522] Hardware and software to be used

[0523] Hardware: Linux server, smartphone

[0524] Software: Python (requests library, ReportLab), external systems (SIEM, firewall management system, intrusion detection system)

[0525] Specific example

[0526] For example, a security officer enters the customer name "SecurityCorp" and clicks the submit button. The server collects security incident information from the security information management system and network security configuration information from the firewall management system. This information is analyzed, a visually understandable PDF report is generated, and displayed on the smartphone application.

[0527] Examples of prompts for generative AI models

[0528] Please enter the customer name (e.g., "SecurityCorp"). Based on this input, we will automatically generate the latest security incident information, network security configuration diagrams, and security reports.

[0529] As described above, this system allows users to quickly collect, analyze, and visually display security-related information from multiple external systems simply by entering a customer's name. This enables security personnel to respond quickly and appropriately even in situations requiring immediate action.

[0530] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0531] Step 1:

[0532] The user enters the customer name on the smartphone application. They enter the customer name in the input form and click the submit button. The entered data (e.g., "SecurityCorp") is sent to the server.

[0533] Step 2:

[0534] The server receives requests sent by users and extracts the entered customer name. Based on this customer name, it generates data for requests to external systems (input: customer name "SecurityCorp", output: request data to each external system).

[0535] Step 3:

[0536] The server uses the generated request data to send information gathering requests to multiple external systems. These external systems include customer relationship management systems, corporate resource planning systems, network management systems, and security information management systems (input: request data, output: information from each system).

[0537] Step 4:

[0538] The external system receives requests from the server and returns information about the relevant customer. This includes transaction history information from the customer relationship management system, purchasing information from the corporate resource planning system, network configuration information from the network management system, and security incident information from the security information management system (input: request, output: customer-related information).

[0539] Step 5:

[0540] The server analyzes customer-related information received from external systems. This analysis process uses programming languages ​​such as Python and specific analysis algorithms to convert the received data into a formattable form (input: information from each system, output: analyzed data).

[0541] Step 6:

[0542] The server generates a visually easy-to-understand format based on the analyzed data. Specifically, it uses PDF generation libraries such as ReportLab to create reports that include security incident information and network configuration diagrams (input: analyzed data, output: generated format).

[0543] Step 7:

[0544] The server sends the generated format to the smartphone application. The user can view and review the report on their smartphone in a visually easy-to-understand format (Input: Generated format, Output: Displayed report).

[0545] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0546] The embodiments for implementing the system of the present invention will be described in detail below.

[0547] This system collects customer-related information based on customer names provided by the user, by linking with multiple systems and APIs, and automatically generates the necessary formats and network diagrams. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it can present information in a way that responds to the user's feelings.

[0548] Explanation of the program's processing

[0549] 1. Customer name input and sentiment recognition

[0550] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (for example, "ExampleCorp") into this form and clicks the submit button. Simultaneously with the input, the emotion engine analyzes the user's typing speed, facial expressions, or voice to recognize the user's emotions.

[0551] 2. Data Collection

[0552] The server receives the request sent from the terminal and extracts the entered customer name. Next, it sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems, etc.) and related APIs to collect information about the customer "ExampleCorp".

[0553] Examples of data collection

[0554] The server sends a request to the Customer Relationship Management (CRM) system to retrieve ExampleCorp's transaction history information.

[0555] The server sends a request to the Enterprise Resource Planning (ERP) system to retrieve purchasing information for ExampleCorp.

[0556] The server sends a request to the network management system to retrieve the network configuration information for ExampleCorp.

[0557] Requests are also sent to other related APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[0558] 3. Information Analysis and Format Generation

[0559] The server analyzes the received data and extracts customer-related information (such as transaction history, purchase information, and network configuration information). Next, it generates the necessary format (FMT) based on this information. Furthermore, the server uses the analyzed network information to generate a network configuration diagram. This involves creating a visual diagram using a network configuration diagram generation API.

[0560] 4. Emotion-based expression

[0561] The server retrieves user emotional information recognized through the emotion engine. For example, if the user is feeling anxious or stressed, the server provides information in a more concise and visual format. Conversely, if the user is relaxed, it provides information in a more detailed format, adjusting the displayed content according to the user's state.

[0562] 5. Providing results

[0563] The server returns the generated format (FMT) and network diagram to the terminal. The user can then view the results displayed on the terminal screen. Because the information is provided in a display format that suits the user's emotional state, it is possible to acquire and understand the information more efficiently.

[0564] Specific example

[0565] The user enters the customer name "ExampleCorp" and clicks the submit button. Simultaneously, the emotion engine analyzes the user's typing speed and facial expressions, recognizing that the user is feeling anxious. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. At the same time, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network diagram related to ExampleCorp are generated. The generated information is presented concisely and visually, taking into account the user's anxiety. Finally, the server sends these results to the terminal, and the user confirms them.

[0566] In this way, users can simply enter their customer name into an input form, and information will be automatically collected from many systems, allowing them to easily obtain the necessary formats and network diagrams. Furthermore, the introduction of an emotion engine enables the provision of information tailored to the user's emotions, thereby improving the user experience.

[0567] The following describes the processing flow.

[0568] Step 1:

[0569] The user accesses the input form on their device. The device displays an input screen for entering the customer's name.

[0570] Step 2:

[0571] The user enters a customer name (e.g., "ExampleCorp") into the input form on the device and clicks the submit button. The device then sends the entered customer name to the server.

[0572] Step 3:

[0573] The device activates an emotion engine to recognize the user's emotions based on their input speed, facial expressions, and voice. Analysis is performed during input and after transmission to obtain the user's emotional information.

[0574] Step 4:

[0575] The server receives the request sent from the terminal and extracts the customer name "ExampleCorp" from the request body. The server also stores the user's sentiment information obtained from the sentiment engine.

[0576] Step 5:

[0577] The server sends a request to the Customer Relationship Management (CRM) system. This request includes the customer name "ExampleCorp" and asks to retrieve transaction history information.

[0578] Step 6:

[0579] The server sends a request to the Enterprise Resource Planning (ERP) system. This request includes the customer name "ExampleCorp" and requests the retrieval of purchasing information.

[0580] Step 7:

[0581] The server sends a request to the network management system. This request includes the customer name "ExampleCorp" and requests the retrieval of network configuration information.

[0582] Step 8:

[0583] The server sends requests to other relevant APIs (e.g., customer information API, network configuration API, etc.) to retrieve additional information.

[0584] Step 9:

[0585] The server aggregates the responses received from each system and API. Each response is received in JSON or XML format.

[0586] Step 10:

[0587] The server analyzes the received data and extracts necessary customer-related information (such as transaction history, purchase information, and network configuration information).

[0588] Step 11:

[0589] The server generates a Customer Information Format (FMT) based on the analysis results. For example, it creates a report-style document that combines transaction history and purchase information.

[0590] Step 12:

[0591] The server uses the network diagram generation API to generate the latest network diagram based on the acquired network information.

[0592] Step 13:

[0593] The server retrieves user emotion information recognized through the emotion engine and adjusts the display format accordingly. For example, if the user is feeling anxious or stressed, the information is presented concisely and visually; if they are relaxed, more detailed information is provided.

[0594] Step 14:

[0595] The server sends the generated customer information format (FMT) and network configuration diagram back to the terminal, and adjusts the display based on the user's sentiment.

[0596] Step 15:

[0597] The user confirms the results displayed on the terminal (customer information format and network configuration diagram). Because the terminal presents information in a format that aligns with the user's emotional state, the user can intuitively understand the information.

[0598] Through these steps, users can simply enter their customer name into an input form, and information will be automatically collected from numerous systems, easily obtaining the necessary formats and network diagrams. Furthermore, the emotion engine enables the provision of information tailored to the user's emotions, thereby improving the user experience.

[0599] (Example 2)

[0600] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0601] Conventional systems only retrieve information by inputting the customer's name, failing to provide information tailored to the user's emotions and making it difficult to present optimal information according to the user's state. In particular, users experiencing anxiety or stress require information in a visually easy-to-understand format, but such flexible responses were insufficient.

[0602] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0603] In this invention, the server includes an input means for entering a customer name, a means for receiving a customer name entered through the input means, an emotion engine means for recognizing the user's emotions based on the entered customer name, a means for sending requests to obtain customer-related information from a plurality of external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for adjusting the display method of the format based on the emotions recognized by the emotion engine means, and a means for displaying the generated format.

[0604] This allows for the display format of information to be adjusted according to the user's emotions, enabling the provision of information that is optimal for the user's state.

[0605] "Input means" refers to a device or interface for a user to enter a customer's name.

[0606] "Receiving means" refers to a device or program that has the function of acquiring the customer name entered through the input means and transmitting it to the server.

[0607] An "emotion engine" refers to software or hardware that analyzes the user's input speed, facial expression data, or voice to recognize the user's emotions.

[0608] "Means for sending requests" refers to a device or program that uses protocols such as HTTP requests to communicate with multiple external systems in order to obtain customer-related information.

[0609] "Analysis means" refers to software or hardware for processing data received from an external system and extracting and analyzing necessary information.

[0610] "Means for generating a format" refers to software or hardware used to create a specific format or report based on analyzed information.

[0611] "Means for adjusting the display method of formatting" refers to software or hardware for changing or optimizing the display format of information based on recognized user sentiment.

[0612] "Display means" refers to a screen or device for providing users with information such as generated formats and network configuration diagrams.

[0613] The following describes in detail the embodiments for implementing the system of the present invention. This system collects and analyzes customer-related information based on the customer name provided by the user, in cooperation with multiple systems and APIs, and provides the information in the most optimal format. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to provide information that corresponds to the user's emotions.

[0614] Customer name input and sentiment recognition

[0615] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (e.g., "ExampleCorp") into this form and clicks the submit button. At this time, the emotion engine analyzes the user's input speed, facial expression data (e.g., obtained from a webcam), or voice in real time to recognize the user's emotions. TensorFlow.js is used for emotion recognition and facial expression analysis.

[0616] Data collection

[0617] The server receives requests sent from the terminal, parses the HTTP requests, and extracts the entered customer name. The server uses Node.js and Express.js, among others. Next, it sends requests to multiple external systems and APIs (e.g., CRM systems, ERP systems, network management systems) to collect customer information. The retrieved data is typically received in JSON format.

[0618] Information analysis and format generation

[0619] The server analyzes the received data and extracts customer-related information (transaction history, purchase information, network configuration information, etc.). The Python pandas library is used for this analysis. Next, the necessary formats (such as reports) are generated based on the analyzed information. An Excel report is generated using pandas. Additionally, a network configuration diagram is visually created using the D3.js library.

[0620] Emotion-based display

[0621] The server retrieves user emotion information recognized through the emotion engine. The server adjusts how the information is displayed based on the user's emotions. For example, it provides information to a user who is feeling anxious in a more concise and visual format, while providing information to a relaxed user in a format that includes more detailed information.

[0622] Providing results

[0623] The server returns the generated format (such as an Excel report) and network diagram to the terminal. The terminal displays the received data in its user interface. The user can then review the results and obtain the necessary information.

[0624] Specific example

[0625] The user enters the customer name "ExampleCorp" and clicks the submit button. At this point, the emotion engine analyzes the user's typing speed and facial expressions, recognizing that the user is feeling anxious. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. Simultaneously, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network diagram related to ExampleCorp are generated. The generated information is presented concisely and visually, taking into account the user's anxiety. Finally, the server sends these results to the terminal, and the user confirms them.

[0626] Example of a prompt

[0627] Collect transaction history, purchase information, and network configuration information for a customer named 'ExampleCorp', and generate and display the necessary format and network configuration diagram based on this information. Note that if the user is feeling anxious, the information should be displayed in a concise and visual format.

[0628] Based on the customer name entered by the user, collect necessary information from relevant external systems and APIs, and automatically generate a format and network configuration diagram. Furthermore, implement a process to adjust the display format according to the user's mood.

[0629] This system allows users to automatically collect information from multiple systems and easily obtain necessary formats and network diagrams simply by entering a customer's name into an input form. Furthermore, the introduction of an emotion engine enables the provision of information tailored to the user's emotions, improving the user experience.

[0630] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0631] Step 1:

[0632] The terminal displays an input form for the user to enter a customer name. As an example, this form is constructed using HTML and JavaScript. The display of this input form is the input, and the output is the user entering a customer name on the form and clicking the submit button. The user enters "Example Corp".

[0633] Step 2:

[0634] The terminal receives the customer name entered in the input form and sends it to the server as an HTTP request. The input is the customer name "ExampleCorp" entered by the user. The output is an HTTP request containing that customer name. This HTTP request is sent in JSON format.

[0635] Step 3:

[0636] The server parses the HTTP request sent from the terminal and extracts the customer name "ExampleCorp". The receipt of this HTTP request is the input, and the extraction of the specified customer name through JSON parsing is the output.

[0637] Step 4:

[0638] The emotion engine analyzes user input speed, facial expression data, or voice data in real time to recognize the user's emotions. TensorFlow.js is used here. The input is the user's customer name input process and its data. The output is user emotion information (e.g., anxiety).

[0639] Step 5:

[0640] The server sends requests to multiple external systems (e.g., CRM system, ERP system, network management system) to collect information related to the customer name "ExampleCorp". The input is requests to the external systems. The output is transaction history, purchase information, and network configuration information retrieved from the external systems. This data is returned in JSON format.

[0641] Step 6:

[0642] The server analyzes the received data. For example, it processes the data using the Python pandas library. Customer-related information obtained from an external system is used as input. The output is an organized dataset containing transaction history, purchase information, and network configuration information.

[0643] Step 7:

[0644] The server generates the required format (e.g., an Excel report) based on the analyzed information. It uses the pandas library to generate the Excel file. The input is a well-organized dataset. The output is an Excel report.

[0645] Step 8:

[0646] The server uses the D3.js library to generate network diagrams. Network configuration information is taken as input. A visual network diagram is generated as output.

[0647] Step 9:

[0648] The server adjusts the display format based on the emotions recognized by the emotion engine. Specifically, if the user is feeling anxious, the information is presented in a concise, visual format; if they are relaxed, detailed information is included. The input is recognized emotion data. The output is a format with the adjusted display method and a network diagram.

[0649] Step 10:

[0650] The server sends the generated format and network diagram to the terminal. The inputs are the generated report and network diagram. The output is the data that is sent as an HTTP response.

[0651] Step 11:

[0652] The terminal displays the received data on the user's screen. Inputs include reports and network diagrams received as HTTP responses. Outputs are visual information displayed on the user interface. The user can review this information and obtain the necessary details.

[0653] (Application Example 2)

[0654] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0655] There is a need for effective management of customer information and manufacturing status in factories, and for providing this information to employees at the appropriate time. In particular, it is important to adjust the information according to the emotional state of employees and present it in an appropriate format. However, conventional systems have problems with adjusting displays based on emotion recognition and managing detailed information in real time. This invention aims to solve these problems.

[0656] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0657] In this invention, the server includes an input means for entering a customer name, a means for receiving a customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for adjusting the display content based on emotional information recognized through the means, and a means for displaying the generated format. This enables easy real-time information gathering and processing, and further allows for information display tailored to the emotional state of employees.

[0658] A "customer name" is a name used to identify a specific customer.

[0659] An "input method" is a means by which a user enters specific information into a system.

[0660] "Means of receiving" refers to a mechanism for receiving input information.

[0661] "Multiple external systems" refers to different systems that exist externally, and examples include customer relationship management systems, corporate resource planning systems, and network management systems.

[0662] "Means for sending requests" refers to functions or devices used to send requests to external systems in order to obtain desired information.

[0663] "Customer-related information" refers to data such as transaction history, purchase information, and network configuration information related to a specific customer.

[0664] "Means of analysis" refer to devices or programs that analyze received information and convert it into meaningful data.

[0665] "Means for generating a format" refers to devices or programs used to organize analyzed information into a specific format.

[0666] "Emotional information" refers to data that indicates the user's emotional state based on factors such as facial expressions, voice, and input speed.

[0667] "Means for adjusting the displayed content" refers to devices or programs for changing the content and format of the information displayed in accordance with recognized emotional information.

[0668] A system that includes "generated formats" refers to documents or data in a specific format created based on the analyzed information.

[0669] A "network diagram" is a diagram that visually represents the connections and structure of a network.

[0670] This invention relates to a system that collects customer-related information from multiple external systems based on the customer name entered by the user, analyzes and processes that information, and generates the necessary format and network configuration diagram. Furthermore, it can provide an optimal information display method according to the user's emotional state.

[0671] This system is configured as follows:

[0672] 1. Hardware and software configuration

[0673] Hardware: Factory robots (e.g., Pepper, UR5), emotion recognition cameras and microphones (e.g., Microsoft Azure Kinect, Intel RealSense)

[0674] Software: Emotion recognition engines (e.g., Affectiva, Microsoft Azure Emotion API), data collection APIs (e.g., Salesforce API, SAP API), network diagram generation APIs (e.g., Lucidchart API, Draw.io API), cloud data analysis engines (e.g., AWS Lambda, Google Cloud Functions)

[0675] 2. User Interface

[0676] The terminal displays a form where the user can enter the customer's name. Once the user enters the customer's name and submits it, the emotion recognition camera and microphone analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[0677] 3. Data Collection

[0678] The server receives requests sent from terminals and extracts the entered customer name. It then sends requests to multiple external systems (e.g., customer relationship management systems and corporate resource planning systems) and related APIs to collect customer information. Data collection APIs are used in this collection process.

[0679] 4. Information Analysis and Format Generation

[0680] The server analyzes the received data and extracts customer-related information. Next, it generates the necessary format based on this information. It also creates network diagrams using a network diagram generation API. A cloud data analysis engine assists in this analysis and generation process.

[0681] 5. Emotion-based display adjustments

[0682] The server retrieves the user's emotional information, recognized through the emotion engine, and adjusts the format and content of the information display. For example, when the user is feeling anxious, the information is presented concisely and visually, while when they are relaxed, detailed information is provided.

[0683] 6. Displaying the results

[0684] Finally, the server sends the generated format and network diagram to the terminal for the user to review. Emotion-based adjustments improve the user experience.

[0685] For example, if a factory worker enters the customer name "XYZCorp" and a sense of urgency is detected, the server retrieves transaction history from the customer relationship management system and extracts purchasing information from the corporate resource planning system. By providing this information in a concise format and visually displaying a network diagram, workers can quickly obtain the information they need.

[0686] An example of a prompt message for a generative AI model is as follows:

[0687] "Customer Name: XYZCorp, Emotion: Impatient, Required Information: Manufacturing progress, quality control data, factory layout diagram:"

[0688] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0689] Step 1:

[0690] The device displays a form where the user can enter the customer's name. The user enters the customer's name into this form and clicks the submit button. Simultaneously with the input, the emotion recognition camera and microphone collect the user's facial expressions and voice, and send them to the emotion engine.

[0691] Input: Customer name, user's facial expression, voice

[0692] Output: User-entered customer name, collected sentiment data

[0693] Step 2:

[0694] The server receives the request sent from the terminal and extracts the entered customer name (e.g., XYZCorp). Next, the emotion engine analyzes the collected data and recognizes the user's emotion (e.g., anxiety).

[0695] Input: Request from the device, customer name, sentiment data

[0696] Output: Recognized emotion information

[0697] Step 3:

[0698] The server sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems) and associated APIs to collect customer information.

[0699] Input: Customer name, API endpoint of the external system

[0700] Output: Customer-related information obtained from each external system

[0701] Step 4:

[0702] The server analyzes the received customer-related information and extracts the necessary data (e.g., transaction history, purchase information). Next, it generates a format based on this data.

[0703] Input: Customer-related information from external systems

[0704] Output: Analyzed data, generated format

[0705] Step 5:

[0706] The server uses a network diagram generation API to generate a network diagram based on the analyzed data.

[0707] Input: Analyzed data

[0708] Output: Network Configuration Diagram

[0709] Step 6:

[0710] The server adjusts the information displayed to the user based on the recognized emotional information. For example, if it detects anxiety, it provides information in a concise and visual format. On the other hand, if the user is relaxed, it provides detailed information.

[0711] Input: Recognized emotion information, generated format, network diagram

[0712] Output: Adjusted information display content

[0713] Step 7:

[0714] The server sends the generated format and network configuration diagram to the terminal for the user to review. The user can then take appropriate action based on the displayed information.

[0715] Input: Adjusted information display content

[0716] Output: Information displayed on the terminal

[0717] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0718] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0719] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0720] [Third Embodiment]

[0721] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0722] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0723] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0724] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0725] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0726] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0727] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0728] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0729] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0730] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0731] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0732] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0733] The embodiments for implementing the system of the present invention will be described in detail below.

[0734] This system collects customer-related information based on customer names provided by the user, in conjunction with multiple systems and APIs, and automatically generates the necessary formats and network configuration diagrams.

[0735] Explanation of the program's processing

[0736] 1. Enter the customer's name.

[0737] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (for example, "ExampleCorp") into this input form and clicks the submit button.

[0738] 2. Data Collection

[0739] The server receives the request sent from the terminal and extracts the entered customer name. Next, it sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems, etc.) and related APIs to collect information about the customer "ExampleCorp".

[0740] Examples of data collection

[0741] The server sends a request to the Customer Relationship Management (CRM) system to retrieve ExampleCorp's transaction history information.

[0742] The server sends a request to the Enterprise Resource Planning (ERP) system to retrieve purchasing information for ExampleCorp.

[0743] The server sends a request to the network management system to retrieve the network configuration information for ExampleCorp.

[0744] Requests are also sent to other related APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[0745] 3. Information Analysis and Format Generation

[0746] The server analyzes the received data and extracts customer-related information (such as transaction history, purchase information, and network configuration information). Next, it generates the necessary format (FMT) based on this information.

[0747] Furthermore, the server uses the analyzed network information to generate a network configuration diagram. This involves creating a visual diagram using a network configuration diagram generation API.

[0748] 4. Providing the results

[0749] The server returns the generated format (FMT) and network diagram to the terminal. The user can then view the results displayed on the terminal screen.

[0750] Specific example

[0751] The user enters the customer name "ExampleCorp" and clicks the submit button. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. Simultaneously, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network configuration diagram for ExampleCorp are generated. Finally, the server sends these results to the terminal, and the user confirms the results.

[0752] In this way, users can easily obtain the necessary information and proceed with their work efficiently simply by entering the customer's name into the input form. This system automates many manual tasks, significantly reducing time and effort.

[0753] The following describes the processing flow.

[0754] Step 1:

[0755] The user accesses the input form on their device. The device displays an input screen for entering the customer's name.

[0756] Step 2:

[0757] The user enters a customer name (e.g., "ExampleCorp") into the input form on the device and clicks the submit button. The device then sends the entered customer name to the server.

[0758] Step 3:

[0759] The server receives the request sent from the terminal and extracts the customer name "ExampleCorp" from the request body.

[0760] Step 4:

[0761] The server sends a request to the Customer Relationship Management (CRM) system. This request includes the customer name "ExampleCorp" and asks to retrieve transaction history information.

[0762] Step 5:

[0763] The server sends a request to the Enterprise Resource Planning (ERP) system. This request includes the customer name "ExampleCorp" and requests the retrieval of purchasing information.

[0764] Step 6:

[0765] The server sends a request to the network management system. This request includes the customer name "ExampleCorp" and requests the retrieval of network configuration information.

[0766] Step 7:

[0767] The server sends requests to other relevant APIs (e.g., customer information API, network configuration API, etc.) to retrieve additional information.

[0768] Step 8:

[0769] The server aggregates the responses received from each system and API. Each response is received in JSON or XML format.

[0770] Step 9:

[0771] The server analyzes the received data and extracts necessary customer-related information (such as transaction history, purchase information, and network configuration information).

[0772] Step 10:

[0773] The server generates a Customer Information Format (FMT) based on the analysis results. For example, it creates a report-style document that combines transaction history and purchase information.

[0774] Step 11:

[0775] The server uses the network diagram generation API to generate the latest network diagram based on the acquired network information.

[0776] Step 12:

[0777] The server combines the generated customer information format (FMT) and network configuration diagram and sends them to the terminal.

[0778] Step 13:

[0779] The user confirms the results displayed on their terminal (customer information format and network configuration diagram). This allows the user to easily and quickly obtain the necessary information.

[0780] Through these steps, users can simply enter a customer's name into an input form, and information will be automatically collected from numerous systems, allowing them to easily obtain the necessary formats and network diagrams.

[0781] (Example 1)

[0782] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0783] Traditional data collection and analysis systems often involved manual data collection, which was time-consuming and labor-intensive. Furthermore, integrating information from multiple different systems, efficiently analyzing it, and generating visual network diagrams was not easy. This resulted in decreased operational efficiency and hindered rapid decision-making.

[0784] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0785] In this invention, the server includes an input means for entering a customer name, a means for receiving the customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for generating a network configuration diagram based on the format, and a means for displaying the generated format and network configuration diagram. This automates a series of processes, from entering a customer name to automatic information collection, analysis, format generation, and network configuration diagram generation and display, enabling increased operational efficiency and faster decision-making.

[0786] "Input method for entering customer names" refers to the interface used by users to enter customer names into an information processing terminal.

[0787] "Means for receiving customer names entered through the input means" refers to a component or mechanism for receiving customer names transmitted through the input means.

[0788] "Means of sending requests to obtain customer-related information from multiple external systems" refers to a function or process for sending requests to multiple different systems for information retrieval or data collection.

[0789] "Means for analyzing customer-related information received from the external system" refers to algorithms or processing mechanisms for processing data received from the external system and extracting useful information.

[0790] "Means for generating a format based on the analyzed information" refers to a function for creating a predetermined format or report format based on the information obtained through analysis.

[0791] "Means for generating a network configuration diagram based on the aforementioned format" refers to a function for visually illustrating the network configuration and topology based on the generated format information.

[0792] "Means for displaying the generated format and network diagram" refers to an interface or device for displaying the created format and network diagram in a way that is visible to the user.

[0793] A "customer relationship management system" refers to a system for managing relationships with customers and centrally managing customer information, transaction history, and other related data.

[0794] A "corporate resource planning system" is a system for efficiently managing a company's resources, and it refers to a system that comprehensively manages business processes such as purchasing, inventory, and manufacturing.

[0795] A "network management system" refers to a system that manages the configuration, status, and performance of a network, and aims to optimize the network.

[0796] An "information processing terminal" refers to a device such as a computer or mobile device that a user uses to interact with a system.

[0797] This invention relates to an information processing system that automatically collects and analyzes customer-related information in cooperation with multiple external systems and APIs based on customer names provided by users, and generates necessary formats and network configuration diagrams. The embodiments for carrying out this invention will be described in detail below.

[0798] Users can enter customer names using an input form displayed on their device. For example, a user might enter "ExampleCorp" as a customer name and click the submit button. The device then sends this input to the server.

[0799] The server receives a request from the terminal and extracts the entered customer name. Next, the server sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems) to collect information about the customer "ExampleCorp". It also sends requests to relevant APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[0800] Specifically, the following requests are sent to the external system:

[0801] A request is sent to the customer relationship management (CRM) system saying, "Please provide transaction history information."

[0802] A request is sent to the Enterprise Resource Planning (ERP) system saying, "Please provide purchasing information."

[0803] A request is sent to the network management system asking for "network configuration information."

[0804] The server analyzes the data received as a response to these requests. It integrates and analyzes the received customer-related information, extracting transaction history, purchase information, and network configuration information. Based on this information, it generates the necessary format.

[0805] Based on the generated format, the server further generates a network diagram. To generate the network diagram, the network diagram generation API is used. Specifically, the acquired network data is analyzed and the network diagram generation API is called to visually represent the network topology.

[0806] Finally, the server sends the generated format and network diagram to the terminal. The user can then view the results on the terminal screen. This allows users to easily obtain the necessary information and significantly improve work efficiency.

[0807] Example of a prompt

[0808] The following are examples of prompts to input into a generative AI model:

[0809] "This system collects customer-related information based on the customer name provided by the user, by integrating with multiple systems and APIs, and automatically generates the necessary formats and network diagrams. Specifically, when a user enters the customer name "ExampleCorp" into the input form and clicks the submit button, the server collects information from the CRM system, ERP system, network management system, and other related APIs, analyzes it, and generates the formats and network diagrams. These are then sent back to the terminal, where the user can review the results."

[0810] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0811] Step 1:

[0812] The user enters the customer name into the input form displayed on the terminal and clicks the submit button. The system receives the customer name entered by the user (e.g., "ExampleCorp") as input. This entered customer name is sent to the system.

[0813] Step 2:

[0814] The terminal sends the customer name "ExampleCorp" entered by the user to the server. The server receives the customer name sent from the terminal as input. The server extracts the customer name and stores it for use in the next step.

[0815] Step 3:

[0816] The server sends information retrieval requests to multiple external systems based on the entered customer name "ExampleCorp". Specifically, it sends the following requests to external systems:

[0817] Send a request to the CRM system to retrieve transaction history information.

[0818] A request is sent to the ERP system to retrieve purchasing information.

[0819] Send a request to the network management system to retrieve network configuration information.

[0820] The input is the customer's name, and the output is a process that sends requests to the respective systems.

[0821] Step 4:

[0822] The server receives responses to requests from external systems. Specifically, it receives the following information:

[0823] Receive transaction history information from the CRM system.

[0824] Receive purchasing information from the ERP system.

[0825] Receive network configuration information from the network management system.

[0826] The input is a response from an external system, and the output is a dataset of customer-related information.

[0827] Step 5:

[0828] The server analyzes the acquired customer-related information. Specifically, it performs the following processes:

[0829] We analyze transaction history information and extract useful data.

[0830] Analyze purchase information and extract the necessary data.

[0831] Analyze network configuration information to understand the network topology.

[0832] The system takes customer-related information obtained from an external system as input, performs data processing and calculations, and outputs analyzed information.

[0833] Step 6:

[0834] The server generates the necessary format based on the parsed information. Specifically, it performs the following processes:

[0835] Integrate transaction history information and purchase information, and create a report format.

[0836] It takes parsed information as input and generates formatted data as output.

[0837] Step 7:

[0838] The server generates a network configuration diagram based on the generated format. Specifically, it performs the following steps:

[0839] The network diagram generation API is called to visually create a network diagram.

[0840] It takes analyzed network configuration information as input and outputs a network configuration diagram.

[0841] Step 8:

[0842] The server sends the generated format data and network diagram to the terminal. It takes the generated format data and network diagram as input and sends this data to the terminal as output.

[0843] Step 9:

[0844] The terminal displays formatted data and a network diagram received from the server to the user. The user can check the results displayed on the terminal screen and obtain the necessary information. It takes data received from the server as input and provides information in a format that the user can easily understand as output.

[0845] (Application Example 1)

[0846] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0847] Conventional security information gathering systems required the individual collection and manual analysis of information from multiple external systems, which was extremely time-consuming and laborious. Furthermore, in situations demanding immediate response based on security incidents and network configurations, rapid information gathering and analysis are essential, but conventional systems struggled to provide adequate responses. Therefore, there is a need for a system that automatically and rapidly collects, analyzes, and visually displays security-related information.

[0848] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0849] In this invention, the server includes an input means for entering a customer name, a means for receiving the customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for displaying the generated format, a means for collecting and analyzing security-related information from external systems, and a means for generating the analyzed security-related information. As a result, security personnel can quickly collect and analyze security incident information and network configuration diagrams from multiple external systems and visually confirm them simply by entering a customer name into an input form.

[0850] "Customer name" refers to the name of the target company or organization entered in order to collect information from an external system.

[0851] An "input method" refers to a device or interface used by a user to input text or strings of characters.

[0852] "Means of receiving" refers to the function by which a server receives data and information transmitted through input means.

[0853] "Means of sending requests" refers to communication functions that allow a server to request information from an external system.

[0854] "Means of analysis" refers to software and algorithms used to process received information, extract, manipulate, and analyze necessary data.

[0855] A "means for generating formats" refers to a function that creates documents and charts based on analyzed data, arranged in a specific format and visual layout.

[0856] "Means of display" refers to devices or interfaces used to display the generated format in a way that is viewable by the user.

[0857] "Security-related information" refers to data concerning the security of a company or organization, including incident information, network configuration, and threat information.

[0858] "External systems" refers to all systems that work in conjunction with servers to provide information, such as security information management systems, customer relationship management systems, corporate resource planning systems, and network management systems.

[0859] A "security configuration diagram" is a diagram that visually shows the arrangement of a company's or organization's network and security equipment.

[0860] A "security information management system" is a system that manages various security-related data, such as incident information, threat status, and alert information.

[0861] The following describes a specific embodiment for carrying out this invention. The system described below is for collecting and analyzing security-related information from an external system based on the customer's name and displaying it visually. This system mainly consists of a server, a smartphone, and an external system.

[0862] 1. Enter the customer's name.

[0863] The user enters the customer name on the smartphone application. After entering the customer name in the input form, they click the submit button. This sends the customer name (e.g., "SecurityCorp") to the server.

[0864] 2. Data Collection

[0865] The server sends information gathering requests to external systems based on the received customer name. These external systems include customer relationship management systems, corporate resource planning systems, network management systems, and security information management systems. For example, the server may obtain security incident information and network configuration information from SIEM (Security Information and Event Management) systems, firewall management systems, and intrusion detection systems.

[0866] 3. Information Analysis and Format Generation

[0867] The server analyzes the collected information and generates security incident reports and network diagrams. This analysis utilizes programming languages ​​such as Python and PDF generation libraries such as ReportLab. The analyzed information is then converted into a visually easy-to-understand format.

[0868] 4. Providing the results

[0869] The generated format and network configuration diagram are displayed on a smartphone application. By reviewing this, users can quickly grasp information about security incidents and network configurations and take appropriate action.

[0870] Hardware and software to be used

[0871] Hardware: Linux server, smartphone

[0872] Software: Python (requests library, ReportLab), external systems (SIEM, firewall management system, intrusion detection system)

[0873] Specific example

[0874] For example, a security officer enters the customer name "SecurityCorp" and clicks the submit button. The server collects security incident information from the security information management system and network security configuration information from the firewall management system. This information is analyzed, a visually understandable PDF report is generated, and displayed on the smartphone application.

[0875] Examples of prompts for generative AI models

[0876] Please enter the customer name (e.g., "SecurityCorp"). Based on this input, we will automatically generate the latest security incident information, network security configuration diagrams, and security reports.

[0877] As described above, this system allows users to quickly collect, analyze, and visually display security-related information from multiple external systems simply by entering a customer's name. This enables security personnel to respond quickly and appropriately even in situations requiring immediate action.

[0878] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0879] Step 1:

[0880] The user enters the customer name on the smartphone application. They enter the customer name in the input form and click the submit button. The entered data (e.g., "SecurityCorp") is sent to the server.

[0881] Step 2:

[0882] The server receives requests sent by users and extracts the entered customer name. Based on this customer name, it generates data for requests to external systems (input: customer name "SecurityCorp", output: request data to each external system).

[0883] Step 3:

[0884] The server uses the generated request data to send information gathering requests to multiple external systems. These external systems include customer relationship management systems, corporate resource planning systems, network management systems, and security information management systems (input: request data, output: information from each system).

[0885] Step 4:

[0886] The external system receives requests from the server and returns information about the relevant customer. This includes transaction history information from the customer relationship management system, purchasing information from the corporate resource planning system, network configuration information from the network management system, and security incident information from the security information management system (input: request, output: customer-related information).

[0887] Step 5:

[0888] The server analyzes customer-related information received from external systems. This analysis process uses programming languages ​​such as Python and specific analysis algorithms to convert the received data into a formattable form (input: information from each system, output: analyzed data).

[0889] Step 6:

[0890] The server generates a visually easy-to-understand format based on the analyzed data. Specifically, it uses PDF generation libraries such as ReportLab to create reports that include security incident information and network configuration diagrams (input: analyzed data, output: generated format).

[0891] Step 7:

[0892] The server sends the generated format to the smartphone application. The user can view and review the report on their smartphone in a visually easy-to-understand format (Input: Generated format, Output: Displayed report).

[0893] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0894] The embodiments for implementing the system of the present invention will be described in detail below.

[0895] This system collects customer-related information based on customer names provided by the user, by linking with multiple systems and APIs, and automatically generates the necessary formats and network diagrams. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it can present information in a way that responds to the user's feelings.

[0896] Explanation of the program's processing

[0897] 1. Customer name input and sentiment recognition

[0898] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (for example, "ExampleCorp") into this form and clicks the submit button. Simultaneously with the input, the emotion engine analyzes the user's typing speed, facial expressions, or voice to recognize the user's emotions.

[0899] 2. Data Collection

[0900] The server receives the request sent from the terminal and extracts the entered customer name. Next, it sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems, etc.) and related APIs to collect information about the customer "ExampleCorp".

[0901] Examples of data collection

[0902] The server sends a request to the Customer Relationship Management (CRM) system to retrieve ExampleCorp's transaction history information.

[0903] The server sends a request to the Enterprise Resource Planning (ERP) system to retrieve purchasing information for ExampleCorp.

[0904] The server sends a request to the network management system to retrieve the network configuration information for ExampleCorp.

[0905] Requests are also sent to other related APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[0906] 3. Information Analysis and Format Generation

[0907] The server analyzes the received data and extracts customer-related information (such as transaction history, purchase information, and network configuration information). Next, it generates the necessary format (FMT) based on this information. Furthermore, the server uses the analyzed network information to generate a network configuration diagram. This involves creating a visual diagram using a network configuration diagram generation API.

[0908] 4. Emotion-based expression

[0909] The server retrieves user emotional information recognized through the emotion engine. For example, if the user is feeling anxious or stressed, the server provides information in a more concise and visual format. Conversely, if the user is relaxed, it provides information in a more detailed format, adjusting the displayed content according to the user's state.

[0910] 5. Providing results

[0911] The server returns the generated format (FMT) and network diagram to the terminal. The user can then view the results displayed on the terminal screen. Because the information is provided in a display format that suits the user's emotional state, it is possible to acquire and understand the information more efficiently.

[0912] Specific example

[0913] The user enters the customer name "ExampleCorp" and clicks the submit button. Simultaneously, the emotion engine analyzes the user's typing speed and facial expressions, recognizing that the user is feeling anxious. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. At the same time, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network diagram related to ExampleCorp are generated. The generated information is presented concisely and visually, taking into account the user's anxiety. Finally, the server sends these results to the terminal, and the user confirms them.

[0914] In this way, users can simply enter their customer name into an input form, and information will be automatically collected from many systems, allowing them to easily obtain the necessary formats and network diagrams. Furthermore, the introduction of an emotion engine enables the provision of information tailored to the user's emotions, thereby improving the user experience.

[0915] The following describes the processing flow.

[0916] Step 1:

[0917] The user accesses the input form on their device. The device displays an input screen for entering the customer's name.

[0918] Step 2:

[0919] The user enters a customer name (e.g., "ExampleCorp") into the input form on the device and clicks the submit button. The device then sends the entered customer name to the server.

[0920] Step 3:

[0921] The device activates an emotion engine to recognize the user's emotions based on their input speed, facial expressions, and voice. Analysis is performed during input and after transmission to obtain the user's emotional information.

[0922] Step 4:

[0923] The server receives the request sent from the terminal and extracts the customer name "ExampleCorp" from the request body. The server also stores the user's sentiment information obtained from the sentiment engine.

[0924] Step 5:

[0925] The server sends a request to the Customer Relationship Management (CRM) system. This request includes the customer name "ExampleCorp" and asks to retrieve transaction history information.

[0926] Step 6:

[0927] The server sends a request to the Enterprise Resource Planning (ERP) system. This request includes the customer name "ExampleCorp" and requests the retrieval of purchasing information.

[0928] Step 7:

[0929] The server sends a request to the network management system. This request includes the customer name "ExampleCorp" and requests the retrieval of network configuration information.

[0930] Step 8:

[0931] The server sends requests to other relevant APIs (e.g., customer information API, network configuration API, etc.) to retrieve additional information.

[0932] Step 9:

[0933] The server aggregates the responses received from each system and API. Each response is received in JSON or XML format.

[0934] Step 10:

[0935] The server analyzes the received data and extracts necessary customer-related information (such as transaction history, purchase information, and network configuration information).

[0936] Step 11:

[0937] The server generates a Customer Information Format (FMT) based on the analysis results. For example, it creates a report-style document that combines transaction history and purchase information.

[0938] Step 12:

[0939] The server uses the network diagram generation API to generate the latest network diagram based on the acquired network information.

[0940] Step 13:

[0941] The server retrieves user emotion information recognized through the emotion engine and adjusts the display format accordingly. For example, if the user is feeling anxious or stressed, the information is presented concisely and visually; if they are relaxed, more detailed information is provided.

[0942] Step 14:

[0943] The server sends the generated customer information format (FMT) and network configuration diagram back to the terminal, and adjusts the display based on the user's sentiment.

[0944] Step 15:

[0945] The user confirms the results displayed on the terminal (customer information format and network configuration diagram). Because the terminal presents information in a format that aligns with the user's emotional state, the user can intuitively understand the information.

[0946] Through these steps, users can simply enter their customer name into an input form, and information will be automatically collected from numerous systems, easily obtaining the necessary formats and network diagrams. Furthermore, the emotion engine enables the provision of information tailored to the user's emotions, thereby improving the user experience.

[0947] (Example 2)

[0948] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0949] Conventional systems only retrieve information by inputting the customer's name, failing to provide information tailored to the user's emotions and making it difficult to present optimal information according to the user's state. In particular, users experiencing anxiety or stress require information in a visually easy-to-understand format, but such flexible responses were insufficient.

[0950] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0951] In this invention, the server includes an input means for entering a customer name, a means for receiving a customer name entered through the input means, an emotion engine means for recognizing the user's emotions based on the entered customer name, a means for sending requests to obtain customer-related information from a plurality of external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for adjusting the display method of the format based on the emotions recognized by the emotion engine means, and a means for displaying the generated format.

[0952] This allows for the display format of information to be adjusted according to the user's emotions, enabling the provision of information that is optimal for the user's state.

[0953] "Input means" refers to a device or interface for a user to enter a customer's name.

[0954] "Receiving means" refers to a device or program that has the function of acquiring the customer name entered through the input means and transmitting it to the server.

[0955] An "emotion engine" refers to software or hardware that analyzes the user's input speed, facial expression data, or voice to recognize the user's emotions.

[0956] "Means for sending requests" refers to a device or program that uses protocols such as HTTP requests to communicate with multiple external systems in order to obtain customer-related information.

[0957] "Analysis means" refers to software or hardware for processing data received from an external system and extracting and analyzing necessary information.

[0958] "Means for generating a format" refers to software or hardware used to create a specific format or report based on analyzed information.

[0959] "Means for adjusting the display method of formatting" refers to software or hardware for changing or optimizing the display format of information based on recognized user sentiment.

[0960] "Display means" refers to a screen or device for providing users with information such as generated formats and network configuration diagrams.

[0961] The following describes in detail the embodiments for implementing the system of the present invention. This system collects and analyzes customer-related information based on the customer name provided by the user, in cooperation with multiple systems and APIs, and provides the information in the most optimal format. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to provide information that corresponds to the user's emotions.

[0962] Customer name input and sentiment recognition

[0963] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (e.g., "ExampleCorp") into this form and clicks the submit button. At this time, the emotion engine analyzes the user's input speed, facial expression data (e.g., obtained from a webcam), or voice in real time to recognize the user's emotions. TensorFlow.js is used for emotion recognition and facial expression analysis.

[0964] Data collection

[0965] The server receives requests sent from the terminal, parses the HTTP requests, and extracts the entered customer name. The server uses Node.js and Express.js, among others. Next, it sends requests to multiple external systems and APIs (e.g., CRM systems, ERP systems, network management systems) to collect customer information. The retrieved data is typically received in JSON format.

[0966] Information analysis and format generation

[0967] The server analyzes the received data and extracts customer-related information (transaction history, purchase information, network configuration information, etc.). The Python pandas library is used for this analysis. Next, the necessary formats (such as reports) are generated based on the analyzed information. An Excel report is generated using pandas. Additionally, a network configuration diagram is visually created using the D3.js library.

[0968] Emotion-based display

[0969] The server retrieves user emotion information recognized through the emotion engine. The server adjusts how the information is displayed based on the user's emotions. For example, it provides information to a user who is feeling anxious in a more concise and visual format, while providing information to a relaxed user in a format that includes more detailed information.

[0970] Providing results

[0971] The server returns the generated format (such as an Excel report) and network diagram to the terminal. The terminal displays the received data in its user interface. The user can then review the results and obtain the necessary information.

[0972] Specific example

[0973] The user enters the customer name "ExampleCorp" and clicks the submit button. At this point, the emotion engine analyzes the user's typing speed and facial expressions, recognizing that the user is feeling anxious. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. Simultaneously, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network diagram related to ExampleCorp are generated. The generated information is presented concisely and visually, taking into account the user's anxiety. Finally, the server sends these results to the terminal, and the user confirms them.

[0974] Example of a prompt

[0975] Collect transaction history, purchase information, and network configuration information for a customer named 'ExampleCorp', and generate and display the necessary format and network configuration diagram based on this information. Note that if the user is feeling anxious, the information should be displayed in a concise and visual format.

[0976] Based on the customer name entered by the user, collect necessary information from relevant external systems and APIs, and automatically generate a format and network configuration diagram. Furthermore, implement a process to adjust the display format according to the user's mood.

[0977] This system allows users to automatically collect information from multiple systems and easily obtain necessary formats and network diagrams simply by entering a customer's name into an input form. Furthermore, the introduction of an emotion engine enables the provision of information tailored to the user's emotions, improving the user experience.

[0978] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0979] Step 1:

[0980] The terminal displays an input form for the user to enter a customer name. As an example, this form is constructed using HTML and JavaScript. The display of this input form is the input, and the output is the user entering a customer name on the form and clicking the submit button. The user enters "Example Corp".

[0981] Step 2:

[0982] The terminal receives the customer name entered in the input form and sends it to the server as an HTTP request. The input is the customer name "ExampleCorp" entered by the user. The output is an HTTP request containing that customer name. This HTTP request is sent in JSON format.

[0983] Step 3:

[0984] The server parses the HTTP request sent from the terminal and extracts the customer name "ExampleCorp". The receipt of this HTTP request is the input, and the extraction of the specified customer name through JSON parsing is the output.

[0985] Step 4:

[0986] The emotion engine analyzes user input speed, facial expression data, or voice data in real time to recognize the user's emotions. TensorFlow.js is used here. The input is the user's customer name input process and its data. The output is user emotion information (e.g., anxiety).

[0987] Step 5:

[0988] The server sends requests to multiple external systems (e.g., CRM system, ERP system, network management system) to collect information related to the customer name "ExampleCorp". The input is requests to the external systems. The output is transaction history, purchase information, and network configuration information retrieved from the external systems. This data is returned in JSON format.

[0989] Step 6:

[0990] The server analyzes the received data. For example, it processes the data using the Python pandas library. Customer-related information obtained from an external system is used as input. The output is an organized dataset containing transaction history, purchase information, and network configuration information.

[0991] Step 7:

[0992] The server generates the required format (e.g., an Excel report) based on the analyzed information. It uses the pandas library to generate the Excel file. The input is a well-organized dataset. The output is an Excel report.

[0993] Step 8:

[0994] The server uses the D3.js library to generate network diagrams. Network configuration information is taken as input. A visual network diagram is generated as output.

[0995] Step 9:

[0996] The server adjusts the display format based on the emotions recognized by the emotion engine. Specifically, if the user is feeling anxious, the information is presented in a concise, visual format; if they are relaxed, detailed information is included. The input is recognized emotion data. The output is a format with the adjusted display method and a network diagram.

[0997] Step 10:

[0998] The server sends the generated format and network diagram to the terminal. The inputs are the generated report and network diagram. The output is the data that is sent as an HTTP response.

[0999] Step 11:

[1000] The terminal displays the received data on the user's screen. Inputs include reports and network diagrams received as HTTP responses. Outputs are visual information displayed on the user interface. The user can review this information and obtain the necessary details.

[1001] (Application Example 2)

[1002] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1003] There is a need for effective management of customer information and manufacturing status in factories, and for providing this information to employees at the appropriate time. In particular, it is important to adjust the information according to the emotional state of employees and present it in an appropriate format. However, conventional systems have problems with adjusting displays based on emotion recognition and managing detailed information in real time. This invention aims to solve these problems.

[1004] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1005] In this invention, the server includes an input means for entering a customer name, a means for receiving a customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for adjusting the display content based on emotional information recognized through the means, and a means for displaying the generated format. This enables easy real-time information gathering and processing, and further allows for information display tailored to the emotional state of employees.

[1006] A "customer name" is a name used to identify a specific customer.

[1007] An "input method" is a means by which a user enters specific information into a system.

[1008] "Means of receiving" refers to a mechanism for receiving input information.

[1009] "Multiple external systems" refers to different systems that exist externally, and examples include customer relationship management systems, corporate resource planning systems, and network management systems.

[1010] "Means for sending requests" refers to functions or devices used to send requests to external systems in order to obtain desired information.

[1011] "Customer-related information" refers to data such as transaction history, purchase information, and network configuration information related to a specific customer.

[1012] "Means of analysis" refer to devices or programs that analyze received information and convert it into meaningful data.

[1013] "Means for generating a format" refers to devices or programs used to organize analyzed information into a specific format.

[1014] "Emotional information" refers to data that indicates the user's emotional state based on factors such as facial expressions, voice, and input speed.

[1015] "Means for adjusting the displayed content" refers to devices or programs for changing the content and format of the information displayed in accordance with recognized emotional information.

[1016] A system that includes "generated formats" refers to documents or data in a specific format created based on the analyzed information.

[1017] A "network diagram" is a diagram that visually represents the connections and structure of a network.

[1018] This invention relates to a system that collects customer-related information from multiple external systems based on the customer name entered by the user, analyzes and processes that information, and generates the necessary format and network configuration diagram. Furthermore, it can provide an optimal information display method according to the user's emotional state.

[1019] This system is configured as follows:

[1020] 1. Hardware and software configuration

[1021] Hardware: Factory robots (e.g., Pepper, UR5), emotion recognition cameras and microphones (e.g., Microsoft Azure Kinect, Intel RealSense)

[1022] Software: Emotion recognition engines (e.g., Affectiva, Microsoft Azure Emotion API), data collection APIs (e.g., Salesforce API, SAP API), network diagram generation APIs (e.g., Lucidchart API, Draw.io API), cloud data analysis engines (e.g., AWS Lambda, Google Cloud Functions)

[1023] 2. User Interface

[1024] The terminal displays a form where the user can enter the customer's name. Once the user enters the customer's name and submits it, the emotion recognition camera and microphone analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[1025] 3. Data Collection

[1026] The server receives requests sent from terminals and extracts the entered customer name. It then sends requests to multiple external systems (e.g., customer relationship management systems and corporate resource planning systems) and related APIs to collect customer information. Data collection APIs are used in this collection process.

[1027] 4. Information Analysis and Format Generation

[1028] The server analyzes the received data and extracts customer-related information. Next, it generates the necessary format based on this information. It also creates network diagrams using a network diagram generation API. A cloud data analysis engine assists in this analysis and generation process.

[1029] 5. Emotion-based display adjustments

[1030] The server retrieves the user's emotional information, recognized through the emotion engine, and adjusts the format and content of the information display. For example, when the user is feeling anxious, the information is presented concisely and visually, while when they are relaxed, detailed information is provided.

[1031] 6. Displaying the results

[1032] Finally, the server sends the generated format and network diagram to the terminal for the user to review. Emotion-based adjustments improve the user experience.

[1033] For example, if a factory worker enters the customer name "XYZCorp" and a sense of urgency is detected, the server retrieves transaction history from the customer relationship management system and extracts purchasing information from the corporate resource planning system. By providing this information in a concise format and visually displaying a network diagram, workers can quickly obtain the information they need.

[1034] An example of a prompt message for a generative AI model is as follows:

[1035] "Customer Name: XYZCorp, Emotion: Impatient, Required Information: Manufacturing progress, quality control data, factory layout diagram:"

[1036] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1037] Step 1:

[1038] The device displays a form where the user can enter the customer's name. The user enters the customer's name into this form and clicks the submit button. Simultaneously with the input, the emotion recognition camera and microphone collect the user's facial expressions and voice, and send them to the emotion engine.

[1039] Input: Customer name, user's facial expression, voice

[1040] Output: User-entered customer name, collected sentiment data

[1041] Step 2:

[1042] The server receives the request sent from the terminal and extracts the entered customer name (e.g., XYZCorp). Next, the emotion engine analyzes the collected data and recognizes the user's emotion (e.g., anxiety).

[1043] Input: Request from the device, customer name, sentiment data

[1044] Output: Recognized emotion information

[1045] Step 3:

[1046] The server sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems) and associated APIs to collect customer information.

[1047] Input: Customer name, API endpoint of the external system

[1048] Output: Customer-related information obtained from each external system

[1049] Step 4:

[1050] The server analyzes the received customer-related information and extracts the necessary data (e.g., transaction history, purchase information). Next, it generates a format based on this data.

[1051] Input: Customer-related information from external systems

[1052] Output: Analyzed data, generated format

[1053] Step 5:

[1054] The server uses a network diagram generation API to generate a network diagram based on the analyzed data.

[1055] Input: Analyzed data

[1056] Output: Network Configuration Diagram

[1057] Step 6:

[1058] The server adjusts the information displayed to the user based on the recognized emotional information. For example, if it detects anxiety, it provides information in a concise and visual format. On the other hand, if the user is relaxed, it provides detailed information.

[1059] Input: Recognized emotion information, generated format, network diagram

[1060] Output: Adjusted information display content

[1061] Step 7:

[1062] The server sends the generated format and network configuration diagram to the terminal for the user to review. The user can then take appropriate action based on the displayed information.

[1063] Input: Adjusted information display content

[1064] Output: Information displayed on the terminal

[1065] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1066] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1067] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1068] [Fourth Embodiment]

[1069] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1070] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1071] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1072] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1073] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1074] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1075] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1076] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1077] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1078] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1079] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1080] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1081] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1082] The embodiments for implementing the system of the present invention will be described in detail below.

[1083] This system collects customer-related information based on customer names provided by the user, in conjunction with multiple systems and APIs, and automatically generates the necessary formats and network configuration diagrams.

[1084] Explanation of the program's processing

[1085] 1. Enter the customer's name.

[1086] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (for example, "ExampleCorp") into this input form and clicks the submit button.

[1087] 2. Data Collection

[1088] The server receives the request sent from the terminal and extracts the entered customer name. Next, it sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems, etc.) and related APIs to collect information about the customer "ExampleCorp".

[1089] Examples of data collection

[1090] The server sends a request to the Customer Relationship Management (CRM) system to retrieve ExampleCorp's transaction history information.

[1091] The server sends a request to the Enterprise Resource Planning (ERP) system to retrieve purchasing information for ExampleCorp.

[1092] The server sends a request to the network management system to retrieve the network configuration information for ExampleCorp.

[1093] Requests are also sent to other related APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[1094] 3. Information Analysis and Format Generation

[1095] The server analyzes the received data and extracts customer-related information (such as transaction history, purchase information, and network configuration information). Next, it generates the necessary format (FMT) based on this information.

[1096] Furthermore, the server uses the analyzed network information to generate a network configuration diagram. This involves creating a visual diagram using a network configuration diagram generation API.

[1097] 4. Providing the results

[1098] The server returns the generated format (FMT) and network diagram to the terminal. The user can then view the results displayed on the terminal screen.

[1099] Specific example

[1100] The user enters the customer name "ExampleCorp" and clicks the submit button. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. Simultaneously, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network configuration diagram for ExampleCorp are generated. Finally, the server sends these results to the terminal, and the user confirms the results.

[1101] In this way, users can easily obtain the necessary information and proceed with their work efficiently simply by entering the customer's name into the input form. This system automates many manual tasks, significantly reducing time and effort.

[1102] The following describes the processing flow.

[1103] Step 1:

[1104] The user accesses the input form on their device. The device displays an input screen for entering the customer's name.

[1105] Step 2:

[1106] The user enters a customer name (e.g., "ExampleCorp") into the input form on the device and clicks the submit button. The device then sends the entered customer name to the server.

[1107] Step 3:

[1108] The server receives the request sent from the terminal and extracts the customer name "ExampleCorp" from the request body.

[1109] Step 4:

[1110] The server sends a request to the Customer Relationship Management (CRM) system. This request includes the customer name "ExampleCorp" and asks to retrieve transaction history information.

[1111] Step 5:

[1112] The server sends a request to the Enterprise Resource Planning (ERP) system. This request includes the customer name "ExampleCorp" and requests the retrieval of purchasing information.

[1113] Step 6:

[1114] The server sends a request to the network management system. This request includes the customer name "ExampleCorp" and requests the retrieval of network configuration information.

[1115] Step 7:

[1116] The server sends requests to other relevant APIs (e.g., customer information API, network configuration API, etc.) to retrieve additional information.

[1117] Step 8:

[1118] The server aggregates the responses received from each system and API. Each response is received in JSON or XML format.

[1119] Step 9:

[1120] The server analyzes the received data and extracts necessary customer-related information (such as transaction history, purchase information, and network configuration information).

[1121] Step 10:

[1122] The server generates a Customer Information Format (FMT) based on the analysis results. For example, it creates a report-style document that combines transaction history and purchase information.

[1123] Step 11:

[1124] The server uses the network diagram generation API to generate the latest network diagram based on the acquired network information.

[1125] Step 12:

[1126] The server combines the generated customer information format (FMT) and network configuration diagram and sends them to the terminal.

[1127] Step 13:

[1128] The user confirms the results displayed on their terminal (customer information format and network configuration diagram). This allows the user to easily and quickly obtain the necessary information.

[1129] Through these steps, users can simply enter a customer's name into an input form, and information will be automatically collected from numerous systems, allowing them to easily obtain the necessary formats and network diagrams.

[1130] (Example 1)

[1131] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1132] Traditional data collection and analysis systems often involved manual data collection, which was time-consuming and labor-intensive. Furthermore, integrating information from multiple different systems, efficiently analyzing it, and generating visual network diagrams was not easy. This resulted in decreased operational efficiency and hindered rapid decision-making.

[1133] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1134] In this invention, the server includes an input means for entering a customer name, a means for receiving the customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for generating a network configuration diagram based on the format, and a means for displaying the generated format and network configuration diagram. This automates a series of processes, from entering a customer name to automatic information collection, analysis, format generation, and network configuration diagram generation and display, enabling increased operational efficiency and faster decision-making.

[1135] "Input method for entering customer names" refers to the interface used by users to enter customer names into an information processing terminal.

[1136] "Means for receiving customer names entered through the input means" refers to a component or mechanism for receiving customer names transmitted through the input means.

[1137] "Means of sending requests to obtain customer-related information from multiple external systems" refers to a function or process for sending requests to multiple different systems for information retrieval or data collection.

[1138] "Means for analyzing customer-related information received from the external system" refers to algorithms or processing mechanisms for processing data received from the external system and extracting useful information.

[1139] "Means for generating a format based on the analyzed information" refers to a function for creating a predetermined format or report format based on the information obtained through analysis.

[1140] "Means for generating a network configuration diagram based on the aforementioned format" refers to a function for visually illustrating the network configuration and topology based on the generated format information.

[1141] "Means for displaying the generated format and network diagram" refers to an interface or device for displaying the created format and network diagram in a way that is visible to the user.

[1142] A "customer relationship management system" refers to a system for managing relationships with customers and centrally managing customer information, transaction history, and other related data.

[1143] A "corporate resource planning system" is a system for efficiently managing a company's resources, and it refers to a system that comprehensively manages business processes such as purchasing, inventory, and manufacturing.

[1144] A "network management system" refers to a system that manages the configuration, status, and performance of a network, and aims to optimize the network.

[1145] An "information processing terminal" refers to a device such as a computer or mobile device that a user uses to interact with a system.

[1146] This invention relates to an information processing system that automatically collects and analyzes customer-related information in cooperation with multiple external systems and APIs based on customer names provided by users, and generates necessary formats and network configuration diagrams. The embodiments for carrying out this invention will be described in detail below.

[1147] Users can enter customer names using an input form displayed on their device. For example, a user might enter "ExampleCorp" as a customer name and click the submit button. The device then sends this input to the server.

[1148] The server receives a request from the terminal and extracts the entered customer name. Next, the server sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems) to collect information about the customer "ExampleCorp". It also sends requests to relevant APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[1149] Specifically, the following requests are sent to the external system:

[1150] A request is sent to the customer relationship management (CRM) system saying, "Please provide transaction history information."

[1151] A request is sent to the Enterprise Resource Planning (ERP) system saying, "Please provide purchasing information."

[1152] A request is sent to the network management system asking for "network configuration information."

[1153] The server analyzes the data received as a response to these requests. It integrates and analyzes the received customer-related information, extracting transaction history, purchase information, and network configuration information. Based on this information, it generates the necessary format.

[1154] Based on the generated format, the server further generates a network diagram. To generate the network diagram, the network diagram generation API is used. Specifically, the acquired network data is analyzed and the network diagram generation API is called to visually represent the network topology.

[1155] Finally, the server sends the generated format and network diagram to the terminal. The user can then view the results on the terminal screen. This allows users to easily obtain the necessary information and significantly improve work efficiency.

[1156] Example of a prompt

[1157] The following are examples of prompts to input into a generative AI model:

[1158] "This system collects customer-related information based on the customer name provided by the user, by integrating with multiple systems and APIs, and automatically generates the necessary formats and network diagrams. Specifically, when a user enters the customer name "ExampleCorp" into the input form and clicks the submit button, the server collects information from the CRM system, ERP system, network management system, and other related APIs, analyzes it, and generates the formats and network diagrams. These are then sent back to the terminal, where the user can review the results."

[1159] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1160] Step 1:

[1161] The user enters the customer name into the input form displayed on the terminal and clicks the submit button. The system receives the customer name entered by the user (e.g., "ExampleCorp") as input. This entered customer name is sent to the system.

[1162] Step 2:

[1163] The terminal sends the customer name "ExampleCorp" entered by the user to the server. The server receives the customer name sent from the terminal as input. The server extracts the customer name and stores it for use in the next step.

[1164] Step 3:

[1165] The server sends information retrieval requests to multiple external systems based on the entered customer name "ExampleCorp". Specifically, it sends the following requests to external systems:

[1166] Send a request to the CRM system to retrieve transaction history information.

[1167] A request is sent to the ERP system to retrieve purchasing information.

[1168] Send a request to the network management system to retrieve network configuration information.

[1169] The input is the customer's name, and the output is a process that sends requests to the respective systems.

[1170] Step 4:

[1171] The server receives responses to requests from external systems. Specifically, it receives the following information:

[1172] Receive transaction history information from the CRM system.

[1173] Receive purchasing information from the ERP system.

[1174] Receive network configuration information from the network management system.

[1175] The input is a response from an external system, and the output is a dataset of customer-related information.

[1176] Step 5:

[1177] The server analyzes the acquired customer-related information. Specifically, it performs the following processes:

[1178] We analyze transaction history information and extract useful data.

[1179] Analyze purchase information and extract the necessary data.

[1180] Analyze network configuration information to understand the network topology.

[1181] The system takes customer-related information obtained from an external system as input, performs data processing and calculations, and outputs analyzed information.

[1182] Step 6:

[1183] The server generates the necessary format based on the parsed information. Specifically, it performs the following processes:

[1184] Integrate transaction history information and purchase information, and create a report format.

[1185] It takes parsed information as input and generates formatted data as output.

[1186] Step 7:

[1187] The server generates a network configuration diagram based on the generated format. Specifically, it performs the following steps:

[1188] The network diagram generation API is called to visually create a network diagram.

[1189] It takes analyzed network configuration information as input and outputs a network configuration diagram.

[1190] Step 8:

[1191] The server sends the generated format data and network diagram to the terminal. It takes the generated format data and network diagram as input and sends this data to the terminal as output.

[1192] Step 9:

[1193] The terminal displays formatted data and a network diagram received from the server to the user. The user can check the results displayed on the terminal screen and obtain the necessary information. It takes data received from the server as input and provides information in a format that the user can easily understand as output.

[1194] (Application Example 1)

[1195] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1196] Conventional security information gathering systems required the individual collection and manual analysis of information from multiple external systems, which was extremely time-consuming and laborious. Furthermore, in situations demanding immediate response based on security incidents and network configurations, rapid information gathering and analysis are essential, but conventional systems struggled to provide adequate responses. Therefore, there is a need for a system that automatically and rapidly collects, analyzes, and visually displays security-related information.

[1197] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1198] In this invention, the server includes an input means for entering a customer name, a means for receiving the customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for displaying the generated format, a means for collecting and analyzing security-related information from external systems, and a means for generating the analyzed security-related information. As a result, security personnel can quickly collect and analyze security incident information and network configuration diagrams from multiple external systems and visually confirm them simply by entering a customer name into an input form.

[1199] "Customer name" refers to the name of the target company or organization entered in order to collect information from an external system.

[1200] An "input method" refers to a device or interface used by a user to input text or strings of characters.

[1201] "Means of receiving" refers to the function by which a server receives data and information transmitted through input means.

[1202] "Means of sending requests" refers to communication functions that allow a server to request information from an external system.

[1203] "Means of analysis" refers to software and algorithms used to process received information, extract, manipulate, and analyze necessary data.

[1204] A "means for generating formats" refers to a function that creates documents and charts based on analyzed data, arranged in a specific format and visual layout.

[1205] "Means of display" refers to devices or interfaces used to display the generated format in a way that is viewable by the user.

[1206] "Security-related information" refers to data concerning the security of a company or organization, including incident information, network configuration, and threat information.

[1207] "External systems" refer to all systems that work in conjunction with servers to provide information, such as security information management systems, customer relationship management systems, corporate resource planning systems, and network management systems.

[1208] A "security configuration diagram" is a diagram that visually shows the arrangement of a company's or organization's network and security equipment.

[1209] A "security information management system" is a system that manages various security-related data, such as incident information, threat status, and alert information.

[1210] The following describes a specific embodiment for carrying out this invention. The system described below is for collecting and analyzing security-related information from an external system based on the customer's name and displaying it visually. This system mainly consists of a server, a smartphone, and an external system.

[1211] 1. Enter the customer's name.

[1212] The user enters the customer name on the smartphone application. After entering the customer name in the input form, they click the submit button. This sends the customer name (e.g., "SecurityCorp") to the server.

[1213] 2. Data Collection

[1214] The server sends information gathering requests to external systems based on the received customer name. These external systems include customer relationship management systems, corporate resource planning systems, network management systems, and security information management systems. For example, the server may obtain security incident information and network configuration information from SIEM (Security Information and Event Management) systems, firewall management systems, and intrusion detection systems.

[1215] 3. Information Analysis and Format Generation

[1216] The server analyzes the collected information and generates security incident reports and network diagrams. This analysis utilizes programming languages ​​such as Python and PDF generation libraries such as ReportLab. The analyzed information is then converted into a visually easy-to-understand format.

[1217] 4. Providing the results

[1218] The generated format and network configuration diagram are displayed on a smartphone application. By reviewing this, users can quickly grasp information about security incidents and network configurations and take appropriate action.

[1219] Hardware and software to be used

[1220] Hardware: Linux server, smartphone

[1221] Software: Python (requests library, ReportLab), external systems (SIEM, firewall management system, intrusion detection system)

[1222] Specific example

[1223] For example, a security officer enters the customer name "SecurityCorp" and clicks the submit button. The server collects security incident information from the security information management system and network security configuration information from the firewall management system. This information is analyzed, a visually understandable PDF report is generated, and displayed on the smartphone application.

[1224] Examples of prompts for generative AI models

[1225] Please enter the customer name (e.g., "SecurityCorp"). Based on this input, we will automatically generate the latest security incident information, network security configuration diagrams, and security reports.

[1226] As described above, this system allows users to quickly collect, analyze, and visually display security-related information from multiple external systems simply by entering a customer's name. This enables security personnel to respond quickly and appropriately even in situations requiring immediate action.

[1227] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1228] Step 1:

[1229] The user enters the customer name on the smartphone application. They enter the customer name in the input form and click the submit button. The entered data (e.g., "SecurityCorp") is sent to the server.

[1230] Step 2:

[1231] The server receives requests sent by users and extracts the entered customer name. Based on this customer name, it generates data for requests to external systems (input: customer name "SecurityCorp", output: request data to each external system).

[1232] Step 3:

[1233] The server uses the generated request data to send information gathering requests to multiple external systems. These external systems include customer relationship management systems, corporate resource planning systems, network management systems, and security information management systems (input: request data, output: information from each system).

[1234] Step 4:

[1235] The external system receives requests from the server and returns information about the relevant customer. This includes transaction history information from the customer relationship management system, purchasing information from the corporate resource planning system, network configuration information from the network management system, and security incident information from the security information management system (input: request, output: customer-related information).

[1236] Step 5:

[1237] The server analyzes customer-related information received from external systems. This analysis process uses programming languages ​​such as Python and specific analysis algorithms to convert the received data into a formattable form (input: information from each system, output: analyzed data).

[1238] Step 6:

[1239] The server generates a visually easy-to-understand format based on the analyzed data. Specifically, it uses PDF generation libraries such as ReportLab to create reports that include security incident information and network configuration diagrams (input: analyzed data, output: generated format).

[1240] Step 7:

[1241] The server sends the generated format to the smartphone application. The user can view and review the report on their smartphone in a visually easy-to-understand format (Input: Generated format, Output: Displayed report).

[1242] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1243] The embodiments for implementing the system of the present invention will be described in detail below.

[1244] This system collects customer-related information based on customer names provided by the user, by linking with multiple systems and APIs, and automatically generates the necessary formats and network diagrams. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it can present information in a way that responds to the user's feelings.

[1245] Explanation of the program's processing

[1246] 1. Customer name input and sentiment recognition

[1247] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (for example, "ExampleCorp") into this form and clicks the submit button. Simultaneously with the input, the emotion engine analyzes the user's typing speed, facial expressions, or voice to recognize the user's emotions.

[1248] 2. Data Collection

[1249] The server receives the request sent from the terminal and extracts the entered customer name. Next, it sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems, network management systems, etc.) and related APIs to collect information about the customer "ExampleCorp".

[1250] Examples of data collection

[1251] The server sends a request to the Customer Relationship Management (CRM) system to retrieve ExampleCorp's transaction history information.

[1252] The server sends a request to the Enterprise Resource Planning (ERP) system to retrieve purchasing information for ExampleCorp.

[1253] The server sends a request to the network management system to retrieve the network configuration information for ExampleCorp.

[1254] Requests are also sent to other related APIs (e.g., customer information API, network configuration API, etc.) to collect additional information.

[1255] 3. Information Analysis and Format Generation

[1256] The server analyzes the received data and extracts customer-related information (such as transaction history, purchase information, and network configuration information). Next, it generates the necessary format (FMT) based on this information. Furthermore, the server uses the analyzed network information to generate a network configuration diagram. This involves creating a visual diagram using a network configuration diagram generation API.

[1257] 4. Emotion-based expression

[1258] The server retrieves user emotional information recognized through the emotion engine. For example, if the user is feeling anxious or stressed, the server provides information in a more concise and visual format. Conversely, if the user is relaxed, it provides information in a more detailed format, adjusting the displayed content according to the user's state.

[1259] 5. Providing results

[1260] The server returns the generated format (FMT) and network diagram to the terminal. The user can then view the results displayed on the terminal screen. Because the information is provided in a display format that suits the user's emotional state, it is possible to acquire and understand the information more efficiently.

[1261] Specific example

[1262] The user enters the customer name "ExampleCorp" and clicks the submit button. Simultaneously, the emotion engine analyzes the user's typing speed and facial expressions, recognizing that the user is feeling anxious. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. At the same time, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network diagram related to ExampleCorp are generated. The generated information is presented concisely and visually, taking into account the user's anxiety. Finally, the server sends these results to the terminal, and the user confirms them.

[1263] In this way, users can simply enter their customer name into an input form, and information will be automatically collected from many systems, allowing them to easily obtain the necessary formats and network diagrams. Furthermore, the introduction of an emotion engine enables the provision of information tailored to the user's emotions, thereby improving the user experience.

[1264] The following describes the processing flow.

[1265] Step 1:

[1266] The user accesses the input form on their device. The device displays an input screen for entering the customer's name.

[1267] Step 2:

[1268] The user enters a customer name (e.g., "ExampleCorp") into the input form on the device and clicks the submit button. The device then sends the entered customer name to the server.

[1269] Step 3:

[1270] The device activates an emotion engine to recognize the user's emotions based on their input speed, facial expressions, and voice. Analysis is performed during input and after transmission to obtain the user's emotional information.

[1271] Step 4:

[1272] The server receives the request sent from the terminal and extracts the customer name "ExampleCorp" from the request body. The server also stores the user's sentiment information obtained from the sentiment engine.

[1273] Step 5:

[1274] The server sends a request to the Customer Relationship Management (CRM) system. This request includes the customer name "ExampleCorp" and asks to retrieve transaction history information.

[1275] Step 6:

[1276] The server sends a request to the Enterprise Resource Planning (ERP) system. This request includes the customer name "ExampleCorp" and requests the retrieval of purchasing information.

[1277] Step 7:

[1278] The server sends a request to the network management system. This request includes the customer name "ExampleCorp" and requests the retrieval of network configuration information.

[1279] Step 8:

[1280] The server sends requests to other relevant APIs (e.g., customer information API, network configuration API, etc.) to retrieve additional information.

[1281] Step 9:

[1282] The server aggregates the responses received from each system and API. Each response is received in JSON or XML format.

[1283] Step 10:

[1284] The server analyzes the received data and extracts necessary customer-related information (such as transaction history, purchase information, and network configuration information).

[1285] Step 11:

[1286] The server generates a Customer Information Format (FMT) based on the analysis results. For example, it creates a report-style document that combines transaction history and purchase information.

[1287] Step 12:

[1288] The server uses the network diagram generation API to generate the latest network diagram based on the acquired network information.

[1289] Step 13:

[1290] The server retrieves user emotion information recognized through the emotion engine and adjusts the display format accordingly. For example, if the user is feeling anxious or stressed, the information is presented concisely and visually; if they are relaxed, more detailed information is provided.

[1291] Step 14:

[1292] The server sends the generated customer information format (FMT) and network configuration diagram back to the terminal, and adjusts the display based on the user's sentiment.

[1293] Step 15:

[1294] The user confirms the results displayed on the terminal (customer information format and network configuration diagram). Because the terminal presents information in a format that aligns with the user's emotional state, the user can intuitively understand the information.

[1295] Through these steps, users can simply enter their customer name into an input form, and information will be automatically collected from numerous systems, easily obtaining the necessary formats and network diagrams. Furthermore, the emotion engine enables the provision of information tailored to the user's emotions, thereby improving the user experience.

[1296] (Example 2)

[1297] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1298] Conventional systems only retrieve information by inputting the customer's name, failing to provide information tailored to the user's emotions and making it difficult to present optimal information according to the user's state. In particular, users experiencing anxiety or stress require information in a visually easy-to-understand format, but such flexible responses were insufficient.

[1299] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1300] In this invention, the server includes an input means for entering a customer name, a means for receiving a customer name entered through the input means, an emotion engine means for recognizing the user's emotions based on the entered customer name, a means for sending requests to obtain customer-related information from a plurality of external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for adjusting the display method of the format based on the emotions recognized by the emotion engine means, and a means for displaying the generated format.

[1301] This allows for the display format of information to be adjusted according to the user's emotions, enabling the provision of information that is optimal for the user's state.

[1302] "Input means" refers to a device or interface for a user to enter a customer's name.

[1303] "Receiving means" refers to a device or program that has the function of acquiring the customer name entered through the input means and transmitting it to the server.

[1304] An "emotion engine" refers to software or hardware that analyzes the user's input speed, facial expression data, or voice to recognize the user's emotions.

[1305] "Means for sending requests" refers to a device or program that uses protocols such as HTTP requests to communicate with multiple external systems in order to obtain customer-related information.

[1306] "Analysis means" refers to software or hardware for processing data received from an external system and extracting and analyzing necessary information.

[1307] "Means for generating a format" refers to software or hardware used to create a specific format or report based on analyzed information.

[1308] "Means for adjusting the display method of formatting" refers to software or hardware for changing or optimizing the display format of information based on recognized user sentiment.

[1309] "Display means" refers to a screen or device for providing users with information such as generated formats and network configuration diagrams.

[1310] The following describes in detail the embodiments for implementing the system of the present invention. This system collects and analyzes customer-related information based on the customer name provided by the user, in cooperation with multiple systems and APIs, and provides the information in the most optimal format. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to provide information that corresponds to the user's emotions.

[1311] Customer name input and sentiment recognition

[1312] The terminal displays an input form where the user can enter a customer name. The user enters a customer name (e.g., "ExampleCorp") into this form and clicks the submit button. At this time, the emotion engine analyzes the user's input speed, facial expression data (e.g., obtained from a webcam), or voice in real time to recognize the user's emotions. TensorFlow.js is used for emotion recognition and facial expression analysis.

[1313] Data collection

[1314] The server receives requests sent from the terminal, parses the HTTP requests, and extracts the entered customer name. The server uses Node.js and Express.js, among others. Next, it sends requests to multiple external systems and APIs (e.g., CRM systems, ERP systems, network management systems) to collect customer information. The retrieved data is typically received in JSON format.

[1315] Information analysis and format generation

[1316] The server analyzes the received data and extracts customer-related information (transaction history, purchase information, network configuration information, etc.). The Python pandas library is used for this analysis. Next, the necessary formats (such as reports) are generated based on the analyzed information. An Excel report is generated using pandas. Additionally, a network configuration diagram is visually created using the D3.js library.

[1317] Emotion-based display

[1318] The server retrieves user emotion information recognized through the emotion engine. The server adjusts how the information is displayed based on the user's emotions. For example, it provides information to a user who is feeling anxious in a more concise and visual format, while providing information to a relaxed user in a format that includes more detailed information.

[1319] Providing results

[1320] The server returns the generated format (such as an Excel report) and network diagram to the terminal. The terminal displays the received data in its user interface. The user can then review the results and obtain the necessary information.

[1321] Specific example

[1322] The user enters the customer name "ExampleCorp" and clicks the submit button. At this point, the emotion engine analyzes the user's typing speed and facial expressions, recognizing that the user is feeling anxious. The server retrieves ExampleCorp's transaction history from the CRM system and purchase information from the ERP system. Simultaneously, it collects ExampleCorp's network configuration information from the network management system. This information is analyzed, and a format and network diagram related to ExampleCorp are generated. The generated information is presented concisely and visually, taking into account the user's anxiety. Finally, the server sends these results to the terminal, and the user confirms them.

[1323] Example of a prompt

[1324] Collect transaction history, purchase information, and network configuration information for a customer named 'ExampleCorp', and generate and display the necessary format and network configuration diagram based on this information. Note that if the user is feeling anxious, the information should be displayed in a concise and visual format.

[1325] Based on the customer name entered by the user, collect necessary information from relevant external systems and APIs, and automatically generate a format and network configuration diagram. Furthermore, implement a process to adjust the display format according to the user's mood.

[1326] This system allows users to automatically collect information from multiple systems and easily obtain necessary formats and network diagrams simply by entering a customer's name into an input form. Furthermore, the introduction of an emotion engine enables the provision of information tailored to the user's emotions, improving the user experience.

[1327] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1328] Step 1:

[1329] The terminal displays an input form for the user to enter a customer name. As an example, this form is constructed using HTML and JavaScript. The display of this input form is the input, and the output is the user entering a customer name on the form and clicking the submit button. The user enters "Example Corp".

[1330] Step 2:

[1331] The terminal receives the customer name entered in the input form and sends it to the server as an HTTP request. The input is the customer name "ExampleCorp" entered by the user. The output is an HTTP request containing that customer name. This HTTP request is sent in JSON format.

[1332] Step 3:

[1333] The server parses the HTTP request sent from the terminal and extracts the customer name "ExampleCorp". The receipt of this HTTP request is the input, and the extraction of the specified customer name through JSON parsing is the output.

[1334] Step 4:

[1335] The emotion engine analyzes user input speed, facial expression data, or voice data in real time to recognize the user's emotions. TensorFlow.js is used here. The input is the user's customer name input process and its data. The output is user emotion information (e.g., anxiety).

[1336] Step 5:

[1337] The server sends requests to multiple external systems (e.g., CRM system, ERP system, network management system) to collect information related to the customer name "ExampleCorp". The input is requests to the external systems. The output is transaction history, purchase information, and network configuration information retrieved from the external systems. This data is returned in JSON format.

[1338] Step 6:

[1339] The server analyzes the received data. For example, it processes the data using the Python pandas library. Customer-related information obtained from an external system is used as input. The output is an organized dataset containing transaction history, purchase information, and network configuration information.

[1340] Step 7:

[1341] The server generates the required format (e.g., an Excel report) based on the analyzed information. It uses the pandas library to generate the Excel file. The input is a well-organized dataset. The output is an Excel report.

[1342] Step 8:

[1343] The server uses the D3.js library to generate network diagrams. Network configuration information is taken as input. A visual network diagram is generated as output.

[1344] Step 9:

[1345] The server adjusts the display format based on the emotions recognized by the emotion engine. Specifically, if the user is feeling anxious, the information is presented in a concise, visual format; if they are relaxed, detailed information is included. The input is recognized emotion data. The output is a format with the adjusted display method and a network diagram.

[1346] Step 10:

[1347] The server sends the generated format and network diagram to the terminal. The inputs are the generated report and network diagram. The output is the data that is sent as an HTTP response.

[1348] Step 11:

[1349] The terminal displays the received data on the user's screen. Inputs include reports and network diagrams received as HTTP responses. Outputs are visual information displayed on the user interface. The user can review this information and obtain the necessary details.

[1350] (Application Example 2)

[1351] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1352] There is a need for effective management of customer information and manufacturing status in factories, and for providing this information to employees at the appropriate time. In particular, it is important to adjust the information according to the emotional state of employees and present it in an appropriate format. However, conventional systems have problems with adjusting displays based on emotion recognition and managing detailed information in real time. This invention aims to solve these problems.

[1353] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1354] In this invention, the server includes an input means for entering a customer name, a means for receiving a customer name entered through the input means, a means for sending requests to obtain customer-related information from multiple external systems, a means for analyzing the customer-related information received from the external systems, a means for generating a format based on the analyzed information, a means for adjusting the display content based on emotional information recognized through the means, and a means for displaying the generated format. This enables easy real-time information gathering and processing, and further allows for information display tailored to the emotional state of employees.

[1355] A "customer name" is a name used to identify a specific customer.

[1356] An "input method" is a means by which a user enters specific information into a system.

[1357] "Means of receiving" refers to a mechanism for receiving input information.

[1358] "Multiple external systems" refers to different systems that exist externally, and examples include customer relationship management systems, corporate resource planning systems, and network management systems.

[1359] "Means for sending requests" refers to functions or devices used to send requests to external systems in order to obtain desired information.

[1360] "Customer-related information" refers to data such as transaction history, purchase information, and network configuration information related to a specific customer.

[1361] "Means of analysis" refer to devices or programs that analyze received information and convert it into meaningful data.

[1362] "Means for generating a format" refers to devices or programs used to organize analyzed information into a specific format.

[1363] "Emotional information" refers to data that indicates the user's emotional state based on factors such as facial expressions, voice, and input speed.

[1364] "Means for adjusting the displayed content" refers to devices or programs for changing the content and format of the information displayed in accordance with recognized emotional information.

[1365] A system that includes "generated formats" refers to documents or data in a specific format created based on the analyzed information.

[1366] A "network diagram" is a diagram that visually represents the connections and structure of a network.

[1367] This invention relates to a system that collects customer-related information from multiple external systems based on the customer name entered by the user, analyzes and processes that information, and generates the necessary format and network configuration diagram. Furthermore, it can provide an optimal information display method according to the user's emotional state.

[1368] This system is configured as follows:

[1369] 1. Hardware and software configuration

[1370] Hardware: Factory robots (e.g., Pepper, UR5), emotion recognition cameras and microphones (e.g., Microsoft Azure Kinect, Intel RealSense)

[1371] Software: Emotion recognition engines (e.g., Affectiva, Microsoft Azure Emotion API), data collection APIs (e.g., Salesforce API, SAP API), network diagram generation APIs (e.g., Lucidchart API, Draw.io API), cloud data analysis engines (e.g., AWS Lambda, Google Cloud Functions)

[1372] 2. User Interface

[1373] The terminal displays a form where the user can enter the customer's name. Once the user enters the customer's name and submits it, the emotion recognition camera and microphone analyze the user's facial expressions and voice, and the emotion engine recognizes the user's emotions.

[1374] 3. Data Collection

[1375] The server receives requests sent from terminals and extracts the entered customer name. It then sends requests to multiple external systems (e.g., customer relationship management systems and corporate resource planning systems) and related APIs to collect customer information. Data collection APIs are used in this collection process.

[1376] 4. Information Analysis and Format Generation

[1377] The server analyzes the received data and extracts customer-related information. Next, it generates the necessary format based on this information. It also creates network diagrams using a network diagram generation API. A cloud data analysis engine assists in this analysis and generation process.

[1378] 5. Emotion-based display adjustments

[1379] The server retrieves the user's emotional information, recognized through the emotion engine, and adjusts the format and content of the information display. For example, when the user is feeling anxious, the information is presented concisely and visually, while when they are relaxed, detailed information is provided.

[1380] 6. Displaying the results

[1381] Finally, the server sends the generated format and network diagram to the terminal for the user to review. Emotion-based adjustments improve the user experience.

[1382] For example, if a factory worker enters the customer name "XYZCorp" and a sense of urgency is detected, the server retrieves transaction history from the customer relationship management system and extracts purchasing information from the corporate resource planning system. By providing this information in a concise format and visually displaying a network diagram, workers can quickly obtain the information they need.

[1383] An example of a prompt message for a generative AI model is as follows:

[1384] "Customer Name: XYZCorp, Emotion: Impatient, Required Information: Manufacturing progress, quality control data, factory layout diagram:"

[1385] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1386] Step 1:

[1387] The device displays a form where the user can enter the customer's name. The user enters the customer's name into this form and clicks the submit button. Simultaneously with the input, the emotion recognition camera and microphone collect the user's facial expressions and voice, and send them to the emotion engine.

[1388] Input: Customer name, user's facial expression, voice

[1389] Output: User-entered customer name, collected sentiment data

[1390] Step 2:

[1391] The server receives the request sent from the terminal and extracts the entered customer name (e.g., XYZCorp). Next, the emotion engine analyzes the collected data and recognizes the user's emotion (e.g., anxiety).

[1392] Input: Request from the device, customer name, sentiment data

[1393] Output: Recognized emotion information

[1394] Step 3:

[1395] The server sends requests to multiple external systems (e.g., customer relationship management systems, corporate resource planning systems) and associated APIs to collect customer information.

[1396] Input: Customer name, API endpoint of the external system

[1397] Output: Customer-related information obtained from each external system

[1398] Step 4:

[1399] The server analyzes the received customer-related information and extracts the necessary data (e.g., transaction history, purchase information). Next, it generates a format based on this data.

[1400] Input: Customer-related information from external systems

[1401] Output: Analyzed data, generated format

[1402] Step 5:

[1403] The server uses a network diagram generation API to generate a network diagram based on the analyzed data.

[1404] Input: Analyzed data

[1405] Output: Network Configuration Diagram

[1406] Step 6:

[1407] The server adjusts the information displayed to the user based on the recognized emotional information. For example, if it detects anxiety, it provides information in a concise and visual format. On the other hand, if the user is relaxed, it provides detailed information.

[1408] Input: Recognized emotion information, generated format, network diagram

[1409] Output: Adjusted information display content

[1410] Step 7:

[1411] The server sends the generated format and network configuration diagram to the terminal for the user to review. The user can then take appropriate action based on the displayed information.

[1412] Input: Adjusted information display content

[1413] Output: Information displayed on the terminal

[1414] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1415] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1416] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1417] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1418] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1419] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1420] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1421] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1422] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1423] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1424] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1425] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1426] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1427] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1428] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1429] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1430] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1431] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1432] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1433] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1434] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[1435] The following is further disclosed regarding the embodiments described above.

[1436] (Claim 1)

[1437] An input method for entering the customer's name,

[1438] A means for receiving the customer name entered through the input means,

[1439] A means of sending requests to obtain customer-related information from multiple external systems,

[1440] Means for analyzing customer-related information received from the aforementioned external system,

[1441] means for generating a format based on the analyzed information,

[1442] A means of displaying the generated format,

[1443] A system that includes this.

[1444] (Claim 2)

[1445] The system according to claim 1, further comprising means for generating a network configuration diagram based on the analyzed information.

[1446] (Claim 3)

[1447] The system according to claim 1, wherein the plurality of external systems include a customer relationship management system, a corporate resource planning system, and a network management system.

[1448] "Example 1"

[1449] (Claim 1)

[1450] An input method for entering the customer's name,

[1451] A means for receiving the customer name entered through the input means,

[1452] A means of sending requests to obtain customer-related information from multiple external systems,

[1453] Means for analyzing customer-related information received from the aforementioned external system,

[1454] means for generating a format based on the analyzed information,

[1455] Means for generating a network configuration diagram based on the aforementioned format,

[1456] A means for displaying the generated format and network configuration diagram,

[1457] An information processing system that includes this.

[1458] (Claim 2)

[1459] The information processing system according to claim 1, wherein the plurality of external systems include a customer relationship management system, a corporate resource planning system, and a network management system.

[1460] (Claim 3)

[1461] The information processing system according to claim 1, wherein the input means includes an input form displayed on an information processing terminal.

[1462] "Application Example 1"

[1463] (Claim 1)

[1464] An input method for entering the customer's name,

[1465] A means for receiving the customer name entered through the input means,

[1466] A means of sending requests to obtain customer-related information from multiple external systems,

[1467] Means for analyzing customer-related information received from the aforementioned external system,

[1468] means for generating a format based on the analyzed information,

[1469] A means of displaying the generated format,

[1470] A means of collecting and analyzing security-related information from external systems,

[1471] Means for generating analyzed security-related information,

[1472] A system that includes this.

[1473] (Claim 2)

[1474] The system according to claim 1, further comprising means for generating a security configuration diagram based on the analyzed information.

[1475] (Claim 3)

[1476] The system according to claim 1, wherein the plurality of external systems include a customer relationship management system, a corporate resource planning system, a network management system, and a security information management system.

[1477] "Example 2 of combining an emotion engine"

[1478] (Claim 1)

[1479] An input method for entering the customer's name,

[1480] A means for receiving the customer name entered through the input means,

[1481] An emotion engine means for recognizing the user's emotions based on the customer name entered,

[1482] A means of sending requests to obtain customer-related information from multiple external systems,

[1483] Means for analyzing customer-related information received from the aforementioned external system,

[1484] means for generating a format based on the analyzed information,

[1485] Means for adjusting the format display method based on the emotions recognized by the emotion engine means,

[1486] A means of displaying the generated format,

[1487] A system that includes this.

[1488] (Claim 2)

[1489] The system according to claim 1, further comprising means for generating a network configuration diagram based on the analyzed information.

[1490] (Claim 3)

[1491] The system according to claim 1, wherein the plurality of external systems include a customer relationship management system, a corporate resource planning system, and a network management system.

[1492] "Application example 2 when combining with an emotional engine"

[1493] (Claim 1)

[1494] An input method for entering the customer's name,

[1495] A means for receiving the customer name entered through the input means,

[1496] A means of sending requests to obtain customer-related information from multiple external systems,

[1497] Means for analyzing customer-related information received from the aforementioned external system,

[1498] means for generating a format based on the analyzed information,

[1499] Means for adjusting the display content based on emotional information recognized through the aforementioned means,

[1500] A means of displaying the generated format,

[1501] A system that includes this.

[1502] (Claim 2)

[1503] The system according to claim 1, further comprising means for generating a network configuration diagram based on the analyzed information.

[1504] (Claim 3)

[1505] The system according to claim 1, wherein the plurality of external systems include a customer relationship management system, a corporate resource planning system, and a network management system. [Explanation of Symbols]

[1506] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input method for entering the customer's name, A means for receiving the customer name entered through the input means, A means of sending requests to obtain customer-related information from multiple external systems, Means for analyzing customer-related information received from the aforementioned external system, means for generating a format based on the analyzed information, A means of displaying the generated format, A system that includes this.

2. The system according to claim 1, further comprising means for generating a network configuration diagram based on the analyzed information.

3. The system according to claim 1, wherein the plurality of external systems include a customer relationship management system, a corporate resource planning system, and a network management system.

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